Biology subjects

Liu, F.

Publications and source records attributed to Liu, F..

At least 19 recordsLinked to original sources

bioRxiv2018

Integrated in vivo quantitative proteomics and nutrient tracing reveals age-related metabolic rewiring of pancreatic β-cell function

Pancreatic {beta}-cell physiology changes substantially throughout life; yet, the mechanisms that drive these changes are poorly understood. Here, we performed comprehensive in vivo quantitative proteomic profiling of pancreatic islets from adolescent and one-year-old mice. The analysis revealed striking differences in abundance of enzymes controlling glucose metabolism. We show that these changes in protein abundance are associated with higher activities of glucose metabolic enzymes involved in coupling factor generation as well as increased activity of the coupling factor-dependent amplifying pathway of insulin secretion. Nutrient tracing and targeted metabolomics demonstrated accelerated accumulation of glucose-derived metabolites and coupling factors in islets from one-year-old mice, indicating that age-related changes in glucose metabolism contribute to improved glucose-stimulated insulin secretion with age. Together, our study provides the first in-depth characterization of age-related changes in the islet proteome and establishes metabolic rewiring as an important mechanism for age-associated changes in {beta}-cell function.

physiology↗

bioRxiv2018

Differential gene expression, including Sjfs800, in Schistosoma japonicum females before, during, and after male-female pairing

Schistosomiasis is a prevalent but neglected tropical disease caused by parasitic trematodes of the genus Schistosoma, with the primary disease-causing species being S. haematobium, S. mansoni, and S. japonicum. Male-female pairing of schistosomes is necessary for sexual maturity and the production of a large number of eggs, which are primarily responsible for schistosomiasis dissemination and pathology. Here, we used microarray hybridization, bioinformatics, quantitative PCR, in situ hybridization, and gene silencing assays to identify genes that play critical roles in S. japonicum reproduction biology, particularly in vitellarium development, a process that affects male-female pairing, sexual maturation, and subsequent egg production. Microarray hybridization analyses generated a comprehensive set of genes differentially transcribed before and after male-female pairing. Although the transcript profiles of females were similar 16 and 18 days after host infection, marked gene expression changes were observed at 24 days. The 30 most abundantly transcribed genes on day 24 included those associated with vitellarium development. Among these, genes for female-specific 800 (fs800), eggshell precursor protein, and superoxide dismutase (cu-zn-SOD) were substantially upregulated. Our in situ hybridization results in female S. japonicum indicated that cu-zn-SOD mRNA was highest in the ovary and vitellarium, eggshell precursor protein mRNA was expressed in the ovary, ootype, and vitellarium, and Sjfs800 mRNA was observed only in the vitellarium, localized in mature vitelline cells. Knocking down the Sjfs800 gene in female S. japonicum by approximately 60% reduced the number of mature vitelline cells, decreased rates of pairing and oviposition, and decreased the number of eggs produced in each male-female pairing by about 50%. These results indicate that Sjfs800 is essential for vitellarium development and egg production in S. japonicum and suggest that Sjfs800 regulation may provide a novel approach for the prevention or treatment of schistosomiasis.\n\nAuthor SummarySchistosomiasis is a common but largely unstudied tropical disease caused by parasitic trematodes of the genus Schistosoma. The eggs of schistosomes are responsible for schistosomiasis transmission and pathology, and the production of these eggs is dependent on the pairing of females and males. In this study, we determined which genes in Schistosoma japonicum females were differentially expressed before and after pairing with males, identifying the 30 most abundantly expressed of these genes. Among these 30 genes, we further characterized those in female S. japonicum that were upregulated after pairing and that were related to reproduction and vitellarium development, a process that affects male-female pairing, sexual maturation, and subsequent egg production. We identified three such genes, S. japonicum female-specific 800 (Sjfs800), eggshell precursor protein, and superoxide dismutase, and confirmed that the mRNAs for these genes were primarily localized in reproductive structures. By using gene silencing techniques to reduce the amount of Sjfs800 mRNA in females by about 60%, we determined that Sjfs800 plays a key role in development of the vitellarium and egg production. This finding suggests that regulation of Sjfs800 may provide a novel approach to reduce egg counts and thus aid in the prevention or treatment of schistosomiasis.

genomics↗

bioRxiv2018

Quantitative Analysis of Interactive Behavior of Mitochondria and Lysosomes Using Structured Illumination Microscopy

Super-resolution optical microscopy has extended the spatial resolution of cell biology from the cellular level to the nanoscale, enabling the observation of the interactive behavior of single mitochondria and lysosomes. Quantitative parametrization of interaction between mitochondria and lysosomes under super-resolution optical microscopy, however, is currently unavailable, which has severely limited our understanding of the molecular machinery underlying mitochondrial functionality. Here, we introduce an M-value to quantitatively investigate mitochondria and lysosome contact (MLC) and mitophagy under structured illumination microscopy. We found that the M-value for an MLC is typically less than 0.4, whereas in mitophagy it ranges from 0.5 to 1.0. This system permits further investigation of the detailed molecular mechanism governing the interactive behavior of mitochondria and lysosomes.

cell biology↗

bioRxiv2018

Cross-linking/Mass Spectrometry: A Community-Wide, Comparative Study Towards Establishing Best Practice Guidelines

The number of publications in the field of chemical cross-linking combined with mass spectrometry (XL-MS) to derive constraints for protein three-dimensional structure modeling and to probe protein-protein interactions has largely increased during the last years. As the technique is now becoming routine for in vitro and in vivo applications in proteomics and structural biology there is a pressing need to define protocols as well as data analysis and reporting formats that are generally accepted in the field and that have shown to lead to high-quality results. This first, community-based harmonization study on XL-MS is based on the results of 32 groups participating worldwide. The aim of this paper is to summarize the status quo of XL-MS and to compare and evaluate existing cross-linking strategies. From the results obtained, common protocols will be established. Our study serves as basis for establishing best practice guidelines in the field for conducting cross-linking experiments, performing data analysis, and reporting formats with the ultimate goal of assisting scientists to generate accurate and reproducible XL-MS results.

biochemistry↗

bioRxiv2018

Different capsid-binding patterns of the β-herpesvirus-specific tegument protein pp150 (pM32/pUL32) in murine and human cytomegaloviruses

The phosphoprotein pp150 is a structurally, immunogenically, and regulatorily important capsid-associated tegument protein abundant in {beta}-herpesviruses including cytomegaloviruses (CMV), but absent in -herpesviruses and {Gamma}-herpesviruses. In human CMV (HCMV), bridging across each triplex and three adjacent major capsid proteins (MCPs) is a group of three pp150 subunits in a \"{bigtriangleup}\"-shaped fortifying configuration, 320 of which encase and stabilize the genome-containing capsid. Because murine CMV (MCMV) has been used as a model for HCMV pathogenesis and therapeutic studies, one might expect that pp150 and the capsid in MCMV and HCMV have similar structures. Here, by cryoEM and sub-particle reconstructions, we have obtained structures of MCMV capsid and pp150 at near atomic resolutions and built their atomic models. Surprisingly, the capsid-binding patterns of pp150 differ between HCMV and MCMV despite their highly similar capsid structures. In MCMV, pp150 is absent on triplex Tc and exists as a \"{Lambda}\"-shaped dimer on other triplexes, leading to only 260 groups of two pp150 subunits per capsid in contrast to 320 groups of three pp150 subunits encasing each HCMV capsid. Many more amino acids contribute to pp150-pp150 interactions in MCMV than in HCMV, making MCMV pp150 dimer inflexible thus incompatible to instigate triplex Tc-binding as observed in HCMV. While pp150 is essential in HCMV, pp150-deleted MCMV mutants remained viable though with attenuated infectivity and exhibiting defects in retaining viral genome. These results support targeting capsid proteins, but invalidate targeting pp150, when using MCMV as a model for HCMV pathogenesis and therapeutic studies.\n\nImportanceCMV infection is a leading viral cause of congenital birth defects and often responsible for life-threating complications in immunocompromised individuals like AIDS and post-organ transplantation patients. Absence of effective vaccines and potent drugs against CMV infections has motivated animal-based studies, mostly based on the mouse model with MCMV, both for understanding pathogenesis of CMV infections and for developing therapeutic strategies. Here, we present the first atomic structures of MCMV and show that the organization patterns of capsid-associated tegument protein pp150 between human and mouse CMV are different despite their highly similar capsid structures. Our functional studies demonstrate that deleting pp150 does not eliminate MCMV infection in contrast to pp150s essential role in HCMV infections. These results thus establish the validity to target capsid proteins, but raise concerns to target pp150, when using MCMV as HCMV model for pathogenesis and therapeutic studies.

microbiology↗

bioRxiv2018

Population based hospitalization burden of laboratory-confirmed hand, foot and mouth disease caused by multiple enterovirus serotypes in southern China

BackgroundHand, foot and mouth disease (HFMD) is spread widely across Asia, and the hospitalization burden is as yet not well understood. Here, we estimated serotype-specific and age-specific hospitalization rates of HFMD in Southern China.\n\nMethodsWe enrolled pediatric patients admitted to 3/3 county-level hospitals and 3/23 township level hospitals in Anhua county, Hunan (CN) with HFMD, and collected samples to identify enterovirus serotypes by RT-PCRs between October 2013 and September 2016. The information of other eligible but un-enrolled patients were retrospectively collected from the same six hospitals. Monthly number of hospitalizations for all causes was collected from each of 23 township level hospitals to extrapolate hospitalizations associated with HFMD among these.\n\nResultsDuring the three years, an estimated 3,236 pediatric patients were hospitalized with lab-confirmed HFMD, and among these only one patient was severe. The mean hospitalization rates were 660 (95% CI: 638-684) per 100,000 person-years for lab-confirmed HFMD, with higher rates among CV-A16 and CV-A6 associated HFMD (213 vs 209 per 100,000 person-years), and lower among EV-A71, CV-A10 and other enteroviruses associated HFMD (134, 39 and 66 per 100,000 person-years, p<0.001). Children aged 12-23 months had the highest hospitalization rates (3,594/100,000 person-years), followed by those aged 24-35 months (1,828/100,000 person-years) and 6-11 months (1,572/100,000 person-years). Compared with other serotypes, CV-A6-associated hospitalizations were evident at younger ages.\n\nConclusionsOur study indicates a substantial hospitalization burden associated with non-severe HFMD in a rural county in southern China. Future mitigation policies should take into account the disease burden identified, and optimize interventions for HFMD.

epidemiology↗

bioRxiv2018

Toward deciphering developmental patterning with deep neural network

Complex biological functions are carried out by the interaction of genes and proteins. Uncovering the gene regulation network behind a function is one of the central themes in biology. Typically, it involves extensive experiments of genetics, biochemistry and molecular biology. In this paper, we show that much of the inference task can be accomplished by a deep neural network (DNN), a form of machine learning or artificial intelligence. Specifically, the DNN learns from the dynamics of the gene expression. The learnt DNN behaves like an accurate simulator of the system, on which one can perform in-silico experiments to reveal the underlying gene network. We demonstrate the method with two examples: biochemical adaptation and the gap-gene patterning in fruit fly embryogenesis. In the first example, the DNN can successfully find the two basic network motifs for adaptation - the negative feedback and the incoherent feed-forward. In the second and much more complex example, the DNN can accurately predict behaviors of essentially all the mutants. Furthermore, the regulation network it uncovers is strikingly similar to the one inferred from experiments. In doing so, we develop methods for deciphering the gene regulation network hidden in the DNN "black box". Our interpretable DNN approach should have broad applications in genotype-phenotype mapping. SignificanceComplex biological functions are carried out by gene regulation networks. The mapping between gene network and function is a central theme in biology. The task usually involves extensive experiments with perturbations to the system (e.g. gene deletion). Here, we demonstrate that machine learning, or deep neural network (DNN), can help reveal the underlying gene regulation for a given function or phenotype with minimal perturbation data. Specifically, after training with wild-type gene expression dynamics data and a few mutant snapshots, the DNN learns to behave like an accurate simulator for the genetic system, which can be used to predict other mutants behaviors. Furthermore, our DNN approach is biochemically interpretable, which helps uncover possible gene regulatory mechanisms underlying the observed phenotypic behaviors.

developmental biology↗

bioRxiv2018

Inductive reasoning differs between taxonomic and thematic contexts: Electrophysiological evidence

Inductive reasoning can be performed in different contexts, but it is unclear whether the neural mechanism of inductive reasoning performed in a thematic context (e.g., panda has x, so bamboo has x) is the same as that performed in a taxonomic context (e.g., panda has x, so bear has x). In the present study, participants were required to judge whether a conclusion was acceptable or not based on its premise, for which the taxonomic or thematic distances between premise and conclusion objects were either far or near. The ERP results indicated that the effect of reasoning context (taxonomic vs. thematic) was initially observed in the P2 component; while the distance effect (far vs. near) was observed in N400 and late components. Moreover, the distance effect on thematic-based inductive reasoning was found in the frontal and frontal-central brain regions, while the distance effect in taxonomic-based inductive reasoning conditions was found in the central-parietal and parietal regions. These results support the view that inductive reasoning is performed differently under different semantic contexts.

neuroscience↗

bioRxiv2018

Pleotropic effects of PPARD accelerate colorectal tumor progression and invasion

Colorectal carcinogenesis (CRC) progression requires additional molecular mechanisms to APC mutations/aberrant {beta}-catenin signaling. PPARD is a druggable ligand-activated nuclear receptor that regulates essential genes involved in cell fate. PPARD is upregulated in intestinal epithelial cells (IECs) of human colorectal adenomas and adenocarcinomas. The mechanistic significance of PPARD upregulation in CRC remains unknown. Here we show that targeted PPARD overexpression in IECs of mice strongly augmented {beta}-catenin activation via BMP7/TAK1 signaling, promoted intestinal tumorigenesis in Apcmin mice, and accelerated CRC progression and invasiveness in mice with IEC-targeted Apc{Delta}580 mutation. Human CRC invasive fronts had higher PPARD expression than their paired adenomas. A PPARD agonist (GW501516) enhanced APC{Delta}580 mutation-driven CRC, while a PPARD antagonist (GSK3787) suppressed it. Functional proteomics analyses and subsequent validation studies uncovered PPARD upregulation of multiple pro-invasive pathways that drive CRC progression (e.g. PDGFR{beta}, AKT1, CDK1 and EIF4G1). Our results identify novel mechanisms by which PPARD promotes CRC invasiveness and provide the rational for the development of PPARD antagonists to suppress CRC.

cancer biology↗

bioRxiv2018

Structural variability and functional association in the epiphytic bacteria assemblies of freshwater macrophytes (Myriophyllum spicatum)

The underlying principles influencing bacteria community assembly have long been of interest in the field of microbial ecology. Environmental heterogeneity is believed to be important in controlling the uniqueness and variability of communities. However, little is known about the influence of the host macrophytes on epiphytic bacteria assembly processe. Here, we produced two contrasting artificial water environments (eutrophic and oligotrophic) for reciprocal transplant experiment of Myriophyllum spicatum, to recover the colonization of epiphytic bacteria accompanied with plants growth. Comparative analysis addressed a higher species diversity in epiphytic bacteria than in bacterioplankton, and the highest microbiome richness in sediment. Our data revealed that the organization of epiphytic bacterial community was interfered by both plant status (i.e. branch number, net photosynthesis rate etc.) and water bodies (i.e. total phosphate, total nitrogen, pH etc.) while plant status effected the assembly in priority to water. 16S rRNA sequencing further indicated that the epiphytic assemblies were motivated by functionalization and interplay with hosts as a whole. The results complemented new evidences for the lottery process in the epiphytic bacteria assembly traits and shed insights into the assembly patterns referring to functional adaptation across epiphytic bacteria and macrophytes.\n\nImportanceA robust understanding of inter-adaptation between microbiome and the host plants have been established basing on vast majority of researches. However, great efforts were made mostly on rhizosphere microbiome. By contrast, referring to another representative group, macrophytes who composed of the freshwater ecosystem were relatively less investigated on such issue. Our study pioneered the experimental operation to interrogate the triadic relationship among macrophytes, epiphytic bacteria and water body. The research present here showed significant exemplar on discussion of plant associate bacteria adaptation taking account of host colonization as well as the epiphytes. The results expand the hypotheses of bacteria assembly principle and provides potential leads on understanding of plant - microbe interactions.

microbiology↗

bioRxiv2018

Comparative analysis of droplet-based ultra-high-throughput single-cell RNA-seq systems

Since its establishment in 2009, single-cell RNA-seq has been a major driver behind progress in biomedical research. In developmental biology and stem cell studies, the ability to profile single cells confers particular benefits. While most studies still focus on individual tissues or organs, the recent development of ultra-high-throughput single-cell RNA-seq has demonstrated potential power in characterizing more complex systems or even the entire body. However, although multiple ultra-high-throughput single-cell RNA-seq systems have attracted attention, no systematic comparison of these systems has been performed. Here, we focus on three widely used droplet-based ultra-high-throughput single-cell RNA-seq systems, inDrop, Drop-seq, and 10X Genomics Chromium. While each system is capable of profiling single-cell transcriptomes, their detailed comparison revealed the distinguishing features and suitable applications for each system.

genomics↗

bioRxiv2018

Super-resolution tracking of mitochondrial dynamics with a third-row transition metal complex dye

Combining luminescent transition metal complex (LTMC) with super-resolution microscopy is an excellent strategy for the long-term visualization of the dynamics of subcellular structures in living cells. However, it remains unclear whether iridium(III) complexes are applicable for a particular type of super-resolution technique, structured illumination microscopy (SIM), to image subcellular structures.\n\nAs described herein, we developed an iridium(III) dye, to track mitochondrial dynamics in living cells under SIM. The dye demonstrated excellent specificity and photostability and satisfactory cell permeability. While using SIM to image mitochondria, we achieved an approximately 80-nm resolution that allowed the clear observation of the structure of mitochondrial cristae. We used the dye to monitor and quantify mitochondrial dynamics relative to lysosomes, including fusion involved in mitophagy, and newly discovered mitochondria-lysosome contact (MLC) under different conditions. MLC remained intact and fusion vanished when five receptors, p62, NDP52, OPTN, NBR1, and TAX1BP1, were knocked out, suggesting that these two processes are independence.

biophysics↗

bioRxiv2018

Convolutional neural network models of V1 responses to complex patterns

In this study, we evaluated the convolutional neural network (CNN) method for modeling V1 neurons of awake macaque monkeys in response to a large set of complex pattern stimuli. CNN models outperformed all the other baseline models, such as Gabor-based standard models for V1 cells and various variants of generalized linear models. We then systematically dissected different components of the CNN and found two key factors that made CNNs outperform other models: thresholding nonlinearity and convolution. In addition, we fitted our data using a pre-trained deep CNN via transfer learning. The deep CNNs higher layers, which encode more complex patterns, outperformed lower ones, and this result was consistent with our earlier work on the complexity of V1 neural code. Our study systematically evaluates the relative merits of different CNN components in the context of V1 neuron modeling.

neuroscience↗

bioRxiv2018

Cullin1 represses systematic inflammasome activation by binding and catalyzing NLRP3 ubiquitination

Activation of the NLRP3 inflammasome is a key process of host immune response, the first line of defense against cellular stresses and pathogen infections. However, excessive inflammasome activation damages the hosts, and thus it must be precisely controlled. The mechanism underlying the repression of systematic inflammasome activation remains largely unknown. This study reveals that CUL1, a key component of the SCF E3 ligase, plays a critical role in regulation of the inflammasome. CUL1 suppresses the inflammasome activation in HEK293T cells, inhibits endogenous NLRP3 in macrophages, and represses inflammatory responses in C57BL/6 mice. Under normal physiological conditions, CUL1 interacts with NLRP3 to disrupt the inflammasome assembly, and catalyzes NLRP3 ubiquitination to repress the inflammasome activation. In response to inflammatory stimuli, CUL1 disassociates from NLRP3 to release the repression of NLRP3 inflammasome activation. This work reveals a distinct mechanism underlying the repression of inflammasome activation under physiological conditions and the induction of inflammasome activation in response to inflammatory stimuli, and thus provides insights into the prevention and treatment of infectious and inflammatory diseases.

immunology↗

bioRxiv2018

Meta-microRNAs as potential noninvasive markers for early diagnosis of Alzheimer’s disease

IntroductionThe aim of this study was to investigate the potential role of a microRNA panel as early diagnostic markers for Alzheimers disease (AD).\n\nMethodsThe differentially expressed serum microRNAs were screened with microarray among cognitively normal controls (CNC), mild cognitive impairment (MCI), and AD. QRT-PCR assay was applied to evaluate differentially expressed microRNAs with two independent cohorts including 202 participants. Logistic regression model based on microRNA panel was constructed using a training cohort and then validated using an independent cohort.\n\nResultsFirst, four differentially expressed serum microRNAs (let-7g, miR-197, miR-126 and miR-29a) were found, which expressions were positively correlated with mini mental state examination (MMSE) score. Second, a microRNA panel with the four microRNAs demonstrated good diagnostic performance for MCI and AD with 84% and 92% accuracy. Third, when combined with MMSE score, the diagnostic performance of the microRNA panel was further improved.\n\nDiscussionBlood microRNAs are potential AD biomarkers that may lead to new diagnostic strategies.

neuroscience↗

bioRxiv2018

Large-scale two-photon imaging revealed super-sparse population codes in V1 superficial layer of awake monkeys

Efficient coding has been proposed as a general principle for the sensory systems. The efficient coding hypothesis predicts that neuronal population responses should be sparse, but limited by the measurement techniques, the precise estimates of the population sparseness of visual cortical neurons are still uncertain. Here, we employed large-scale two-photon calcium imaging to examine the neuronal population activities in V1 superficial layers of awake macaques in response to a large set of natural images. We found that only 0.5% of these neurons on average responded strongly to any given natural image with response strength above half of their individual peak responses, which is more than tenfold sparse over those reported by early studies. We further showed that these sparse population activities contain sufficient information for discriminating images with high accuracy. This study provided the first accurate measure of sparseness in V1 neuronal population responses, which support super-sparse neural codes in primates.

neuroscience↗

bioRxiv2018

Epigenetic Drift of H3K27me3 in Aging Links Glycolysis to Healthy Longevity

Epigenetic alteration has been implicated in aging. However, the mechanism by which epigenetic change impacts aging is unclear. H3K27me3, a highly conserved histone modification signifying transcriptional repression, is marked and maintained by Polycomb Repressive Complexes (PRCs). Here, we explore the mechanism by which age-modulated increase of H3K27me3 impacts adult lifespan. Using Drosophila, we reveal that aging leads to loss of fidelity in epigenetic marking and drift of H3K27me3 and consequential reduction in the expression of glycolytic genes with negative effects on energy production and redox state. Moreover, we show that a reduction of H3K27me3 by PRCs-deficiency promotes glycolysis and healthy lifespan. While perturbing glycolysis by gene mutation diminishes the pro-lifespan benefits mediated by PRCs-deficiency, transgenic increase of glycolytic genes in wild-type animals extends longevity. Together, we propose that epigenetic drift of H3K27me3 defines a new aging mechanism and that stimulation of glycolysis promotes metabolic health and longevity.

molecular biology↗

bioRxiv2018

Task-Related EEG Source Localization via Graph Regularized Low-Rank Representation Model

To infer brain source activation patterns under different cognitive tasks is an integral step to understand how our brain works. Traditional electroencephalogram (EEG) Source Imaging (ESI) methods usually do not distinguish task-related and spurious non-task-related sources that jointly generate EEG signals, which inevitably yield misleading reconstructed activation patterns. In this research, we argue that the task-related source signal intrinsically has a low-rank property, which is exploited to to infer the true task-related EEG sources location. Although the true task-related source signal is sparse and low-rank, the contribution of spurious sources scattering over the source space with intermittent activation patterns makes the actual source space lose the low-rank property. To reconstruct a low-rank true source, we propose a novel ESI model that involves a spatial low-rank representation and a temporal Laplacian graph regularization, the latter of which guarantees the temporal smoothness of the source signal and eliminate the spurious ones. To solve the proposed model, an augmented Lagrangian objective function is formulated and an algorithm in the framework of alternating direction method of multipliers is proposed. Numerical results illustrate the effectiveness of the proposed method in terms of reconstruction accuracy with high effciency.

bioinformatics↗