Biology subjects

Lu, H.

Publications and source records attributed to Lu, H..

At least 253 records · Page 14Linked to original sources

bioRxiv2020

Reduction of neuronal activity mediated by blood-vessel regression in the brain

The brain vasculature supplies neurons with glucose and oxygen, but little is known about how vascular plasticity contributes to brain function. Using longitudinal in vivo imaging, we reported that a substantial proportion of blood vessels in the adult brain sporadically occluded and regressed. Their regression proceeded through sequential stages of blood-flow occlusion, endothelial cell collapse, relocation or loss of pericytes, and retraction of glial endfeet. Regressing vessels were found to be widespread in mouse, monkey and human brains. Both brief occlusions of the middle cerebral artery and lipopolysaccharide-mediated inflammation induced an increase of vessel regression. Blockage of leukocyte adhesion to endothelial cells alleviated LPS-induced vessel regression. We further revealed that blood vessel regression caused a reduction of neuronal activity due to a dysfunction in mitochondrial metabolism and glutamate production. Our results elucidate the mechanism of vessel regression and its role in neuronal function in the adult brain.

neuroscience↗

bioRxiv2020

Long-lasting salt bridges provide the anchoring mechanism of oncogenic KRas-4B at cell membranes

Ras is a family of related proteins participating in all animal cell lineages and organs. Ras proteins work as GDP-GTP binary switches and regulate cytoplasmic signalling networks that are able to control several cellular processes, playing an essential role in signal transduction pathways involved in cell growth, differentiation and survival so that overacting Ras signalling can lead to cancer. One of the hardest challenges to face is, with more than hundred different missense mutations found in cancer, the design of mutation-selective therapeutic strategies. In this work, a G12D mutated farnesylated GTP bound KRas-4B protein has been simulated at the interface of a DOPC/DOPS/cholesterol model anionic cell membrane at the all-atom level. A specific long-lasting salt bridge connection between farnesyl and the hypervariable region of the protein has been identified as the main mechanism responsible of the binding of oncogenic farnesylated KRas-4B to the cell membrane, since this particular bond is absent in both wild-type and oncogenic methylated species of KRas-4B. This finding may lead to a deeper understanding of the mechanisms of protein binding and eventual growing and spreading inside cell membranes. From free energy landscapes obtained by well-tempered metadynamics simulations, we have characterised local and global minima of KRas-4B binding to the cell membrane revealing the main pathways between anchored and released states.

biophysics↗

bioRxiv2020

Genetic signatures for lineage/sublineage classification of HPV16, 18, 52 and 58 variants

Increasing evidences indicate that high-risk HPV variants are heterogeneous in carcinogenicity and ethnic dispersion. In this work, we identified genetic signatures for convenient determination of lineage/sublineage of HPV16, 18, 52 and 58 variants. Using publicly available genomes, we found that E2 of HPV16, L2 of HPV18, L1 and LCR of HPV52, and L2, LCR and E1 of HPV58 contain the proper genetic signature for lineage/sublineage classification. Sets of hierarchical signature nucleotide positions (SNPs) were further confirmed for high accuracy (>98%) by classifying HPV genomes obtained from Chinese females, which included 117 HPV16 variants, 48 HPV18 variants 117 HPV52 variants and 89 HPV58 variants. The circulation of HPV variants posing higher cancer risk in Eastern China, such as HPV16 A4 and HPV58 A3, calls for continuous surveillance in this region. The marker genes and signature nucleotide positions may facilitate cost-effective diagnostic detections of HPV variants in clinical settings.

evolutionary biology↗

bioRxiv2020

Inter-determination of blood metabolite levels and gut microbiome supported by Mendelian randomization

The gut microbiome has been implicated in a variety of physiological states, but controversy over causality remains unresolved. Here, we performed bidirectional Mendelian randomization (MR) analyses on 3,432 Chinese individuals with whole genome, whole metagenome, anthropometric, and blood metabolic trait data. We identified 58 causal relationships between the gut microbiome and blood metabolites, and replicated 43 of them. Increased relative abundances of fecal Oscillibacter and Alistipes were causally linked to decreased triglyceride concentration. Conversely, blood metabolites such as glutamic acid appeared to decrease fecal Oxalobacter, and members of Proteobacteria were influenced by metabolites such as 5-methyltetrahydrofolic acid, alanine, glutamate, and selenium. Two-sample MR with data from Biobank Japan partly corroborated results with triglyceride and with uric acid, and also provided causal support for published fecal bacterial markers for cancer and cardiovascular diseases. This study illustrates the value of human genetic information to help prioritize gut microbial features for mechanistic and clinical studies.

genetics↗

bioRxiv2020

Single-cell screening of SARS-CoV-2 target cells in pets, livestock, poultry and wildlife

A few animals have been suspected to be intermediate hosts of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, a large-scale single-cell screening of SARS-CoV-2 target cells on a wide variety of animals is missing. Here, we constructed the single-cell atlas for 11 representative species in pets, livestock, poultry, and wildlife. Notably, the proportion of SARS-CoV-2 target cells in cat was found considerably higher than other species we investigated and SARS-CoV-2 target cells were detected in multiple cell types of domestic pig, implying the necessity to carefully evaluate the risk of cats during the current COVID-19 pandemic and keep pigs under surveillance for the possibility of becoming intermediate hosts in future coronavirus outbreak. Furthermore, we screened the expression patterns of receptors for 144 viruses, resulting in a comprehensive atlas of virus target cells. Taken together, our work provides a novel and fundamental strategy to screen virus target cells and susceptible species, based on single-cell transcriptomes we generated for domesticated animals and wildlife, which could function as a valuable resource for controlling current pandemics and serve as an early warning system for coping with future infectious disease threats.

cell biology↗

bioRxiv2020

Medial Prefrontal Cortex Interacts with the Anteromedial Thalamus in Motivation and Dopaminergic Activity

How does the prefrontal cortex (PFC) regulate motivated behavior? Our experiments characterize the circuits of the PFC regulating motivation, reinforcement and dopamine activity, revealing a novel cortico-thalamic loop. The stimulation of medial PFC (mPFC) neurons activated many downstream regions, as shown by functional MRI. Axonal terminal stimulation of mPFC neurons in downstream regions, including the anteromedial thalamic nucleus (AM), reinforced behavior and activated midbrain dopaminergic neurons. The stimulation of AM neurons projecting to the mPFC also reinforced behavior and activated dopamine neurons, and mPFC and AM showed a positive-feedback loop organization. Reciprocal excitatory functional connectivity, as well as co-activation of the two regions, was found in human participants who watched reinforcing videos. Our results suggest that this cortico-thalamic loop regulates motivation, reinforcement and dopaminergic neuron activity.

neuroscience↗

bioRxiv2020

p53 induces ARTS to promote mitochondrial apoptosis

Apoptosis Related protein in TGF-{beta} Signaling pathway (ARTS) was originally discovered in cells undergoing apoptosis in response to TGF-{beta}, but ARTS also acts downstream of many other apoptotic stimuli. ARTS induces apoptosis by antagonizing the anti-apoptotic proteins XIAP and Bcl-2. Here, we identified the pro-apoptotic Sept4/ARTS gene as a p53-responsive target gene. Ectopic p53 and a variety of p53-inducing agents increased both mRNA and protein levels of ARTS, whereas ablation of p53 reduced ARTS expression in response to multiple stress conditions. Also, {gamma}-irradiation induced p53-dependent ARTS expression in mice. Consistently, p53 binds to the responsive DNA element on the ARTS promoter and transcriptionally activated the promoter-driven expression of a luciferase reporter gene. Interestingly, ARTS binds to and sequesters p53 at mitochondria, enhancing the interaction of the latter with Bcl-XL. Ectopic ARTS markedly augments DNA damage stress- or Nutlin-3-triggered apoptosis, while ablation of ARTS preferentially impairs p53-induced apoptosis. Altogether, these findings demonstrate that ARTS collaborates with p53 in mitochondria-engaged apoptosis.

cancer biology↗

bioRxiv2020

Supramammillary neurons projecting to the septum regulate dopamine and motivation for environmental interaction

The supramammillary region (SuM) is a posterior hypothalamic structure, known to regulate hippocampal theta oscillations and arousal. However, recent studies reported that the stimulation of SuM neurons with neuroactive chemicals, including substances of abuse, is reinforcing. We conducted experiments to illuminate how SuM neurons mediate such effects. The excitation of SuM glutamatergic (GLU) neurons was reinforcing in mice; this effect was relayed by the projections to septal GLU neurons. SuM neurons were active during exploration and approach behavior and diminished activity during sucrose consumption. Consistently, inhibition of SuM neurons disrupted approach responses, but not sucrose consumption. Such functions are similar to those of mesolimbic dopamine neurons. Indeed, the stimulation of SuM-to-septum GLU neurons and septum-to-ventral tegmental area (VTA) GLU neurons activated mesolimbic dopamine neurons. We propose that the supramammillo-septo-VTA pathway is important in reinforcement and approach motivation and may play an important role in mood and substance-use disorders.

neuroscience↗

bioRxiv2020

Single-cell atlas of a non-human primate reveals new pathogenic mechanisms of COVID-19

Stopping COVID-19 is a priority worldwide. Understanding which cell types are targeted by SARS-CoV-2 virus, whether interspecies differences exist, and how variations in cell state influence viral entry is fundamental for accelerating therapeutic and preventative approaches. In this endeavor, we profiled the transcriptome of nine tissues from a Macaca fascicularis monkey at single-cell resolution. The distribution of SARS-CoV-2 facilitators, ACE2 and TMRPSS2, in different cell subtypes showed substantial heterogeneity across lung, kidney, and liver. Through co-expression analysis, we identified immunomodulatory proteins such as IDO2 and ANPEP as potential SARS-CoV-2 targets responsible for immune cell exhaustion. Furthermore, single-cell chromatin accessibility analysis of the kidney unveiled a plausible link between IL6-mediated innate immune responses aiming to protect tissue and enhanced ACE2 expression that could promote viral entry. Our work constitutes a unique resource for understanding the physiology and pathophysiology of two phylogenetically close species, which might guide in the development of therapeutic approaches in humans. Bullet pointsO_LIWe generated a single-cell transcriptome atlas of 9 monkey tissues to study COVID-19. C_LIO_LIACE2+TMPRSS2+ epithelial cells of lung, kidney and liver are targets for SARS-CoV-2. C_LIO_LIACE2 correlation analysis shows IDO2 and ANPEP as potential therapeutic opportunities. C_LIO_LIWe unveil a link between IL6, STAT transcription factors and boosted SARS-CoV-2 entry. C_LI

cell biology↗

bioRxiv2020

PremPRI: Predicting the Effects of Single Mutations on Protein-RNA Interactions

Protein-RNA interactions are crucial for many cellular processes, such as protein synthesis and regulation of gene expression. Missense mutations that alter protein-RNA interaction may contribute to the pathogenesis of many diseases. Here we introduce a new computational method PremPRI, which predicts the effects of single mutations occurring in RNA binding proteins on the protein-RNA interactions by calculating the binding affinity changes quantitatively. The multiple linear regression scoring function of PremPRI is composed of 11 sequence- and structure-based features, and is parameterized on 248 mutations from 50 protein-RNA complexes. Our model shows a good agreement between calculated and experimental values of binding affinity changes with Pearson correlation coefficient of 0.72 and the corresponding root-mean-square error of 0.76 kcal mol-1, outperforming three other available methods. PremPRI can be used for finding functionally important variants, understanding the molecular mechanisms, and designing new protein-RNA interaction inhibitors. PremPRI is freely available at http://lilab.jysw.suda.edu.cn/research/PremPRI/.

bioinformatics↗

bioRxiv2020

PremPS: Predicting the Effects of Single Mutations on Protein Stability

Protein stability is related to its functional activities, and effect on stability or misfolding could be one of the major disease-causing mechanisms of missense mutations. Here we developed a novel machine learning computational method PremPS, which predicts the effects of single mutations on protein stability by calculating the changes in unfolding Gibbs free energy. PremPS uses only ten evolutionary- and structure-based features and is parameterized on five thousand mutations. Our approach outperforms previous methods and shows a considerable improvement in estimating the effects of mutations increasing protein stability. In addition, PremPS presents an outstanding performance in predicting the pathogenicity of missense mutations using an experimental dataset composed of two thousand non-neutral and neutral mutations. PremPS can be applied to many tasks, including finding functionally important variants, revealing the molecular mechanisms of functional influences and protein design. It is freely available at https://lilab.jysw.suda.edu.cn/research/PremPS/. Key PointsO_LIConsiderable improvement in estimating the effects of mutations increasing protein stability; C_LIO_LIComprehensive comparison with other 25 computational methods on different test sets; C_LIO_LIAn outstanding performance in predicting the pathogenicity of missense mutations; C_LIO_LIPremPS employs only ten distinct features belonging to six categories, and the most important feature describes evolutionary conservation of the site; C_LIO_LIThe webserver allows to do large-scale mutational scanning and takes about ten minutes to perform calculations for one thousand mutations from a normal size protein. C_LI

bioinformatics↗

bioRxiv2020

Investigation in scanning beampattern generated by resonance cavities

The previous study has reported that the presence of a small flap in the Brown Long-Eared Bat (Plecotus auritus) generate useful spatial information by the frequency-driven beam scanning. However, it did not investigate the beampattern generating mechanism of the flap. In this study, according to the dipole equivalence principle, the two resonance cavities split by the flap are simplified to a dipole source with certain vibration orientation. The analytical solution of the dipole shows obvious frequency-driven sidelobe scanning in the beampattern, which matches the numerical results obtained from the pinna quite well. The results support the hypothesis that the frequency-driven sidelobe scanning is generated by the resonance in the two cavities split by the flap. This method can be applied to design a reflector antenna with small geometric structures for splitting existent resonance cavities to meet requirements of beam scanning.

biophysics↗

bioRxiv2020

An engineered Abcb4 expressing model reveals the central role of NF-κB in the regulation of drug resistance in zebrafish

Multidrug resistance (MDR) represents the major cause of unsatisfaction in the application of chemotherapy for cancer treatment. So far, an in vivo robust high-throughput screening system for anti-tumor drug MDR is still lacking and the molecular mechanisms for MDR still remain elusive. Given a myriad of merits of zebrafish relative to other animal models, we aimed to establish MDR system in zebrafish stably expressing ATP-binding cassette (ATP-cassette) superfamily transporters and study the potential regulatory mechanism. We first constructed a Tg(abcb4:EGFP) transgenic zebrafish stably expressing both Abcb4 and EGFP using Tol2-mediated approach. The expression level of Abcb4 and EGFP was significantly induced when Tg(abcb4:EGFP) transgenic zebrafish embryos were exposed to doxorubicin (DOX) or vincristine (VCR), accompany with a marked decrease in rhodamine B (RhB) accumulation in embryos, which indicates a remarkable increase in drug efflux upon the exposure to DOX or VCR. Mechanistically, AKT and ERK signaling were activated when treated with DOX or VCR. With the application of AKT and ERK inhibitors, the drug resistance phenomena could be reversed with differential responsive effects. Of note, downstream NF-κB played a central role in the regulation of Abcb4-mediated drug resistance. Taken together, the engineered Tg(abcb4:EGFP) transgenic zebrafish model provides a new platform for drug resistance screening in vivo, which could facilitate and accelerate the process of drug development.View Full Text

zoology↗

bioRxiv2020

Predicting Molecular Fingerprint from Electron-Ionization Mass Spectrum with Deep Neural Networks

Electron-ionization mass spectrometry (EI-MS) hyphenated gas chromatography (GC) is the workhorse to analyze volatile compounds in complex samples. The spectral matching method can only identify compounds within spectral database. In response, we present a deep-learning-based approach (DeepEI) for structure elucidation of unknown compound with its EI-MS spectrum. DeepEI employs deep neural networks to predict molecular fingerprint from EI-MS spectrum, and searches molecular structure database with the predicted fingerprints. In addition, a convolutional neural network was also trained to filter the structures in database and improve the identification performance. Our method shows improvement on the competing method NEIMS in identification accuracy on both NIST test dataset and MassBank dataset. Furthermore, DeepEI (spectrum to fingerprint) and NEIMS (fingerprint to spectrum) can be combined to improve identification accuracy.

bioinformatics↗

bioRxiv2020

Deep Learning Enable Untargeted Metabolite Extraction from High Throughput Coverage Data-Independent Acquisition

The sequential window acquisition of all theoretical spectra (SWATH) technique is a specific variant of data-independent acquisition (DIA), which is supposed to increase the metabolite coverage and the reproducibility compared to data-dependent acquisition (DDA). However, SWATH technique lost the direct link between the precursor ion and the fragments. Here, we propose a deep-learning-based approach (DeepSWATH) to reconstruct the association between the MS/MS spectra and their precursors. Comparing with MS-DIAL, the proposed method can extract more accurate spectra with less noise to improve the identification accuracy of metabolites. Besides, DeepSWATH can also handle severe coelution conditions.

bioinformatics↗

bioRxiv2020

Convergence within divergence: insights of wheat adaptation from Triticum population sequencing

Bread wheat expanded its habitats from a small core area of the Fertile Crescent to global environments within [~]10,000 years. Genetic mechanisms of this remarkable evolutionary success are not well understood. By whole-genome sequencing of populations from 25 subspecies within genera Triticum and Aegilops, we identified composite introgression from these wild populations contributing 13%[~]36% of the bread wheat genome, which tremendously increased the genetic diversity of bread wheat and allowed its divergent adaptation. Meanwhile, convergent adaption to human selection showed 2- to 16-fold enrichment relative to random expectation in Triticum species despite their drastic differences in ploidy levels and growing zones, indicating the vital importance of adaptive constraints in the success of bread wheat. These results showed the genetic necessities of wheat as a global crop and provided new perspectives on leveraging adaptation success across species for crop improvement.

genetics↗

bioRxiv2020

Automated Annotation of Cell Identities in Dense Cellular Images

Although identifying cell names in dense image stacks is critical in analyzing functional whole-brain data enabling comparison across experiments, unbiased identification is very difficult, and relies heavily on researchers experiences. Here we present a probabilistic-graphical-model framework, CRF_ID, based on Conditional Random Fields, for unbiased and automated cell identification. CRF_ID focuses on maximizing intrinsic similarity between shapes. Compared to existing methods, CRF_ID achieves higher accuracy on simulated and ground-truth experimental datasets, and better robustness against challenging noise conditions common in experimental data. CRF_ID can further boost accuracy by building atlases from annotated data in highly computationally efficient manner, and by easily adding new features (e.g. from new strains). We demonstrate cell annotation in C. elegans images across strains, animal orientations, and tasks including gene-expression localization, multi-cellular and whole-brain functional imaging experiments. Together, these successes demonstrate that unbiased cell annotation can facilitate biological discovery, and this approach may be valuable to annotation tasks for other systems.

neuroscience↗

bioRxiv2020

Multiple-biological matrices metabolomics identified new metabolite biomarkers for the precise diagnosis of pancreatic cancer and associated tissue metastasis

PurposeTo improve clinical diagnosis and enhance therapeutic outcome, we figure out to identify and validate metabolite biomarkers from the plasma samples of patients with pancreatic cancer that can easily, sensitively and efficiently diagnose the onsite progression, and metastasis of the disease. Experimental DesignWe employed the newly developed precision-targeted metabolomics method to validate that many differential metabolites have the capacity to markedly distinguish patients with pancreatic cancer from healthy controls. To further enhance the specificity and selectivity of metabolite biomarkers, a dozen tumor tissues from PC patients and paired normal tissues were used to clinically validate the biomarker performance. ResultsWe eventually verified five new metabolite biomarkers in plasma (creatine, inosine, beta-sitosterol, sphinganine and glycocholic acid), which can be used to readily diagnose pancreatic cancer in a clinical setting. Excitingly, we proposed a panel biomarker by integrating these five individual metabolites into one pattern, demonstrating much higher accuracy and specificity to precisely diagnose pancreatic cancer than conventional biomarkers (CA125, CA19-9, CA242 and CEA); Moreover, we characterized succinic acid and gluconic acid as having a great capability to monitor the progression and metastasis of pancreatic cancer at different stages. ConclusionsTaken together, this metabolomics method was used to identify and validate metabolite biomarkers that can precisely and sensitively diagnose the onsite progression and metastasis of pancreatic cancer in a clinical setting. Furthermore, such effort should leave clinicians with the correct time frame to facilitate early and efficiently therapeutic interventions, which could largely improve the five-year survival rate of PC patients.

biochemistry↗