Biology subjects

Tang, J.

Publications and source records attributed to Tang, J..

At least 163 records · Page 9Linked to original sources

bioRxiv2022

Genome-wide mapping of fluoroquinolone-stabilized DNA gyrase cleavage sites displays drug specific effects that correlate with bacterial persistence

Persisters are rare phenotypic variants that are suspected to be culprits of recurrent infections. Fluoroquinolones (FQs) are a class of antibiotic that facilitate DNA damage by stabilizing type II topoisomerases when they are in a complex with cleaved DNA. In Escherichia coli, DNA gyrase is the primary FQ target, and previous work has demonstrated that persisters are not spared from FQ-induced DNA damage. Since DNA gyrase cleavage sites (GCSs) largely govern the sites of DNA damage from FQ treatment, we hypothesized that GCS characteristics (e.g., number, strength, location) may influence persistence. To test this hypothesis, we measured genome-wide GCS distributions after treatment with a panel of FQs. We found drug-specific effects on the GCS distribution and discovered a strong negative correlation between the cumulative cleavage strength across the chromosome and FQ persister levels. Further experiments and analyses suggested that persistence was not governed by cleavage to individual sites, but rather survival was a function of the cumulative GCS distribution. Together, these findings demonstrate FQ-specific differences in GCS distribution that correlate with persister levels and suggest that FQs that better stabilize DNA gyrase in cleaved complexes with DNA will lead to lower levels of persistence.

microbiology↗

bioRxiv2022

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

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

bioinformatics↗

bioRxiv2022

Essential role of the amino-terminal region of Drosha for the Microprocessor function

The ribonuclease (RNase) III enzyme Drosha enables processing of microRNA (miRNA) primary transcripts (pri-miRNAs) and control of ribosomal protein (RP) biogenesis by the Microprocessor. The extensively studied carboxyl-terminal half of Drosha is sufficient to crop pri-miRNAs in vitro, but the function of the evolutionarily conserved Drosha amino-terminal region (NTR) is unknown, despite it harboring mutations linked to a hereditary vascular disorder. Here, we provide evidence that, when replacing the endogenous Drosha, a mutant missing the NTR ({Delta}N-Drosha) fails to associate with endogenous pri-miRNAs and to support the expression of all miRNAs, except the miR-183 cluster. Surprisingly, Argonaute2 (Ago2) associates with and cleaves pri-miR-183 in {Delta}N-Drosha cells and in Drosha-depleted cells. {Delta}N-Drosha is also unable to inhibit RP biogenesis upon serum starvation. Thus, Drosha NTR is essential for pri-miRNA processing and RP biogenesis in vivo, and Ago2 can process the miR-183 cluster in the absence of Drosha.

molecular biology↗

bioRxiv2022

Semantic reconstruction of continuous language from non-invasive brain recordings

A brain-computer interface that decodes continuous language from non-invasive recordings would have many scientific and practical applications. Currently, however, decoders that reconstruct continuous language use invasive recordings from surgically implanted electrodes1-3, while decoders that use non-invasive recordings can only identify stimuli from among a small set of letters, words, or phrases4-7. Here we introduce a non-invasive decoder that reconstructs continuous natural language from cortical representations of semantic meaning8 recorded using functional magnetic resonance imaging (fMRI). Given novel brain recordings, this decoder generates intelligible word sequences that recover the meaning of perceived speech, imagined speech, and even silent videos, demonstrating that a single language decoder can be applied to a range of semantic tasks. To study how language is represented across the brain, we tested the decoder on different cortical networks, and found that natural language can be separately decoded from multiple cortical networks in each hemisphere. As brain-computer interfaces should respect mental privacy9, we tested whether successful decoding requires subject cooperation, and found that subject cooperation is required both to train and to apply the decoder. Our study demonstrates that continuous language can be decoded from non-invasive brain recordings, enabling future multipurpose brain-computer interfaces.

neuroscience↗

bioRxiv2022

Highly Sensitive and Specific Amyloid-β Oligomers Detection Using CRISPR-Cas12a Probe System aided by Graphene Oxide for Early Diagnosis of Alzheimer's Diseases

Alzheimers disease (AD) is highly age-specific that results in cognitive incapability including dementia. It is proposed that AD is caused by the dysfunctional gene producing excessive amyloid-{beta} protein that eventually results in aggregated form of amyloid-{beta} Oligomers (A{beta}O). We couple the CRISPR-Cas12a system with a specially designed single-stranded DNA (ssDNA) aptamer that specifically forms a hybrid complex with A{beta}O. We exploit the aptamer as the substrate for the crRNA-aptamer duplex due to its high flexibility, sensitivity, and selectivity. We further adopted the graphene oxide (GO) fluorescent system to couple with our CRISPR-Cas12a probe system. Our coupled probe system can effectively detect the presence of A{beta}O by quantitatively returning fluorescent signals with high specificity and accuracy.

biochemistry↗

bioRxiv2022

A natural language fMRI dataset for voxelwise encoding models

Speech comprehension is a complex process that draws on humans abilities to extract lexical information, parse syntax, and form semantic understanding. These sub-processes have traditionally been studied using separate neuroimaging experiments that attempt to isolate specific effects of interest. More recently it has become possible to study all stages of language comprehension in a single neuroimaging experiment using narrative natural language stimuli. The resulting data are richly varied at every level, enabling analyses that can probe everything from spectral representations to high-level representations of semantic meaning. We provide a dataset containing BOLD fMRI responses recorded while 8 subjects each listened to 27 complete, natural, narrative stories (~6 hours). This dataset includes pre-processed and raw MRIs, as well as hand-constructed 3D cortical surfaces for each participant. To address the challenges of analyzing naturalistic data, this dataset is accompanied by a python library containing basic code for creating voxelwise encoding models. Altogether, this dataset provides a large and novel resource for understanding speech and language processing in the human brain.

neuroscience↗

bioRxiv2022

Improve the Protein Complex Prediction with Protein Language Models

AlphaFold-Multimer has greatly improved protein complex structure prediction, but its accuracy also depends on the quality of the multiple sequence alignment (MSA) formed by the interacting homologs (i.e., interologs) of the complex under prediction. Here we propose a novel method, denoted as ESMPair, that can identify interologs of a complex by making use of protein language models (PLMs). We show that ESMPair can generate better interologs than the default MSA generation method in AlphaFold-Multimer. Our method results in better complex structure prediction than AlphaFold-Multimer by a large margin (+10.7% in terms of the Top-5 best DockQ), especially when the predicted complex structures have low confidence. We further show that by combining several MSA generation methods, we may yield even better complex structure prediction accuracy than Alphafold-Multimer (+22% in terms of the Top-5 best DockQ). We systematically analyze the impact factors of our algorithm and find out the diversity of MSA of interologs significantly affects the prediction accuracy. Moreover, we show that ESMPair performs particularly well on complexes in eucaryotes.

bioinformatics↗

bioRxiv2022

Microcirculatory dysfunction associates with neurovascular uncoupling in peri-ischemic brain regions after ischemic stroke

BackgroundDespite recanalization after ischemic stroke, neurovascular coupling, i.e., the local hyperaemic response to neuronal activity, is impaired in peri-ischemic brain regions. Reduced neurovascular coupling may contribute to neurological deterioration over time. The mechanism underlying dysfunctional neurovascular coupling following stroke is largely unknown. MethodsMice implanted with chronic cranial windows were trained for awake head-fixation prior to experiments. One hour occlusion of the anterior middle cerebral artery branch was induced using single vessel photothrombosis. Cerebral perfusion and neurovascular coupling were assessed by optical coherence tomography and laser speckle contrast imaging. Capillaries and pericytes were studied in perfusion-fixed tissue by labelling lectin and platelet-derived growth factor receptor {beta}. ResultsArterial occlusion induced on average 11 spreading depressions over one hour associated with substantially reduced blood flow in the peri-ischemic cortex. Approximately half of the capillaries in the peri-ischemic area were no longer perfused 3 and 24 hours after reperfusion, which was associated with constriction of an equivalent proportion of peri-ischemic capillary pericytes. The capillaries in the peri-ischemic cortex that remained perfused showed increased prevalence of dynamic flow stalling. Whisker stimulation led to reduced neurovascular coupling responses in the sensory cortex corresponding to the peri-ischemic region 3 and 24 hours after reperfusion. ConclusionArterial occlusion led to constriction of pericytes in the peri-ischemic cortex associated with long-lasting microcirculatory failure. This reduced capillary capacity may, at least in part, underlie impaired neurovascular coupling in peri-ischemic brain regions after stroke and reperfusion.

physiology↗

bioRxiv2022

Interpretable prognostic modeling of endometrial cancer

Endometrial carcinoma (EC) is one of the most common gynecological cancers in the world. In this work we apply Cox proportional hazards (CPH) and optimal survival tree (OST) algorithms to the retrospective prognostic modeling of disease-specific survival in 842 EC patients. We demonstrate that the linear CPH models are preferred for the EC risk assessment based on clinical features alone, while the interpretable, non-linear OST models are favored when patient profiles are enriched with tumor molecular data. By studying the OST decision path structure, we show how explainable tree models recapitulate existing clinical knowledge prioritizing L1 cell-adhesion molecule and estrogen receptor status indicators as key risk factors in the p53 abnormal EC subgroup. We believe that visually interpretable tree algorithms are a promising method to explore feature interactions and generate novel research hypotheses. To aid further clinical adoption of advanced machine learning techniques, we stress the importance of quantifying model discrimination and calibration performance in the development of explainable clinical prediction models.

bioinformatics↗

bioRxiv2022

Endothelial TIE1 restricts angiogenic sprouting to coordinate vein assembly in synergy with its homologue TIE2

ObjectiveVascular growth followed by vessel specification is crucial for the establishment of a hierarchical blood vascular network. We have here investigated mechanisms underlying venogenesis, particularly the molecular control over venous fate acquisition during vascular development. Approach and ResultsWe analyzed the function of TIE1 as well as its synergy with TIE2 in the regulation of vein formation by employing genetic mouse models targeting Tie1 and Tek. Cardinal vein growth appeared normal in TIE1 deficient mice, whereas TIE2 deficiency altered the identity of cardinal vein endothelial cells with the aberrant expression of DLL4. Interestingly, the parallel growth of murine cutaneous veins along with arteries, which was initiated at approximately embryonic day 13.5, was retarded in mice lack of TIE1. Tie1 deletion disrupted also venous integrity, displaying increased sprouting angiogenesis and vascular bleeding. Abnormal venous sprouts with defective arteriovenous alignment were also observed in the mesenteries of Tie1 deleted mice. Mechanistically, TIE1 deficiency resulted in the decreased expression of venous regulators including TIE2 while angiogenic regulators were upregulated. The alteration of TIE2 level by TIE1 insufficiency was further confirmed by the siRNA-mediated knockdown of Tie1 in cultured endothelial cells. Additionally, combining the endothelial deletion of Tie1 with one null allele of Tek resulted in a progressive increase of vein-associated angiogenesis leading to the formation of vascular tufts in retinas, whereas the loss of Tie1 alone produced only a relatively mild venous defect. ConclusionsFindings from this study imply that TIE1 and TIE2 act in a synergistic manner to restrict sprouting angiogenesis during vein formation.

developmental biology↗

bioRxiv2022

Tracing back primed resistance in cancer via sister cells

Exploring non-genetic evolution of cell states during cancer treatments has become attainable by recent advances in lineage-tracing methods. However, transcriptional changes that drive cells into resistant fates may be subtle, necessitating high resolution analysis. We developed ReSisTrace that uses shared transcriptomic features of synchronised sister cells to predict the states that prime treatment resistance. We applied ReSisTrace in ovarian cancer cells perturbed with olaparib, carboplatin or natural killer (NK) cells. The pre-resistant phenotypes were defined by cell cycle and proteostatic features, reflecting the traits enriched in the upcoming subclonal selection. Furthermore, DNA repair deficiency rendered cells susceptible to both DNA damaging agents and NK killing in a context-dependent manner. Finally, we leveraged the pre-resistance profiles to predict and validate small molecules driving cells to sensitive states prior to treatment. In summary, ReSisTrace resolves pre-existing transcriptional features of treatment vulnerability, facilitating both molecular patient stratification and discovery of synergistic pre-sensitizing therapies.

cancer biology↗

bioRxiv2022

Life history strategies and niches of soil bacteria emerge from interacting thermodynamic, biophysical, and metabolic traits

Efficient biochemical transformation of belowground carbon by microorganisms plays a critical role in determining the long-term fate of soil carbon. As plants assimilate carbon from the atmosphere, up to 50% is exuded into the area surrounding growing roots, where it may be transformed into microbial biomass and subsequently stabilized through mineral associations. However, due to a hierarchy of interacting microbial traits, it remains elusive how emergent life-history strategies of microorganisms influence the processing of root exudate carbon. Here, by combining theory-based predictions of substrate uptake kinetics for soil bacteria and a new genome-informed trait-based dynamic energy budget model, we predicted life history traits and trade-offs of a broad range of soil bacteria growing on 82 root exudate metabolites. The model captured resource-dependent trade-offs between growth rate (power) and growth efficiency (yield) that are fundamental to microbial fitness in communities. During early phases of plant development, growth rates of bacteria were largely constrained by maximum growth potential, highlighting the predictive power of genomic traits during nutrient-replete soil conditions. In contrast, selection for efficiency was important later in the plant growing season, where the model successfully predicted microbial substrate preferences for aromatic organic acids and plant hormones. The predicted carbon-use efficiencies for growth on organics acids were much higher than typical values observed in soil. These predictions provide mechanistic underpinning for the apparent efficiency of the microbial route to mineral stabilization in the rhizosphere and add an additional layer of complexity to rhizosphere microbial community assembly.

ecology↗

bioRxiv2022

Development of allosteric, selective cyclin-dependent kinase 2 (CDK2) inhibitors that are negatively cooperative with cyclin binding and show potential as contraceptive agents

Compared to most ATP-site kinase inhibitors, small molecules that target an allosteric pocket have the potential for improved selectivity due to the often observed lower structural similarity at these distal sites. Despite their promise, relatively few examples of structurally confirmed, high-affinity allosteric kinase inhibitors exist. Cyclin-dependent kinase 2 (CDK2) is a target for many therapeutic indications, including non-hormonal contraception.1 However, an inhibitor against this kinase with exquisite selectivity has not reached the market because of the structural similarity between CDKs.1-2 In this paper, we describe the development and mechanism of action of new type III inhibitors that bind CDK2 with nanomolar affinity, making them the highest affinity, structurally confirmed allosteric CDK inhibitors reported. Notably, these anthranilic acid inhibitors exhibit a strong negative cooperative relationship with cyclin binding, which remains an underexplored mechanism for CDK2 inhibition. Furthermore, the binding profile of these compounds in both biophysical and cellular assays demonstrate the promise of this series for further development into a therapeutic selective for CDK2 over highly similar kinases like CDK1. The potential of these inhibitors as efficacious contraceptive agents is seen by incubation with mouse testicular explants, where they recapitulate Cdk2-/- and Spdya-/- phenotypes.

pharmacology and toxicology↗

bioRxiv2022

The structure of the humanised A33 Fab C226S variant, an immunotherapy candidate for colorectal cancer

Colorectal cancer (CRC) causes the second highest cancer-related deaths worldwide. The human A33 antigen is a validated immunotherapy target, which is homogeneously expressed in 95% cases of primary and metastatic colorectal cancers. In this article, we report the structure of a humanised antigen-binding fragment A33 (A33 Fab), a therapeutic antibody candidate, in two different crystal forms. Insights into the structural features of A33 Fab are provided with a focus on the grafted complementarity-determining regions (CDRs) and the switch linker between the variable and the constant regions. SynopsisThe crystal structure of humanised A33 Fab, targeting colorectal cancer related antigen, was determined in two different space groups.

biophysics↗

bioRxiv2022

Integrating inflammatory biomarker analysis and artificial intelligence-enabled image-based profiling to identify drug targets for intestinal fibrosis

Intestinal fibrosis is a common complication of several enteropathies with inflammatory bowel disease being the major cause. The progression of intestinal fibrosis may lead to intestinal stenosis and obstruction. Even with an increased understanding of tissue fibrogenesis, there are no approved treatments for intestinal fibrosis. Historically, drug discovery for diseases like intestinal fibrosis has been impeded by a lack of screenable cellular phenotypes. Here we applied Cell Painting, a scalable image-based morphology assay, augmented with machine learning algorithms to identify small molecules that were able to morphologically reverse the activated fibrotic phenotype of intestinal myofibroblasts under pro-fibrotic TNF stimulus. In combination with measuring CXCL10, a common pro-inflammatory cytokine in intestinal fibrosis, we carried out a high-throughput small molecule chemogenomics screen of approximately 5000 compounds with known targets or mechanisms, which have achieved clinical stage or approval by the FDA. Through the use of two divergent analytical methods, we identified several compounds and target classes that are potentially able to treat intestinal fibrosis. The phenotypic screening platform described here represents significant improvements in identifying a wide range of drug targets over conventional methods by integrating morphological analyses and artificial intelligence using pathologically-relevant cells and disease-relevant stimuli.

pharmacology and toxicology↗

bioRxiv2022

Respiratory mucosal vaccination of peptide-poloxamine-DNA nanoparticles provides complete protection against lethal SARS-CoV-2 challenge

The ongoing SARS-CoV-2 pandemic represents a brutal reminder of the continual threat of mucosal infectious diseases. Mucosal immunity may provide robust protection at the predominant sites of SARS-CoV-2 infection. However, it remains unclear whether respiratory mucosal administration of DNA vaccines could confer protective immune responses against SARS-CoV-2 challenge due to the insurmountable barriers posed by the airway. Here, we applied self-assembled peptide-poloxamine nanoparticles with mucus-penetrating properties for pulmonary inoculation of a COVID-19 DNA vaccine (pSpike/PP-sNp). Not only displays the pSpike/PP-sNp superior gene-transfection and favorable biocompatibility in the mouse airway, but pSpike/PP-sNp promotes a tripartite immunity consisting of systemic, cellular and mucosal immune responses that are characterized by mucosal IgA secretion, high levels of neutralizing antibodies, and resident memory phenotype T-cell responses in the lungs of mice. Most importantly, pSpike/PP-sNp completely eliminates SARS-CoV-2 infection in both upper and lower respiratory tracts and enables 100% survival rate of mice following lethal SARS-CoV-2 challenge. Our findings indicate PP-sNp might be a promising platform in mediating DNA vaccines to elicit all-around mucosal immunity against SARS-CoV-2.

immunology↗

bioRxiv2022

Translocator protein is a marker of activated microglia in rodent models but not human neurodegenerative diseases

Microglial activation plays central roles in neuro-inflammatory and neurodegenerative diseases. Positron emission tomography (PET) targeting 18kDa Translocator Protein (TSPO) is widely used for localising inflammation in vivo, but its quantitative interpretation remains uncertain. We show that TSPO expression increases in activated microglia in mouse brain disease models but does not change in a non-human primate disease model or in common neurodegenerative and neuroinflammatory human diseases. We describe genetic divergence in the TSPO gene promoter, consistent with the hypothesis that the increase in TSPO expression in activated myeloid cells is unique to a subset of species within the Muroidea superfamily of rodents. We show that TSPO is mechanistically linked to classical pro-inflammatory myeloid cell function in rodents but not humans. These data emphasise that TSPO expression in human myeloid cells is related to different phenomena than in mice, and that TSPO PET reflects density of inflammatory cells rather than activation state.

neuroscience↗

bioRxiv2022

DrugRepo: A novel approach to repurpose a huge collection of compounds based on chemical and genomic features

The drug development process consumes 9-12 years and approximately one billion US dollars in terms of costs. Due to high finances and time costs required by the traditional drug discovery paradigm, repurposing the old drugs to treat cancer and rare diseases is becoming popular. Computational approaches are mainly data-driven and involve a systematic analysis of different data types leading to the formulation of repurposing hypotheses. This study presents a novel scoring algorithm based on chemical and genomic data types to repurpose vast collection of compounds for 674 cancer types and other diseases. The data types used to design the scoring algorithm are chemical structures, drug-target interactions (DTI), pathways, and disease-gene associations. The repurpose scoring algorithm is strengthened by integrating the most comprehensive manually curated datasets for each data type. More than 100 of our repurposed compounds can be matched with ongoing studies at clinical trials (https://clinicaltrials.gov/). Our analysis is supported by a web tool available at: http://drugrepo.org/.

bioinformatics↗