Biology subjects

Qin, H.

Publications and source records attributed to Qin, H..

At least 73 records · Page 4Linked to original sources

bioRxiv2022

Virtually the same? Evaluating the effectiveness of remote undergraduate research experiences

In-person undergraduate research experiences (UREs) promote students integration into careers in life science research. In 2020, the COVID-19 pandemic prompted institutions hosting summer URE programs to offer them remotely, raising questions about whether undergraduates who participate in remote research can experience scientific integration. To address this, we investigated indicators of scientific integration for students who participated in remote life science URE programs in summer 2020. We found that these students experienced gains in their scientific self-efficacy and scientific identity similar to results reported for in-person UREs. We also found that these students perceived high benefits and low costs of doing research at the outset of their programs, and their perceptions did not change despite the remote circumstances. Yet, their perceptions differed by program, indicating that programs differentially affected students perceptions of the costs of doing research. Finally, we observed that students with prior research experience made greater gains in self-efficacy and identity, as well as in their perceptions of the alignment of their values with those of the scientific community, in comparison to students with no prior research experience. This finding suggests that additional programming may be needed for undergraduates with no prior experience to benefit from remote research.

scientific communication and education↗

bioRxiv2021

DENA: training an authentic neural network model using Nanopore sequencing data of Arabidopsis transcripts for detection and quantification of N6-methyladenosine on RNA

Models developed using Nanopore direct RNA sequencing data from in vitro synthetic RNA with all adenosine replaced by N6-methyladenosine (m6A), are likely distorted due to superimposed signals from saturated m6A residues. Here, we develop a neural network, DENA, for m6A quantification using the sequencing data of in vivo transcripts from Arabidopsis. DENA identifies 90% of miCLIP-detected m6A sites in Arabidopsis, and obtains modification rates in human consistent to those found by SCARLET, demonstrating its robustness across species. We sequence the transcriptome of two additional m6A-deficient Arabidopsis, mtb and fip37-4, using Nanopore and evaluate their single-nucleotide m6A profiles using DENA.

bioinformatics↗

bioRxiv2021

Biosynthesis of linear protein nanoarrays using the flagellar axoneme

Applications in biotechnology and synthetic biology often make use of soluble proteins, but there are many potential advantages to anchoring enzymes to a stable substrate, including stability and the possibility for substrate channeling. To avoid the necessity of protein purification and chemical immobilization, there has been growing interest in bio-assembly of protein-containing nanoparticles, exploiting the self-assembly of viral capsid proteins or other proteins that form polyhedral structures. But these nanoparticle are limited in size which constrains the packaging and the accessibility of the proteins. The axoneme, the insoluble protein core of the eukaryotic flagellum or cilium, is a highly ordered protein structure that can be several microns in length, orders of magnitude larger than other types of nanoparticles. We show that when proteins of interest are fused to specific axonemal proteins and expressed in living cells, they become incorporated into linear arrays which have the advantages of high protein loading capacity, high stability, and single-step purification with retention of biomass. The arrays can be isolated as membrane enclosed vesicle or as exposed protein arrays. The approach is demonstrated for both fluorescent proteins and enzymes, and in the latter case it is found that incorporation into axoneme arrays provides increased stability for the enzyme.

synthetic biology↗

bioRxiv2021

Active Cell Divisions Generate Exotic Fourfold Orientationally Ordered Phase in Living Tissue

AO_SCPLOWBSTRACTC_SCPLOWMorphogenesis, the process through which genes generate form, establishes tissue scale order as a template for constructing the complex shapes of the body plan. The extensive growth required to build these ordered substrates is fuelled by cell proliferation, which, naively, should destroy order. The active mechanisms that couple cellular and physical processes to generate and maintain global order, thereby reconciling this seeming contradiction, remain elusive. Using live imaging and tissue cartography, we quantitatively analyze the dynamics of fourfold tissue ordering in the crustacean Parhyale hawaiensis. We show that cell divisions are the main drivers of tissue flow leading to a fourfold orientationally ordered phase. Waves of anisotropic cell proliferation propagate across the embryo with precise choreography, such that defects introduced into the nascent lattice by cell divisions are healed by subsequent divisions through active defect climb. Orchestrating cell proliferation rates and orientations enables cell divisions to organize, rather than fluidize, the tissue. The result is a robust, active mechanism for generating global orientational order in a non-equilibrium system that sets the stage for the subsequent development of shape and form.

developmental biology↗

bioRxiv2021

Regulation of brain aging by neutral sphingomyelinase 2

We have shown that deficiency of neutral sphingomyelinase 2 (nSMase2), an enzyme generating the sphingolipid ceramide, improves memory in adult mice. Here, we performed sphingolipid and RNA-seq analyses on the cortex from 10 month-old nSMase2-deficient (fro/fro) and heterozygous (+/fro) mice. fro/fro cortex showed reduced levels of ceramide, particularly in astrocytes. Differentially abundant transcripts included several functionally related groups, with decreases in mitochondrial oxidative phosphorylation and astrocyte activation transcripts, while axon guidance and synaptic transmission transcripts were increased, indicating a role of nSMase2 in oxidative stress, astrocyte activation, and cognition. Experimentally induced oxidative stress decreased the level of glutathione (GSH), an endogenous inhibitor of nSMase2, and increased immunolabeling for ceramide in primary +/fro astrocytes, but not in fro/fro astrocytes. {beta}-galactosidase activity was lower in 5-weeks old fro/fro astrocytes, indicating delayed senescence due to nSMase2 deficiency. In fro/fro cortex, levels of the senescence markers C3b and p27, and the proinflammatory cytokines interleukin 1{beta}, interleukin 6, and tumor necrosis factor were reduced, concurrent with 2-fold decreased phosphorylation of their downstream target, protein kinase Stat3. RNA and protein levels of the ionotropic glutamate receptor subunit 2b (Grin2b or NR2B) were increased by 2-fold, an effect known to enhance cognition. This was consistent with 3.5-fold reduced levels of exosomes carrying miR-223-3p, a micro-RNA downregulating Grin2b. In summary, our data show that nSMase2 deficiency prevents oxidative stress-induced elevation of ceramide and secretion of exosomes by astrocytes that suppress neuronal function, indicating a role of nSMase2 in the regulation of neuroinflammation and cognition during brain aging. Significance statementOxidative stress is associated with brain aging and cognitive decline. The underlying mechanism how oxidative stress impairs brain function is still not clear. We provide evidence that oxidative stress increases ceramide in astrocytes, which is prevented by deficiency of nSMase2, an enzyme that is activated by oxidative stress and generates ceramide from sphingomyelin. Mass spectrometric and transciptomic (RNA-seq) analyses show that in middle aged (10-month old) mouse cortex, nSMase2 deficiency reduces ceramide and increases expression of genes important for synaptic transmission and cognition. Therefore, our data show that oxidative stress-induced activation of nSMase2 and generation of ceramide is significant for cognitive decline during aging.

neuroscience↗

bioRxiv2021

Rescuable effect of R-salbutamol in LPS-induced immune dysfunction of sepsis

Sepsis is a severe life-threatening condition caused by a dysregulated host response to infection. So far, there are no pharmacotherapies to stop sepsis. Salbutamol, a commonly used {beta}2-adrenoreceptor agonist, has found to be potential in regulating immune response dysfunction and exert anti-inflammatory effect. However, salbutamol exists two isomers. R-isomer exhibits the therapeutic effect and clinical benefit, while S-isomer proves to be detrimental rather than benign. So, in this study, we investigated the preventive and therapeutic effect of R-salbutamol (R-sal), S-salbutamol (S-sal) or racemic mixture in a mouse model of lipopolysaccharide (LPS)-induced sepsis. Dexamethasone (Dex) was set as comparison. The results showed that R-sal markedly improved seven-day survival rate of septic mice both administered before or after LPS. Whereas Dex showed toxic and accelerated the death of septic mice when given before LPS injection. Lung histological examination and lung function assay revealed that LPS challenge resulted in acute lung damage, including inflammatory cell infiltration, thickened alveolar septa and congestion, and decreased minute volume in septic mice. R-sal pretreatment efficiently inhibited these changes, accompanying by markedly reduced lung MPO level, serum cytokines levels and lactate release and significantly restored the lymphocytes and suppressed the percentage of monocytes. Racemic mixture exhibited diminished effects while S-sal showed enhanced cytokines release. In addition, R-sal pretreatment showed a better improvement in prognostic pulmonary function at day4 in survived mice than that of Rac-sal. Collectively, our results indicate the potential benefit of R-sal for sepsis and sepsis-induced lung injury.

pharmacology and toxicology↗

bioRxiv2021

"How do we do this at a distance?!" A descriptive study of remote undergraduate research programs during COVID-19

The COVID-19 pandemic shut down undergraduate research programs across the U.S. Twenty-three sites offered remote undergraduate research programs in the life sciences during summer 2020. Given the unprecedented offering of remote research experiences, we carried out a study to describe and evaluate these programs. Using structured templates, we documented how programs were designed and implemented, including who participated. Through focus groups and surveys, we identified programmatic strengths and shortcomings as well as recommendations for improvements from the perspectives of participating students. Strengths included the quality of mentorship, opportunities for learning and professional development, and development of a sense of community. Weaknesses included limited cohort building, challenges with insufficient structure, and issues with technology. Although all programs had one or more activities related to diversity, equity, inclusion, and justice, these topics were largely absent from student reports even though programs coincided with a peak in national consciousness about racial inequities and structural racism. Our results provide evidence for designing remote REUs that are experienced favorably by students. Our results also indicate that remote REUs are sufficiently positive to further investigate their affordances and constraints, including the potential to scale up offerings, with minimal concern about disenfranchising students.

scientific communication and education↗

bioRxiv2021

State-Transition Analysis of Time-Sequential microRNA Expression Predicts Development of Acute Myeloid Leukemia

MicroRNAs (miRNAs) are small non-coding RNA molecules involved in post-transcriptional regulation of gene expression and have been shown to hold prognostic value in a variety of settings, including acute myeloid leukemia (AML). However, the temporal dynamics of miRNA expression profiles as it relates to AML initiation and progression is poorly understood. Using serial samples from a mouse model of AML, we show that the miRNA transcriptome undergoes state-transition during AML initiation and progression. The AML state-transition was visualized and modeled by constructing an AML state-space from singular value decomposition of the time-series miRNA sequencing data. Within the AML state-space, we identified critical points of AML development characterized by unique differentially expressed miRNAs compared to healthy controls at critical points of leukemogenesis (early, transition, and late). Interestingly, we observed that changes in miRNA expression during leukemogenesis followed two patterns: 1) a monotonic pattern with continuously increasing or decreasing expression; and 2) a non-monotonic pattern with a local maximum or minimum at the transition critical point which was the "point of no-return" from health to AML. We validated the AML state-space and dynamics in an independent cohort of mice and demonstrated the state-transition model accurately predicted time to AML. Of note, we show that the miRNA-derived state-transition model produced a state-space and critical points that were strikingly similar, but not identical to that produced by the coding (i.e., messenger [m]RNA-based) transcriptome. This indicates that while both miRNA and mRNA expression may provide similar information, they also capture independent features of AML state-transition. SignificanceWe show that the microRNA transcriptome undergoes a global state transition during the initiation and progression of acute myeloid leukemia, and accurately predicts time to disease development.

cancer biology↗

bioRxiv2021

Time-restricted feeding near dawn entrains long-term behavioral changes through the suprachiasmatic nucleus

The suprachiasmatic nucleus (SCN) is a master circadian pacemaker known to integrate light intensity and seasonal information with peripheral tissues to coordinate daily rhythms of physiology and behavior. However, the contribution of food information to the regulation of the SCN network remains controversial. Here, we identified the effect induced by time-restricted feeding (TRF) at dawn, but not at another time widow, inducing a robust and long-term shift in locomotor behavior and increased wakefulness. Comparing the oscillations of intracellular Ca2+ signals in the SCN GABAergic neurons of freely moving mice, before and after TRF, revealed significant activation of these neurons in dawn-TRF mice. Moreover, RNA-seq profiling in the dawn TRF-induced behavioral changes identified altered expressed genes involved in regulating extracellular exosome, ion transporters, and ECM-receptor interaction, but not core clock genes. Furthermore, injection in the SCN of insulin-like growth factor (IGF2) inhibitor Chromeceptin, targeting the most upregulated gene in extracellular exosome, abolished the after effect induced by ZT0-4 TRF. Finally, GABAergic-neuron-specific disruption of the potassium-chloride cotransporter Kcc2 intensified the dawn TRF-induced after effect, indicating that Kcc2 encodes food intake derived signals that control SCN clock entrainment. Thus, our study functionally links SCN GABAergic neuron activity and central clock entrainment regulation to both hunger- and food-response-related behaviors in mice.

physiology↗

bioRxiv2020

Automatic Recognition of Auditory Brainstem Response Characteristic Waveform based on BiLSTM

BackgroundAuditory brainstem response (ABR) test is widely used in newborn hearing screening and hearing disease diagnosis. Identifying and marking are challenging and repetitive tasks because of complex rules of ABR characteristic waveform and interference of background noise. MethodsThis study proposes an automatic method to recognize ABR characteristic waveform. First, binarization is created to mark 1024 sampling points accordingly. The selected characteristic area of ABR data is 0-8ms. The marking area is enlarged to expand feature information and reduce marking error. Second, a bi-directional long short-term memory (BiLSTM) network structure is established to improve relevance of sampling points, and an ABR sampling point classifier is obtained by training. Finally, mark points are obtained through thresholding. ResultsSpecific structure, related parameters, recognition effect, and noise resistance of network were explored in 614 sets of ABR clinical data, and recognition accuracy of waves I, III, and V can reach 92.91%. DiscussionThus, the proposed method can reduce the repetitive work of doctors and meet accuracy effectively. Therefore, this method has clinical potential.

bioinformatics↗

bioRxiv2020

Automatic Measurement of Inner Ear in Different Mammals

ObjectiveTo facilitate the selection of optimal animal models for noise-induced hearing loss (NIHL) research, this study aims to develop an accurate, automatic centerline-based method to construct three-dimensional (3D) inner ear models in various mammals and assess their morphological similarities to humans. MethodsThree adult mice, three guinea pigs, three mini pigs, and one human temporal bone were scanned using Micro-CT. After segmentation, 3D inner ear models were reconstructed. A novel centerline method was established to automatically estimate 3D properties and calculate length, volume, and angle parameters across species. ResultsDetailed 3D models of the cochlea, vestibule, and semicircular canals were successfully constructed. Mean lengths and volumes of the cochlea and semicircular canals generally increased with body size, with mini pigs demonstrating the closest proximity to human data. Notably, numerical assessments showed that the semicircular canals in both mice and mini pigs closely resembled human structures. ConclusionAutomatic centerline-based measurement provides an effective tool for assessing 3D inner ear morphology. By confirming the high morphological similarity between mini pigs and humans, this study provides a critical theoretical basis for the mechanical analysis of noise-induced damage and the selection of biomimetic animal models for NIHL studies.

neuroscience↗

bioRxiv2020

Protein-protein interaction probability landscapes for yeast replicative aging

We proposed a novel probability landscape approach to map the systems-level profile changes of gene networks during replicative aging in Saccharomyces cerevisiae. This approach enabled us to apply quasi-potentials, the negative logarithm of the probabilities, to calibrate the elevation of the landscapes with young cells as a reference state. Our approach detected opposite landscape changes based on protein abundances from transcript levels, especially for intra-essential gene interactions. We showed that essential proteins play different roles from hub proteins on the age-dependent landscapes. We verified that hub proteins tend to avoid other hub proteins, but essential proteins are attractive to other essential proteins. Overall, we showed that the probability landscape is promising for inferring network profile change during aging and that the essential hub proteins may play an important role in the uncoupling between protein and transcript levels during replicative aging.

systems biology↗

bioRxiv2020

Association Study based on Topological Constraints of Protein-Protein Interaction Networks

The non-random interaction pattern of a protein-protein interaction network (PIN) is biologically informative but its potentials have not been fully utilized in omics studies. Here, we propose a network-permutation-based association study (NetPAS) method that gauges the observed interactions between two sets of genes based on the comparison between permutation null models and the empirical networks. This enables NetPAS to evaluate relationships, constrained by network topology, between gene sets related to different phenotypes. We demonstrated the utility of NetPAS in 50 well-curated gene sets and comparison of association studies using Z-scores, p-values or overrepresentations. Using NetPAS, a weighted human disease network was generated from the association scores of 19 gene sets from OMIM. We also applied NetPAS in gene sets derived from gene ontology and pathway annotations and showed that NetPAS uncovered functional terms missed by DAVID and other network-based enrichment tools. Overall, we show that NetPAS can take topological constraints of molecular networks into account and offer new perspectives than existing methods.

bioinformatics↗

bioRxiv2020

Counteracting Genome Instability by p53-dependent Mintosis

Entosis was proposed to promote aneuploidy and genome instability by cell-in-cell mediated engulfment in tumor cells. We reported here, in epithelial cells, that entosis coupled with mitotic arrest functions to counteract genome instability by targeting aneuploid mitotic progenies for engulfment and elimination. We found that the formation of cell-in-cell structures associated with prolonged mitosis, which was sufficient to induce entosis. This process was controlled by the tumor suppressor p53 (wild type) that upregulates Rnd3 expression in response to DNA damages associated with prolonged metaphase. Rnd3 compartmentalized RhoA activities accumulated during prolonged metaphase to drive cell-in-cell formation. Remarkably, this prolonged mitosis-induced entosis (mintosis) selectively targets non-diploid progenies for internalization, blockade of which increased aneuploidy. Thus, our work uncovered a heretofore unrecognized mechanism of mitotic surveillance for entosis, which eliminates newly-born abnormal daughter cells in a p53-depedent way to maintain genome integrity.

cell biology↗

bioRxiv2019

Complementary Performances of Convolutional and Capsule Neural Networks on Classifying Microfluidic Images of Dividing Yeast Cells

Microfluidic-based assays have become effective high-throughput approaches to examining replicative aging of budding yeast cells. Deep learning may offer an efficient way to analyze a large number of images collected from microfluidic experiments. Here, we compare three deep learning architectures to classify microfluidic time-lapsed images of dividing yeast cells into categories that represent different stages in the yeast replicative aging process. We found that convolutional neural networks outperformed capsule networks in terms of accuracy, precision, and recall. The capsule networks had the most robust performance at detecting one specific category of cell images. An ensemble of three best-fitted single-architecture models achieves the highest overall accuracy, precision, and recall due to complementary performances. In addition, extending classification classes and augmentation of the training dataset can improve the predictions of the biological categories in our study. This work lays a useful framework for sophisticated deep-learning processing of microfluidics-based assays of yeast replicative aging.

bioinformatics↗

bioRxiv2019

Speed and diffusion of kinesin-2 are competing limiting factors in flagellar length control model

Flagellar length control in Chlamydomonas is a tractable model system for studying the general question of organelle size regulation. We have previously proposed that diffusive return of the kinesin motor that powers intraflagellar transport can play a key role in length regulation. Here we explore how the motor speed and diffusion coefficient for the return of kinesin-2 affect flagellar growth kinetics. We find that the system can exist in two distinct regimes, one dominated by motor speed and one by diffusion coefficient. Depending on length, a flagellum can switch between these regimes. Our results indicate that mutations can affect length in distinct ways. We discuss our theorys implication for flagellar growth influenced by beating and provide possible explanations for the experimental observation that a beating flagellum is usually longer than its immotile mutant. These results demonstrate how our simple model can suggest explanations for mutant phenotypes.\n\nStatement of SignificanceThe eukaryotic flagellum is an ideal case study in organelle size control because of its simple linear shape and well-understood building mechanism. In our previous work, we proved that flagellar length in the green algae Chlamydomonas can be controlled by the diffusive gradient of the kinesin-2 motors that deliver building blocks to the tip. In this study, we expand on the analytical formulation of the diffusion model to show how physical parameters affect final length and regeneration time, enhancing the models potential to explain length mutants and motivate future research with precise predictions.

cell biology↗

bioRxiv2019

CNOT1 mediates phosphorylation via Protein kinase A on the circadian clock

At the core of the mammalian circadian feedback loop, CLOCK (NPAS2)-BMAL1 is the positive element to activate transcription of downstream genes encoding the negative elements PERs and CRYs. Here we show that CNOT1 associates with both CLOCK and BMAL1, promotes their phosphorylation and increases their protein stability, and in turn inhibits the transcriptional activity of CLOCK-BMAL1. Expression of either CLOCK, BMAL1 or CNOT1 could interact with endogenous Protein Kinase A (PKA) as assessed by co-immunoprecipitation (Co-IP) and kinase assays. PKA could phosphorylate CLOCK and BMAL1 and this was promoted by CNOT1. Genetic deletion of PKA-C by CRISPR-Cas9 results in a longer period of the circadian rhythm; while overexpression of PKA-C induces a shorter period. Furthermore, we demonstrate that CNOT1 associates with CLOCK and BMAL1 in the mouse liver and promotes their phosphorylation. PER2, but not CRY2, is also a PKA target. Our results suggest that CNOT1 and PKA play a critical role in the mammalian circadian clock, revealing a conserved function in eukaryotic circadian regulations.

developmental biology↗

bioRxiv2018

NDRG2 Regulates Adherens Junction Integrity to Restrict Colitis and Tumorigenesis

Paracellular barriers play an important role in the pathogenesis of IBDs and maintain gut homeostasis. N-myc downstream-regulated gene 2 (NDRG2) has been reported to be a tumor suppressor gene and inhibits colorectal cancer metastasis. However, whether NDRG2 affects colitis initiation and colitis-associated colorectal cancer is unclear. Here, We found that intestine-specific Ndrg2 deficiency caused mild spontaneous colitis with ageing, aggravated DSS and TNBS induced colitis, increased AOM-DSS induced colitis-associated tumor. Ndrg2 loss led to adherens junction (AJ) structure destruction via E-cadherin expression attenuation, resulting in diminished epithelial barrier function and increased intestinal epithelial permeability. Mechanistically, NDRG2 enhancing the interaction of E3 ligase FBXO11 with Snail, the repressor of E-cadherin, to promote Snail degradation by ubiquitination, and maintained E-cadherin expression. In human ulcerative colitis patients, reduced NDRG2 expression is positively correlated with severe inflammation. These findings demonstrate that NDRG2 is an essential colonic epithelial barrier regulator and plays important role in gut homeostasis maintenance and colitis-associated tumor development. SUMMARYAdherens junctoin (AJ) as the key part of intestinal epithelial barrier plays important role in the pathogenesis of IBDs. Intestinal specific Ndrg2 loss attenuates E-cadherin expression and disrupts the integrity of AJ structure which is feasible for colitis and tumor development.

cancer biology↗