Biology subjects

Hu, J.

Publications and source records attributed to Hu, J..

At least 379 records · Page 21Linked to original sources

bioRxiv2021

Reduced infectivity but increased immune escape of the new SARS-CoV-2 variant of concern Omicron

A new detected SARS-CoV-2 variant Omicron (B.1.1.529) had reported from more than 80 countries. In the past few weeks, a new wave of infection driven by Omicron is in progress. Omicron Spike (S) protein pseudotyped virus was used to determine the effect of S mutations on its capacity of infectivity and immune evasion. Our results showed the lower entry efficiency and less cleavage ability of Omicron than D614G variant. Pseudotype-based neutralizing assay was performed to analyze neutralizing antibodies elicited by previously infection or the RBD-based protein subunit vaccine ZF2001 against the Omicron variant. Sera sampled at around one month after symptom onset from 12 convalescents who were previously infected by SARS-CoV-2 original strain shows a more than 20-fold decrease of neutralizing activity against Omicron variant, when compared to D614G variant. Among 12 individuals vaccinated by RBD subunit vaccine, 58.3% (7/12) sera sampled at 15-60 days after 3rd-dose vaccination did not neutralize Omicron. Geometric mean titers (GMTs, 50% inhibitory dose [ID50]) of these sera against Omicron were 9.4-fold lower than against D614G. These results suggested a higher risk of Omicron breakthrough infections and reduced efficiency of the protective immunity elicited by existing vaccines. There are important implications about the modification and optimization of the current epidemic prevention and control including vaccine strategies and therapeutic antibodies against Omicron variant.

microbiology↗

bioRxiv2021

Selfee: Self-supervised Features Extraction of animal behaviors

Fast and accurately characterizing animal behaviors is crucial for neuroscience research. Deep learning models are efficiently used in laboratories for behavior analysis. However, it has not been achieved to use a fully unsupervised method to extract comprehensive and discriminative features directly from raw behavior video frames for annotation and analysis purposes. Here, we report a self-supervised feature extraction (Selfee) convolutional neural network with multiple downstream applications to process video frames of animal behavior in an end-to-end way. Visualization and classification of the extracted features (Meta-representations) validate that Selfee processes animal behaviors in a comparable way of human understanding. We demonstrate that Meta-representations can be efficiently used to detect anomalous behaviors that are indiscernible to human observation and hint in-depth analysis. Furthermore, time-series analyses of Meta-representations reveal the temporal dynamics of animal behaviors. In conclusion, we present a self-supervised learning approach to extract comprehensive and discriminative features directly from raw video recordings of animal behaviors and demonstrate its potential usage for various downstream applications.

neuroscience↗

bioRxiv2021

Genetic Sex Validation for Sample Tracking in Clinical Testing

BackgroundNext generation DNA sequencing (NGS) has been rapidly adopted by clinical testing laboratories for detection of germline and somatic genetic variants. The complexity of sample processing in a clinical DNA sequencing laboratory creates multiple opportunities for sample identification errors, demanding stringent quality control procedures. MethodsWe utilized DNA genotyping via a 96-SNP PCR panel applied at sample acquisition in comparison to the final sequence, for tracking of sample identity throughout the sequencing pipeline. The 96-SNP PCR panels inclusion of sex SNPs also provides a mechanism for a genotype-based comparison to recorded sex at sample collection for identification. This approach was implemented in the clinical genomic testing pathways, in the multi-center Electronic Medical Records and Genomics (eMERGE) Phase III program ResultsWe identified 110 inconsistencies from 25,015 (0.44%) clinical samples, when comparing the 96-SNP PCR panel data to the test requisition-provided sex. The 96-SNP PCR panel genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density hybridization-based genotyping arrays. Results identified clerical errors, samples from transgender participants and stem cell or bone marrow transplant patients and undetermined sample mix-ups. ConclusionThe 96-SNP PCR panel provides a cost-effective, robust tool for tracking samples within DNA sequencing laboratories, while the ability to predict sex from genotyping data provides an additional quality control measure for all procedures, beginning with sample collections. While not sufficient to detect all sample mix-ups, the inclusion of genetic versus reported sex matching can give estimates of the rate of errors in sample collection systems.

genomics↗

bioRxiv2021

Cohesin modulates DNA replication to preserve genome integrity

Cohesin participates in loop formation by extruding DNA fibers from its ring-shaped structure. Cohesin dysfunction eliminates chromatin loops but only causes modest transcription perturbation, which cannot fully explain the frequently observed mutations of cohesin in various cancers. Here, we found that DNA replication initiates at more than one thousand extra dormant origins after acute depletion of RAD21, a core subunit of cohesin, resulting in earlier replicating timing at approximately 30% of the human genomic regions. In contrast, CTCF is dispensable for suppressing the early firing of dormant origins that are distributed away from the loop boundaries. Furthermore, greatly elevated levels of gross DNA breaks and genome-wide chromosomal translocations arise in RAD21-depleted cells, accompanied by dysregulated replication timing at dozens of hotspot genes. Thus, we conclude that cohesin coordinates DNA replication initiation to ensure proper replication timing and safeguards genome integrity.

genetics↗

bioRxiv2021

MDR1 Drug Efflux Pump Promotes Intrinsic and Acquired Resistance to PROTACs in Cancer Cells

PROTACs (Proteolysis-Targeting Chimeras) represent a promising new class of drugs that selectively degrade proteins of interest from cells. PROTACs targeting oncogenes are avidly being explored for cancer therapies, with several currently in clinical trials. Drug resistance represents a significant challenge in cancer therapies, and the mechanism by which cancer cells acquire resistance to PROTACs remains poorly understood. Using proteomics, we discovered acquired and intrinsic resistance to PROTACs in cancer cells can be mediated by upregulation of the drug efflux pump MDR1. PROTAC-resistant cells could be re-sensitized to PROTACs through co-administering MDR1 inhibitors. Notably, co-treatment of MDR1-overexpressing colorectal cancer cells with MEK1/2 or KRASG12C degraders and the dual ErbB receptor/MDR1 inhibitor lapatinib exhibited potent drug synergy due to simultaneous blockade of MDR1 and ErbB receptor activity. Together, our findings suggest that concurrent blockade of MDR1 will likely be required in combination with PROTACs to achieve durable protein degradation and therapeutic response in cancer.

cancer biology↗

bioRxiv2021

The systematic assessment of completeness of public metadata accompanying omics studies

Recent advances in high-throughput sequencing technologies have made it possible to collect and share a massive amount of omics data, along with its associated metadata. Enhancing metadata availability is critical to ensure data reusability and reproducibility and to facilitate novel biomedical discoveries through effective data reuse. Yet, incomplete metadata accompanying public omics data may hinder reproducibility and reusability by reducing sample interpretability and limiting secondary analyses. In this study, we performed a comprehensive assessment of metadata completeness shared in both scientific publications and/or public repositories by analyzing over 253 studies encompassing over 164 thousands samples, including both human and non-human mammalian studies. We observed that studies often omit over a quarter of important phenotypes, with an average of only 74.8% of them shared either in the text of publication or the corresponding repository. Notably, public repositories alone contained 62% of the metadata, surpassing the textual content of publications by 3.5%. Only 11.5% of studies completely shared all phenotypes, while 37.9% shared less than 40% of the phenotypes. Studies involving non-human samples were more likely to share metadata than studies involving human samples. We observed similar results on the extended dataset spanning 2.1 million samples across over 61,000 studies from the Gene Expression Omnibus repository. The limited availability of metadata reported in our study emphasizes the necessity for improved metadata sharing practices and standardized reporting. Finally, we discuss the numerous benefits of improving the availability and quality of metadata to the scientific community and beyond, supporting data-driven decision-making and policy development in the field of biomedical research. This work provides a scalable framework for evaluating metadata availability and may help guide future policy and infrastructure development.

bioinformatics↗

bioRxiv2021

Remodeling of dermal adipose tissue alleviates cutaneous toxicity induced by anti-EGFR therapy

Anti-epidermal growth factor receptor (EGFR) therapy-associated cutaneous toxicity is a syndrome characterized by papulopustular rash, local inflammation, folliculitis and microbial infection, resulting in a decrease in quality of life and dose interruption. However, no effective clinical intervention is available for this adverse effect. Here, we report the atrophy of dermal white adipose tissue (dWAT), a highly plastic adipose tissue with various skin-specific functions, correlates with rash occurrence and exacerbation in a murine model of EGFR inhibitor-induced rash. The reduction in dWAT is due to the inhibition of adipogenic differentiation by defects in peroxisome proliferator-activated receptor {gamma} (PPAR{gamma}) signaling, and increased lipolysis by the induced expression of the lipolytic cytokine IL6. The activation of PPAR{gamma} by rosiglitazone maintains adipogenic differentiation and represses the transcription of IL6, eventually improving skin functions and ameliorating the severity of rash without altering the antitumor effects. Thus, activation of PPAR{gamma} represents a promising approach to ameliorate cutaneous toxicity in patients with cancer who receive anti-EGFR therapy. Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

pharmacology and toxicology↗

bioRxiv2021

Glyphosate and its formulations Roundup Bioflow and RangerPro alter bacterial and fungal community composition in the rat caecum microbiome

The potential health consequences of glyphosate-induced gut microbiome alterations have become a matter of intense debate. As part of a multifaceted study investigating toxicity, carcinogenicity and multigenerational effects of glyphosate and its commercial herbicide formulations, we assessed changes in bacterial and fungal populations in the caecum microbiota of rats exposed prenatally until adulthood (13 weeks after weaning) to three doses of glyphosate (0.5, 5, 50 mg/kg body weight/day), or to the formulated herbicide products Roundup Bioflow and RangerPro at the same glyphosate-equivalent doses. Caecum bacterial microbiota were evaluated by 16S rRNA sequencing whilst the fungal population was determined by ITS2 amplicon sequencing. Results showed that both fungal and bacterial diversity were affected by the Roundup formulations in a dose-dependent manner, whilst glyphosate alone significantly altered only bacterial diversity. At taxa level, a reduction in Bacteroidota abundance, marked by alterations in the levels of Alloprevotella, Prevotella and Prevotellaceae UCG-003, was concomitant to increased levels of Firmicutes (e.g., Romboutsia, Dubosiella, Eubacterium brachy group or Christensenellaceae) and Actinobacteria (e.g., Enterorhabdus, Adlercreutzia, or Asaccharobacter). Treponema and Mycoplasma also had their levels reduced by the pesticide treatments. Analysis of fungal composition indicated that the abundance of the rat gut commensal Ascomycota Kazachstania was reduced while the abundance of Gibberella, Penicillium, Claviceps, Cornuvesica, Candida, Trichoderma and Sarocladium were increased by exposure to the Roundup formulations, but not to glyphosate. Altogether, our data suggest that glyphosate and its Roundup RangerPro and Bioflow caused profound changes in caecum microbiome composition by affecting the fitness of major commensals, which in turn reduced competition and allowed opportunistic fungi to grow in the gut, in particular in animals exposed to the herbicide formulations. This further indicates that changes in gut microbiome composition might influence the long-term toxicity, carcinogenicity and multigenerational effects of glyphosate-based herbicides.

pharmacology and toxicology↗

bioRxiv2021

The NK receptor NKp46 recognizes ecto-calreticulin on ER-stressed cells

Natural killer cells (NK) are a first line of immune defense to eliminate infected, transformed and stressed cells by releasing cytotoxic granules1. NK activation is controlled by the balance of signals transmitted by activating and inhibitory receptors but activating receptor engagement is required to trigger cytotoxicity. The activating receptor NKp46, encoded by the NCR1 gene, is expressed by virtually all NK cells and is the most evolutionarily ancient NK receptor. NKp46 plays a major role in NK recognition of cancer cells, since NKp46 blocking antibodies potently inhibit NK killing of many cancer targets2,3. Although a few viral, fungal and soluble host ligands4 have been identified, the endogenous cell-surface ligand of this important activating NK receptor is unknown. Here we show that NKp46 recognizes and is activated by the P-domain of externalized calreticulin (ecto-CRT). CRT, normally localized to the ER, translocates to the cell surface during ER stress and is a hallmark of chemotherapy-treated dying cancer cells that induce an immune response (immunogenic cell death, ICD)5. NKp46 caps with ecto-CRT in NK immune synapses formed with ecto-CRT-bearing target cells. ER stress, induced by ZIKV infection, ICD-causing chemotherapy drugs and some senescence activators, externalizes CRT and triggers NKp46 signaling. NKp46-mediated killing is inhibited by CRT knockout or knockdown or anti-CRT antibodies and is enhanced by ectopic expression of GPI-anchored CRT. NCR1/Ncr1-deficient human and mouse NK are impaired in killing ZIKV-infected, ER-stressed, and senescent cells and cancer cells that endogenously or ectopically express ecto-CRT. Importantly, NKp46 recognition of ecto-CRT controls the growth of B16 melanoma and RAS-driven lung cancer in mouse models and enhances tumor-infiltrating NK degranulation and cytokine secretion. Thus, ecto-CRT is a danger-associated molecular pattern (DAMP) that is an endogenous NKp46 ligand that promotes innate immune elimination of ER-stressed cells.

immunology↗

bioRxiv2021

A comprehensive evaluation of CRISPR lineage recorders using TraceQC

The CRISPR-Cas9 genome editing-based lineage tracing system is emerging as a powerful tool to track cell lineages at unprecedented scale and resolution. However, the complexity of CRISPR-Cas9 induced mutations has raised challenges in lineage reconstruction, which requires a unique computational analysis framework. Meanwhile, multiple distinctive CRISPR-based high-throughput lineage recorders have been developed over the years in which the data analysis is incompatible across platforms. To address these challenges, first, we present the TraceQC, a cross-platform open-source package for data processing and quality evaluation of CRISPR lineage tracing data. Second, by using the TraceQC package, we performed a comprehensive analysis across multiple CRISPR lineage recorders to uncover the speed and distribution of CRISPR-induced mutations. Together, this work provides a computational framework for the CRISPR lineage tracing system that should broadly benefit the design and application of this promising technology.

bioinformatics↗

bioRxiv2021

Emergent phases of ecological diversity and dynamics mapped in microcosms

Natural ecological communities display striking features, such as high biodiversity and a wide range of dynamics, that have been difficult to explain in a unified framework. Using experimental bacterial microcosms, we perform the first direct test of recent complex systems theory predicting that simple aggregate parameters dictate emergent behaviors of the community. As either the number of species or the strength of species interactions is increased, we show that microbial ecosystems transition between distinct qualitative dynamical phases in the predicted order, from a stable equilibrium where all species coexist, to partial coexistence, to emergence of persistent fluctuations in species abundance. Under the same conditions, high biodiversity and fluctuations allow and require each other. Our results demonstrate predictable emergent diversity and dynamics in ecological communities. One-Sentence SummaryA phase diagram of ecological dynamics and diversity as a function of coarse-grained features of species interaction network.

biophysics↗

bioRxiv2021

Short term treatment with a cocktail of rapamycin, acarbose and phenylbutyrate slows aging in mice

Pharmaceutical intervention of aging requires targeting multiple pathways, thus there is rationale to test combinations of drugs each targeting different but overlapping processes. In order to determine if combining drugs previously shown to improve lifespan would have greater impact than any individuyal drug, a diet containing rapamycin at 14 ppm, acarbose at 1000 ppm, and phenylbutyrate at 1000 ppm was fed to 20-month-old C57BL/6 and HET3 4-way cross mice of both sexes for three months. Mice fed the cocktail diet showed a strain and gender-dependent phenotype consistent with healthy aging including decreased body fat and blood glucose, improved cognition, and increased grip strength and walking ability compared to mice fed individual drug or control diets. A cocktail diet containing [1/2] dosing of each compound was overall less effective than the full dose. The composite age-related lesion score of heart, lungs, liver and kidney was decreased in mice fed the cocktail diet compared to mice fed individual drug or control diets suggesting an interactive advantage of the three drugs. Senescence and inflammatory cytokine levels in kidneys from mice fed the cocktail diet were lower than in kidneys from mice fed control diet, and consistent with low expression levels in kidneys from young untreated mice, suggesting the cocktail diet delayed aging partly by senolytic and anti-inflammatory effects.

systems biology↗

bioRxiv2021

Palaeogenomics reveal a hybrid origin of the world's largest Camelus species

The extinct Camelus knoblochi is known as the largest camel in genus Camelus, but its relationship to modern Camelus species remains unclear. In this study, we reported the first mitochondrial and nuclear analyses of seven Late Pleistocene C. knoblochi samples from Northeastern China. We found that they are inseparable to wild Bactrian camel on the matrilineal side, but belong to a distinct cluster on the biparental nuclear side. Further admixture proportion analyses suggested hybrid ancestry between both the ancestors of the modern wild and domesticated Bactrian camels, with ~65% contribution from the former and ~35% from the later. By calculating the coalescence time for three Camelus species above, we estimated the hybridization event occurred between approximately 0.8 and 0.33 Ma. We also used Bayesian skyline to reconstruct the maternal demographic trajectories for different Camelus to better compare their evolutionary histories. Our results provide molecular insights into C. knoblochi and fill in a vital piece in understanding the genus Camelus.

molecular biology↗

bioRxiv2021

Heat shock chaperone HSPB1 regulates cytoplasmic TDP-43 phase separation and liquid-to-gel transition

While the RNA binding protein TDP-43 reversibly phase separates within nuclei into complex droplets (anisosomes) with TDP-43-containing liquid outer shells and liquid centers of HSP70 family chaperones, cytoplasmic aggregates of TDP-43 are hallmarks of multiple neurodegenerative diseases, including ALS. Here we show that transient oxidative stress, proteasome inhibition, or inhibition of HSP70s ATP-dependent chaperone activity provokes reversible cytoplasmic TDP-43 de-mixing and transition from liquid to gel/solid, independent of RNA binding or stress granules. Isotope labeling mass spectrometry is used to identify that phase separated cytoplasmic TDP-43 is primarily bound by the small heat shock protein HSPB1. Binding is direct, mediated through TDP-43s RNA binding and low complexity domains. HSPB1 partitions into TDP-43 droplets, inhibits TDP-43 assembly into fibrils, and is essential for disassembly of stress-induced, TDP-43 droplets. Decrease of HSPB1 promotes cytoplasmic TDP-43 de-mixing and mislocalization. HSPB1 depletion is identified within ALS-patient spinal motor neurons containing aggregated TDP-43. These findings identify HSPB1 to be a regulator of cytoplasmic TDP-43 phase separation and aggregation.

cell biology↗

bioRxiv2021

The language network supports both lexical access and sentence generation during language production

A fronto-temporal brain network has long been implicated in language comprehension. However, this networks role in language production remains debated. In particular, it remains unclear whether all or only some language regions contribute to production, and which aspects of production these regions support. Across three fMRI experiments that rely on robust individual-subject analyses, we characterize the language networks response to high-level production demands. We report three novel results. First, sentence production, spoken or typed, elicits a strong response throughout the language network. Second, the language network responds to both phrase-structure building and lexical access demands, although the response to phrase-structure building is stronger and more spatially extensive, present in every language region. Finally, contra some proposals, we find no evidence of brain regions--within or outside the language network--that selectively support phrase-structure building in production relative to comprehension. Instead, all language regions respond more strongly during production than comprehension, suggesting that production incurs a greater cost for the language network. Together, these results align with the idea that language comprehension and production draw on the same knowledge representations, which are stored in a distributed manner within the language-selective network and are used to both interpret and generate linguistic utterances.

neuroscience↗

bioRxiv2021

A universal approach for integrating super large-scale single-cell transcriptomes by exploring gene rankings

Advancement in single-cell RNA sequencing leads to exponential accumulation of single-cell expression data. However, there is still lack of tools that could integrate these unlimited accumulation of single-cell expression data. Here, we presented a universal approach iSEEEK for integrating super large-scale single-cell expression via exploring expression rankings of top-expressing genes. We developed iSEEEK with 13.7 million single-cells. We demonstrated the efficiency of iSEEEK with canonical single-cell downstream tasks on five heterogenous datasets encompassing human and mouse samples. iSEEEK achieved good clustering performance benchmarked against well-annotated cell labels. In addition, iSEEEK could transfer its knowledge learned from large-scale expression data on new dataset that was not involved in its development. iSEEEK enables identification of gene-gene interaction networks that are characteristic of specific cell types. Our study presents a simple and yet effective method to integrate super large-scale single-cell transcriptomes and would facilitate translational single-cell research from bench to bedside.

bioinformatics↗

bioRxiv2021

Three-level Sleep Stage Classification Based on Wrist-worn Accelerometry Data Alone

ObjectiveThe use of wearable sensor devices on daily basis to track real-time movements during wake and sleep has provided opportunities for automatic sleep quantification using such data. Existing algorithms for classifying sleep stages often require large training data and multiple input signals including heart rate and respiratory data. We aimed to examine the capability of classifying sleep stages using sensible features directly from accelerometers only with the aid of advanced recurrent neural networks. Materials and MethodsWe analyzed a publicly available dataset with accelerometry data in 5s epoch length and polysomnography assessments. We developed long short-term memory (LSTM) models that take the 3-axis accelerations, angles, and temperatures from concurrent and historic observation windows to predict wake, REM and non-REM sleep. Leave-one-subject-out experiments were conducted to compare and evaluate the model performance with conventional nonsequential machine learning models using metrics such as multiclass training and testing accuracy, weighted precision, F1 score and area-under-the-curve (AUC). ResultsOur sequential analysis framework outperforms traditional non-sequential models in all aspects of model evaluation metrics. We achieved an average of 65% and a maximum of 81% validation accuracy for classifying three sleep labels even with a relatively small training sample of clinical visitors. The presence of two additional derived variables, local variability and range, have shown to strongly improve the model performance. DiscussionResults indicate that it is crucial to account for deep temporal dependency and assess local variability of the features. The post-hoc analysis of individual model performances on subjects demographic characteristics also suggest the need of including pathological samples in the training data in order to develop robust machine learning models that are capable of capturing normal and anomaly sleep patterns in the population.

neuroscience↗

bioRxiv2021

Comparative proteomic analysis of vancomycin-sensitive and vancomycin-intermediate resistant S. aureus

The extensive use of vancomycin has led to the development of MRSA (methicillin-resistant Staphylococcus aureus) strains with varying degrees of resistance to vancomycin. Accumulation of surplus cell wall material, decreased cross-linking of peptidoglycan, and/ or other cell wall alterations has been put forward to explain the VISA phenotype. To our knowledge, the protein profiles of hVISA and VISA strains are rarely analyzed via quantitative comparative proteomics. In this study, we subjected subcellular fractions isolated from two isogenic S. aureus strains (vancomycin-intermediate resistant S. aureus) to proteomic analysis, using an integrated quantitative proteomic approach assisted by bioinformatic analysis. In total,128 up-regulated proteins (mainly AhpC, Adh, ArgF et al.) were identified,21 down-regulated proteins (mainly LtaS, SdrD, MsrR, MsrB, OatA et al.) were obtained. The largest group of differentially expressed proteins is composed of enzymic proteins associated with metabolic and catalytic activity, which accounts for 50% and 51% of the total proteins, respectively.Some proteins which take an indispensable part in the regulatory networks of S. aureus with vancomycin treatment are related to Cell wall metabolism ( MurA ), Cell adhesion ( SdrC, SdrD, ClfA, ClfB ), Proteolysis ( Atl, LytM, SceD ) and Pressure response ( MsrA, MsrB, AhpC ) process.In conclusion, our proteomic study revealed regulatory proteins associated with vancomycin resistance in S. aureus, and some of these proteins are involved in the regulation of cell metabolism and function, providing protential targets for further development of drug resistance strategies.

microbiology↗