Biology subjects

Qin, Z.

Publications and source records attributed to Qin, Z..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

AI in Paleontology

Accumulating data have led to the emergence of data-driven paleontological studies, which reveal an unprecedented picture of evolutionary history. However, the fast-growing quantity and complication of data modalities make data processing laborious and inconsistent, while also lacking clear benchmarks to evaluate data collection and generation, and the performances of different methods on similar tasks. Recently, Artificial Intelligence (AI) is widely practiced across scientific disciplines, but has not become mainstream in paleontology where manual workflows are still typical. In this study, we review more than 70 paleontological AI studies since the 1980s, covering major tasks including micro-and macrofossil classification, image segmentation, and prediction. These studies feature a wide range of techniques such as Knowledge Based Systems (KBS), neural networks, transfer learning, and many other machine learning methods to automate a variety of paleontological research workflows. Here, we discuss their methods, datasets, and performance and compare them with more conventional AI studies. We attribute the recent increase in paleontological AI studies to the lowering bar in training and deployment of AI models rather than real progress. We also present recently developed AI implementations such as diffusion model content generation and Large Language Models (LLMs) to speculate how these approaches may interface with paleontological research. Even though AI has not yet flourished in paleontological research, successful implementation of AI is growing and show promise for transformative effect on the workflow in paleontological research in the years to come. HighlightsO_LIFirst systematic review of AI applications in paleontology. C_LIO_LIThere is a 10 to 20-year gap between AI in paleontology and mainstream studies. C_LIO_LIRecent progress in paleontological AI studies is likely a result of lowering bar in training and deployment. C_LIO_LIFuture direction discussed for interactions between paleontology and AI. C_LI

paleontology↗

bioRxiv2023

Dendritic Cells Overcome Cre/Lox Induced Gene Deficiency by Siphoning Material From Neighboring Cells Using Intracellular Monitoring - a Novel Mechanism of Antigen Acquisition

Macrophages and dendritic cells (DCs) in peripheral tissue interact closely with their local microenvironment by scavenging protein and nucleic acids released by neighboring cells. Material transfer between cell types is necessary for pathogen detection and antigen presentation, but thought to be relatively limited in scale. Recent reports, however, demonstrate that the quantity of transferred material can be quite large when DCs are in direct contact with live cells. This observation may be problematic for conditional gene deletion models that assume gene products will remain in the cell they are produced in. Here, we investigate whether conditional gene deletions induced by the widely used Cre/Lox system can be overcome at the protein level in DCs. Of concern, using the human Langerin Cre mouse model, we find that epidermal Langerhans cells and CD11b+CD103+ mesenteric DCs can overcome gene deletion if the deleted gene is expressed by neighboring cells. Surprisingly, we also find that the mechanism of material transfer does not resemble known mechanisms of antigen uptake, is dependent on extra- and intracellular calcium, PI3K, and scavenger receptors, and mediates a majority of material transfer to DCs. We term this novel process intracellular monitoring, and find that it is specific to DCs, but occurs in all murine DC subsets tested, as well as in human DCs. Transferred material is successfully presented and cross presented on MHC-II and MHC-I, and occurs between allogeneic donor and acceptors cells--implicating this widespread and unique process in immunosurveillance and organ transplantation. ONE SENTENCE SUMMARYDendritic cells maintain RNA and protein levels for conditionally deleted genes by siphoning material from neighboring cells using a novel mechanism.

immunology↗

bioRxiv2023

Extracting herbicide and antibiotic natural products from a plant-microbe interaction system

Plants and their associated microbes live in complicated, changeable, and unpredictable environments. They usually interact with each other in many ways by proceeding in multi-dimensional, multi-scale and multi-level coupling manners, leading to challenges of the co-existence of randomness and determinism, or continuity and discreteness. Gaining a deeper understanding of these diverse interaction mechanisms can facilitate the development of new data mining theories and methods for complex systems, new coupled modelling for the system with different spatiotemporal scales and functional properties, or even universal theory of information and information interactions. In this study, we use a "close-loop" model to present a plant-microbe interaction system and describe the probable functions from the microbial natural products. Specifically, we report a rhizosphere species, Streptomyces ginsengnesis G7, which produces polyketide lydicamycins and other active metabolites. Interestingly, these distinct molecules have the potential to function both as antibiotics and herbicides for crop protection. Detailed laboratory experiments combined with comprehensive bioinformatics analysis allow us to rationalise a model for this specific plant-microbe interaction process. Our work reveals the benefits of exploring otherwise neglectable resources for the identification of novel functional molecules and provides a good reference to better understand the system biology in the complex ecosystems.

cell biology↗

bioRxiv2023

Protein language model-based end-to-end type II polyketide prediction without sequence alignment

Natural products are important sources for drug development, and the precise prediction of their structures assembled by modular proteins is an area of great interest. In this study, we introduce DeepT2, an end-to-end, cost-effective, and accurate machine learning platform to accelerate the identification of type II polyketides (T2PKs), which represent a significant portion of the natural product world. Our algorithm is based on advanced natural language processing models and utilizes the core biosynthetic enzyme, chain length factor (CLF or KS{beta}), as computing inputs. The process involves sequence embedding, data labeling, classifier development, and novelty detection, which enable precise classification and prediction directly from KS{beta} without sequence alignments. Combined with metagenomics and metabolomics, we evaluated the ability of DeepT2 and found this model could easily detect and classify KS{beta} either as a single sequence or a mixture of bacterial genomes, and subsequently identify the corresponding T2PKs in a labeled categorized class or as novel. Our work highlights deep learning as a promising framework for genome mining and therefore provides a meaningful platform for discovering medically important natural products.

evolutionary biology↗

bioRxiv2023

Doxorubicin inhibits phosphatidylserine decarboxylase and confers broad-spectrum antifungal activity

O_LIAs phospholipids of cell membranes, phosphatidylethanolamine (PE) and phosphatidylserine (PS) play crucial roles in glycerophospholipid metabolism. Broadly, some phospholipid biosynthesis enzymes serve as potential fungicide targets. Therefore, revealing the functions and mechanism of PE biosynthesis in plant pathogens would provide potential targets for crop disease control. C_LIO_LIWe performed analyses including phenotypic characterizations, lipidomics, enzyme activity, site-directed mutagenesis, and chemical inhibition assays to study the function of PS decarboxylase-encoding gene MoPSD2 in rice blast fungus Magnaporthe oryzae. C_LIO_LIThe Mopsd2 mutant was defective in development, lipid metabolism and plant infection. The PS level increased while PE decreased in Mopsd2, consistent with the enzyme activity. Furthermore, chemical doxorubicin inhibited the enzyme activity of MoPsd2 and showed antifungal activity against ten phytopathogenic fungi including M. oryzae and reduced disease severity of two crop diseases in the field. Three predicted doxorubicin-interacting residues are important for MoPsd2 functions. C_LIO_LIOur study demonstrates that MoPsd2 is involved in de novo PE biosynthesis and contributes to the development and plant infection of M. oryzae and that doxorubicin shows broad-spectrum antifungal activity as a fungicide candidate. The study also implicates that bacterium Streptomyces peucetius, which biosynthesizes doxorubicin, could be potentially used as an eco-friendly biocontrol agent. C_LI

pathology↗

bioRxiv2023

pan-ECM: live brain extracellular matrix imaging with protein-reactive dye

The brain extracellular matrix (ECM), consisting of proteins and glycosaminoglycans, is a critical scaffold in the development, homeostasis, and disorders of the central nervous system (CNS) and undergoes remodeling in response to environmental cues. Live imaging of brain ECM structure represents a native view of the brain ECM but, until now, remains challenging due to the lack of a robust fluorescent labeling approach. Here, we developed a pan-ECM method for labeling the entire (Greek: pan) brain ECM network by screening and delivering a protein-reactive dye into the brain. pan-ECM enables imaging of ECM compartments in live brain tissue, including the interstitial matrix, basement membrane (BM), and perineuronal nets (PNNs), and even the ECM in glioblastoma and stroke mouse brains. This approach provides access to the structure and dynamics of the ECM and enhances our understanding of the complexities of the brain ECM and its contribution to brain health and disease.

neuroscience↗

bioRxiv2023

Dysregulation of Prefrontal Oligodendrocyte Lineage Cells Across Mouse Models of Adversity and Human Major Depressive Disorder

Animal models of adversity have yielded few molecular mechanisms that translate to human stress-related diseases like major depressive disorder (MDD). We congruently analyze publicly available bulk-tissue transcriptomic data from prefrontal cortex (PFC) in multiple mouse models of adversity and in MDD. We apply strategies, to quantify cell-type specific enrichment from bulk-tissue transcriptomics, utilizing reference single cell RNA sequencing datasets. These analyses reveal conserved patterns of oligodendrocyte (OL) dysregulation across animal experiments, including susceptibility to social defeat, acute cocaine withdrawal, chronic unpredictable stress, early life stress, and adolescent social isolation. Using unbiased methodologies, we further identify a dysregulation of layer 6 neurons that associate with deficits in goal-directed behavior after social isolation. Human post-mortem brains with MDD show similar OL transcriptome changes in Brodmann Areas 8/9 in both male and female patients. This work assesses cell type involvement in an unbiased manner from differential expression analyses across animal models of adversity and human MDD and finds a common signature of OL dysfunction in the frontal cortex.

neuroscience↗

bioRxiv2023

Intravital microscopy of satellite cell dynamics and their interaction with myeloid cells during skeletal muscle regeneration

Skeletal muscle regeneration requires the highly coordinated cooperation of muscle satellite cells (MuSCs) with other cellular components. However, due to technical limitations, it remains unclear how MuSCs dynamically interact with non-myogenic cells, especially myeloid cells, in live animals. In this work, we developed a dual-laser multimodal nonlinear optical microscope platform to serve as an effective tool for studying the real-time interaction between MuSCs and non-myogenic cells during the early phase of muscle regeneration. Increased cell volume and mitochondrial mass, cell density, and myotube formation are indicative of MuSCs activation/growth, proliferation, and differentiation, respectively. Using 3D time-lapse imaging on live reporter mice containing both red fluorescence protein (RFP)-labeled macrophages and yellow fluorescence protein (YFP)-labeled MuSCs, and taking advantages of the autofluorescence of reduced nicotinamide adenine dinucleotide (NADH), we monitored the real-time spatiotemporal interaction between RFP+ macrophages/RFP- non-myogenic cells and YFP+ muscle stem/progenitor cells during the activation and the proliferation stages of regeneration. Our results indicated that their cell-cell contact was transient in nature. By inhibiting macrophage infiltration, we further showed that direct cell-cell contact between macrophages and MuSCs was not required for early activation of MuSCs before the proliferation stage. However, decreased macrophage infiltration impeded the proliferation and differentiation of MuSCs and also led to intramuscular fibrosis. Besides, neutrophil depletion in the CCR2 deficient mice did not delay the initial growth of MuSCs. These findings provide a new perspective on myeloid cells role during muscle regeneration.

cell biology↗

bioRxiv2023

Structure of the Native Chemotaxis Core Signalling Unit from E-gene lysed E. coli cells

Motile bacteria detect ambient chemical gradients and control their locomotion via conserved chemotaxis signaling networks, enabling cells to locate nutrients, potential hosts and other important biological niches. The sensory apparatus of the chemotaxis pathway is an array of core-signaling units (CSU) composed of transmembrane chemoreceptors, the histidine kinase CheA and an adaptor protein CheW. Although chemotaxis pathways represent the best understood signaling systems, a detailed mechanistic understanding of signal transduction has been hindered by the lack of a complete structural picture of the CSU and extended array. In this study, we present the structure of the complete CSU from phage E-gene lysed E. coli cells, determined using cryo-electron tomography and sub-tomogram averaging to 12 [A] resolution. Using AlphaFold2, we further predict the atomic structures of the CSUs constituent proteins as well as key protein-protein interfaces, enabling the assembly an all-atom CSU model, which we conformationally refine using our cryoET map. Molecular dynamics simulations of the resulting model provide new insight into the periplasmic organization of the complex, including novel interactions between neighboring receptor ligand binding domains. Our results further elucidate previously unresolved interactions between individual CheA domains, including an anti-parallel P1 dimer and non-productive binding mode between P1 and P4, enhancing our understanding of the structural mechanisms underlying CheA signaling and regulation.

microbiology↗

bioRxiv2022

Asymmetric HIV-1 envelope trimers bound to one and two CD4 molecules are intermediates during membrane binding

Human immunodeficiency virus 1 (HIV-1) infection is initiated by binding of the viral envelope glycoprotein (Env) to the cell-surface receptor CD4. Although high resolution structures of Env complexed with soluble domains of CD4 have been determined, the binding process is less understood on native membranes. Here, we apply cryo-electron tomography (cryo-ET) to monitor Env-CD4 interactions at membrane-membrane interfaces formed between HIV-1 and CD4-presenting virus-like particles. Env-CD4 complexes organized into clusters and rings, bringing opposing membranes closer together. Additionally, Env-CD4 clustering was dependent on capsid maturation. Subtomogram averaging and classification revealed that Env bound one, two, and finally three CD4 molecules, upon which Env adopted a partially open state. Our data indicate that asymmetric HIV-1 Env trimers bound to one and two CD4 molecules are detectable intermediates during virus binding to host cell membranes, which likely has consequences for antibody-mediated immune responses and vaccine immunogen design.

microbiology↗

bioRxiv2022

Lactate-derived HDAC6 Lactylation as a new target for neuronal protection in cerebral ischemic reperfusion injury

Lactylation is a newly found lactate-derived post-translational modification, which is firstly reported on histone protein lysine residues to regulate gene expression. Here, we provided evidence that higher serum lactate level was possibly associated with better prognosis in ischemic stroke patients. Meanwhile, inhibition of endogenous lactate increased the infarct volume and decreased protein pan-lactylation in the affected brain tissue in cerebral ischemia mice. We further demonstrated that downregulating lactylation level of Hdac6 (Histone Deacetylase 6) in neurons exacerbated ischemic neuronal injury. The underlying mechanisms involved Hdac6 lactylation disturbing calcium homeostasis through binding BiP (Binding immunoglobulin protein), an endoplasmic reticulum-related protein. Collectively, our findings identified a new effect of lactate for neuroprotection through Hdac6 lactylation during cerebral ischemic reperfusion injury which introduced a potential therapeutic approach against ischemic stroke.

neuroscience↗

bioRxiv2022

Machine learning-guided directed evolution for the development of small-molecule antibiotics originating from antimicrobial peptides

Antimicrobial peptides (AMPs) are valuable alternatives to traditional antibiotics that possess a variety of potent biological activities by exerting immunomodulatory effects to clear difficult-to-treat infections. Understanding the structure-activity relationships (SARs) of AMPs can direct the synthesis of desirable therapeutics. In this study, we use machine learning-guided directed evolution to develop the lipopolysaccharide-binding domain (LBD), which acts as a functional domain of anti-lipopolysaccharide factor (ALF), a family of AMPs, identified from Marsupenaeus japonicus. We report the identification of LBDA-D as an output of this algorithm with the input of the original LBDMj sequence and show the NMR solution structure of LBDB, which possesses a circular extended structure with a disulfide crosslink in each terminus and two 310-helices and exhibits a broad antimicrobial spectrum. Scanning electron microscopy and transmission electron microscopy showed LBDB induced the formation of a cluster of bacteria wrapped in a flexible coating that ruptured and consequently killed the bacteria. The co-injection of LBDB and Vibrio alginolyticus, Staphylococcus aureus and another major pathogen in shrimp aquaculture white spot syndrome virus in vivo improved the survival of M. japonicus, indicating a promising therapeutic role of LBDB for infectious disease. The findings of this study pave the way for the rational drug design of activity-enhanced peptide antibiotics.

synthetic biology↗

bioRxiv2022

Quartet protein reference materials and datasets for multi-platform assessment of label-free proteomics

Quantitative proteomics is an indispensable tool in life science research. However, there is a lack of reference materials for evaluating the reproducibility of label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based measurements among different instruments and laboratories. We developed the Quartet as a proteome reference material with built-in truths, and distributed the same aliquots to 15 laboratories with nine conventional LC-MS/MS platforms across six cities in China. Relative abundance of over 12,000 proteins on 816 MS files were obtained and compared for reproducibility among the instruments and laboratories to ultimately generate proteomics benchmark datasets. There was a wide dynamic range of proteomes spanning ~7 orders of magnitude (101-108 copies/cell), and the injection order had marked effects on quantitative instead of qualitative. Overall, the Quartet offers valuable standard materials and data resources for improving the quality control of proteomic analyses as well as the reproducibility and reliability of research findings.

molecular biology↗

bioRxiv2022

Significantly amplified photoacoustic effect for silica-coated gold nanoparticles by interface heat transfer mechanisms

Plasmonic gold nanoparticles (AuNPs) are effective photoacoustic (PA) signal agents and have found important biomedical applications. The silica coating on the surface of AuNPs showed enhanced PA efficiency, however, the PA amplification mechanism remains unclear. Here, we systematically studied the silica coating effect on PA generation of AuNPs under different laser pulse durations. We experimentally demonstrated up to 4-fold PA amplification under thin silica coating (<5 nm) and a picosecond laser excitation. The theoretical model further suggests that the PA amplification originates from two interface heat transfer mechanisms including 1) the enhanced interface thermal conductance on the silica-water interface and 2) the electron-phonon energy transfer channel on the gold/silica interface. This study discovers a regime of large PA amplification and provides a new rationale for plasmonic nanoparticle design to achieve better PA efficiency.

bioengineering↗

bioRxiv2022

Proteomics Characteristics Reveal the Risk of T1 Colorectal Cancer Metastasis to Lymph Nodes

BackgroundThe presence of lymph node metastasis (LNM) affects treatment strategy decisions in T1NxM0 colorectal cancer (CRC), but the currently used clinicopathological-based risk stratification cannot predict LNM accurately. In this study, we established a classifier for predicting LNM in T1 CRC. MethodsWe detected proteins in formalin-fixed paraffin-embedded (FFPE) tumor samples from 143 LNM-negative and 78 LNM-positive patients with T1 CRC and revealed changes in molecular and biological pathways by label-free LC-MS/MS. An effective prediction model was built and validated in a training cohort (N=132) and two validation cohorts (VC1, N=42; VC2, N=47) by machine learning. We further built a simplified classifier with 9 proteins. The expression patterns of 13 proteins were confirmed by immunohistochemistry, and the IHC score of 5 proteins were used to build a IHC predict model. ResultPatients with or without LNM have different molecular signatures. The 55-proteins prediction model achieved an impressive AUC of 1.00 in the training cohort, 0.96 in VC1 and 0.93 in VC2. The 9-protein classifier achieved an AUC of 0.824, and the calibration plot was excellent. We found that 5 biomarkers could predict LNM by the IHC score, with an AUC of 0.825. RHOT2 silence significantly enhanced migration and invasion of colon cancer cells. ConclusionsOur study explored the mechanism of metastasis in T1 CRC and can be used to facilitate the individualized prediction of LNM in patients with T1 CRC, which may provide a guidance for clinical practice in T1 CRC.

cancer biology↗

bioRxiv2022

Human iPSC-derived neuron of 16p11.2 deletion reveals haplotype-specific expression of MAPK3 and its contribution to variable NDD phenotypes

Recurrent proximal 16p11.2 deletion (16p11.2del) is risk factor of diverse neurodevelopmental disorders (NDDs) with variable penetrance. Although previous human induced pluripotent stem cell (hiPSC) models of 16p11.2del confirmed disrupted neuron development, it is not known which gene(s) at this interval are mainly responsible for the abnormal cellular phenotypes and how the NDD penetrance is regulated. After haplotype phasing of 16p11.2 region, we generated hiPSCs for two 16p11.2del families with distinct residual haplotypes and variable NDD phenotypes. We also differentiated the hiPSCs to cortical neural cells and demonstrated MAPK3 as a driver signal of 16p11.2 region contributing to the dysfunctions in multiple pathways related to neuron development, which leads to altered morphological or electrophysiological properties in neuron cells. Furthermore, residual haplotype-specific MAPK3 expression was identified in 16p11.2del neuron cells, associating MAPK3 down-expression with the minor allele of the residual haplotype. Ten SNPs of the residual haplotype are mapped as enhancer SNPs (enSNPs) of MAPK3, eight enSNPs were functionally validated by luciferase assays, implying enSNPs contribute to residual haplotype-specific MAPK3 expression via cis-regulation. Finally, the analyses of three different patient cohorts showed that the residual haplotype of 16p11.2del is associated with variable NDD phenotypes.

genetics↗

bioRxiv2022

Optical Control Of Neuronal Activities With Photoswitchable Nanovesicles

Precise modulation of neuronal activity by neuroactive molecules is essential for understanding brain circuits and behavior. However, tools for highly controllable molecular release are lacking. Here, we developed a photoswitchable nanovesicle with azobenzene-containing phosphatidylcholine (azo-PC), coined azosome, for neuromodulation. Irradiation with 365 nm light triggers the trans-to-cis isomerization of azo-PC, resulting in a disordered lipid bilayer with decreased thickness and cargo release. Irradiation with 455 nm light induces reverse isomerization and switches the release off. Real-time fluorescence imaging shows controllable and repeatable cargo release within seconds (< 3 s). Importantly, we demonstrate that SKF-81297, a dopamine D1-receptor agonist, can be released from the azosome to activate cultures of primary striatal neurons. Azosome shows promise in precise optical control over the molecular release and can be a valuable tool for molecular neuroscience studies.

bioengineering↗

bioRxiv2022

Optical Modulation of Blood-Brain-Tumor Barrier Permeability Enhances Drug Delivery in Diverse Preclinical Glioblastoma Models

Glioblastoma multiforme (GBM) is the most prevalent malignant tumor in the central nervous system. It has diverse phenotypes, including diffuse single-cell infiltration in which the tumor cells co-opt the normal microvasculature, and the neovascularization of an expanding tumor mass. The blood-brain-tumor barrier (BBTB) is a significant obstacle to GBM treatment and restricts entry of most FDA-approved effective oncology drugs. Herein, we report that picosecond laser excitation of vascular-targeted plasmonic gold nanoparticles (AuNPs) can non-invasively and reversibly modulate the BBTB permeability (optoBBTB). OptoBBTB enhances the delivery of paclitaxel (Taxol) in two genetically engineered glioma models (GEMM) that span the spectrum of GBM phenotypes. OptoBBTB followed by Taxol delivery effectively suppresses tumor growth and prolongs the survival time of both GEMM. Moreover, our results raise the possibility that paclitaxel, which is amongst the most widely used oncology drugs because of its proven efficacy but has been abandoned for GBM following its failure to efficacy in early phase clinical trials due to poor blood-brain barrier (BBB) penetration, could now be reconsidered in combination with strategies to increase BBB permeability. In summary, optoBBTB is a novel and effective approach to increase the delivery of therapeutics with limited BBB permeability to treat neoplastic and non-neoplastic brain diseases.

bioengineering↗