Biology subjects

Liang, L.

Publications and source records attributed to Liang, L..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

GABA Increases Sensory Transmission In Monkeys

Sensory input flow is central to voluntary movements. For almost a century, GABA was believed to modulate this flow by inhibiting sensory axons in the spinal cord to sculpt neural inputs into skilled motor output. Instead, here we show that GABA can also facilitate sensory transmission in monkeys and consequently increase spinal and cortical neural responses to sensory inputs challenging our understanding of generation and perception of movement.

neuroscience↗

bioRxiv2023

A multistage, dual voxel study of glutamate in the anterior cingulate cortex in schizophrenia supports a primary pyramidal dysfunction model of disorganization

BackgroundSchizophrenia is an illness where glutamatergic dysfunction in the anterior cingulate cortex (ACC) has been long suspected; Recent in vivo evidence (Adams et al. 2022) has implicated pyramidal dysfunction (reduced glutamate tone) as the primary pathophysiology contributing to subtle features, with a secondary disinhibition effect (higher glutamate tone) resulting in the later emergence of prominent clinical symptoms. We investigate if genetic high risk (GHR) for schizophrenia reduces glutamatergic tone in ACC when compared to the states of clinical high risk (CHR) and first episode schizophrenia (FES) where symptoms are already prominent. MethodsWe recruited 302 individuals across multiple stages of psychosis (CHR, n=63; GHR, n=76; FES, n=96) and healthy controls (n=67) and obtained proton magnetic resonance spectroscopy of glutamate from perigenual ACC (pACC) and dorsal ACC (dACC) using 3-Tesla scanner. ResultsGHR had lower Glu compared to CHR while CHR had higher Glu compared to FES and HC. Higher disorganization burden, but not any other symptom domain, was predicted by lower levels of Glu in the GHR group (dACC and pACC) and in the CHR group (pACC only). ConclusionsThe reduction in glutamatergic tone in GHR supports the case for a pyramidal dysfunction contributing to higher disorganization, indicating disorganization to be the core domain in the pathophysiology of schizophrenia. Higher glutamate (likely due to disinhibition) is apparent when psychotic symptoms are raising to be prominent (CHR), though at the full-blown stage of psychosis, the relationship between glutamate and symptoms ceases to be a simple linear one.

neuroscience↗

bioRxiv2023

Population genetic analyses of longitudinal vaginal microbiome reveal racioethnic evolutionary dynamics and prevailing positive selection of Lactobacillus adhesins

The vaginal microbiome is important for reproductive health and should constantly evolve in response to dynamic host-microbe interactions. The composition of the vaginal microbiome is associated with ethnicity; however, the evolutionary landscape of the vaginal microbiome, especially in the multi-ethnic context, remains under-studied. In this study, we performed a longitudinal evolutionary vaginal microbiome analysis of 351 samples from 35 pregnant women with diverse ethnic backgrounds and validated the main findings in two cohorts totaling 462 samples from 90 multi-ethnic women. Microbiome alpha diversity and community states showed strong ethnic signatures. Lactobacillaceae species had a significantly higher nonsynonymous/synonymous mutation ratio (pN/pS) than non-Lactobacillaceae species in all ethnicities. In addition, non-Lactobacillaceae anaerobic bacteria were enriched in Black and Latino women, with significantly elevated nucleotide diversity and lower pN/pS in Black women. Intriguingly, the Lactobacillaceae species had a large repertoire of positively selected genes, including the human mucin-binding and bacterial cell wall anchor genes, which showed independent, recurrent signatures of positive selection across multiple strains, indicating that the host-microbiome interactions directly drive microbial evolution at the molecular interface. Finally, we propose that the evolutionary metrics reflect the environmental niches of adapting microbes. Our study revealed the extensive ethnic signatures in vaginal microbial diversity, composition, community state, and evolutionary dynamics at species and gene levels, highlighting the importance of studying the host-microbiome ecosystem from an evolutionary perspective. HighlightsO_LIExtensive ethnic signatures in the vaginal microbial diversity, composition, community state, and evolutionary dynamics were demonstrated. C_LIO_LIHealthy Lactobacillaceae species showed lower nucleotide diversity but much more relaxed or even positive selection of genes than non-Lactobacillaceae species. C_LIO_LIIn Black women, non-Lactobacillaceae species displayed higher nucleotide diversity and more stringent negative selection. C_LIO_LILactobacillus mucin-binding and cell wall anchor genes showed convergent signatures of positive selection across vaginal microbiomes. C_LI

microbiology↗

bioRxiv2023

A conserved N-terminal motif of CUL3 mediates assembly and licenses E3 ligase activation of CRL3KLHL22

The CUL3-RING E3 ubiquitin ligases (CRL3s) play an essential role in response to extracellular nutrition and stress stimuli. The ubiquitin ligase function of CRL3s is activated through E3-E3 dimerization. However, how and why such a dimeric assembly is required for its ligase activity remains elusive. Here, we report the cryo-EM structure of the dimeric CRL3KLHL22 complex and reveal a conserved N-terminal motif in CUL3 that mediates the dimerization assembly and licenses the activation of CRL3KLHL22. Deletion of the CUL3 N-terminal motif leads to non-stochiometric assembly and impairs E3 activity of both CRL3KLHL22 and several other CRL3s. In addition, we found that the dynamics of dimeric E3-E3 superassembly generates a variable ubiquitination zone, potentially facilitating substrate recognition and ubiquitination. These findings demonstrate a CUL3 N-terminal motif-dependent E3-E3 superassembly mechanism and provide insights into the assembly and activation of CRL3s.

molecular biology↗

bioRxiv2023

Biomechanical stress analysis of Type-A aortic dissection at pre-dissection, post-dissection, and post-repair states

Acute type A aortic dissection remains a deadly and elusive condition, with risk factors such as hypertension, bicuspid aortic valves, and genetic predispositions. As existing guidelines for surgical intervention based solely on aneurysm diameter face scrutiny, there is a growing need to consider other predictors and parameters, including wall stress, in assessing dissection risk. Through our research, we aim to elucidate the biomechanical underpinnings of aortic dissection and provide valuable insights into its prediction and prevention. We applied finite element analysis (FEA) to assess stress distribution on a rare dataset comprising computed tomography (CT) images obtained from eight patients at three stages of aortic dissection: pre-dissection (preD), post-dissection (postD), and post-repair (postR). Our findings reveal significant increases in both mean and peak aortic wall stresses during the transition from the preD state to the postD state, reflecting the mechanical impact of dissection. Surgical repair effectively restores aortic wall diameter to pre-dissection levels, documenting its effectiveness in mitigating further complications. Furthermore, we identified stress concentration regions within the aortic wall that closely correlated with observed dissection borders, offering insights into high-risk areas. This study demonstrates the importance of considering biomechanical factors when assessing aortic dissection risk. Despite some limitations, such as uniform wall thickness assumptions and the absence of dynamic blood flow considerations, our patient-specific FEA approach provides valuable mechanistic insights into aortic dissection. These findings hold promise for improving predictive models and informing clinical decisions to enhance patient care.

bioengineering↗

bioRxiv2023

A Cryptic Basic Groove formed by Ubiquitin and Histone H3 Mediates the Selective Recognition of H2AK119Ub Nucleosomes by Synovial Sarcoma X Breakpoint 1 Protein

The cancer-specific fusion oncoprotein SS18-SSX1 disturbs chromatin accessibility by hijacking the BAF complex from the promoters and enhancers to the polycomb-repressed chromatin regions. This process relies on the selective recognition of H2AK119Ub nucleosomes by SSX1. However, the mechanism by which SSX1 selective recognition of H2AK119Ub nucleosomes in the absence of ubiquitin (Ub)-binding capacity remains unknown. Here we report the cryo-EM structure of SSX1 bound to H2AK119Ub nucleosomes at 3.1 [A] resolution. Combined in vitro biochemical and cellular assays revealed that the Ub recognition by SSX1 is unique and depends on a cryptic basic groove formed by H3 and the Ub motif on the H2AK119 site. Moreover, this unorthodox binding mode of SSX1 induces DNA unwrapping at the entry/exit sites. Together, our results describe a unique mode of site-specific ubiquitinated nucleosome recognition that underlies the specific hijacking of the BAF complex to polycomb regions by SS18-SSX1 in synovial sarcoma.

molecular biology↗

bioRxiv2023

Structural Visualization of HECT-E3 Ufd4 accepting and transferring Ubiquitin to Form K29/K48-branched Polyubiquitination on N-degron

The K29/K48-linked ubiquitination generated by the cooperative catalysis of E3 ligase Ufd4 and Ubr1 is an enhanced protein degradation signal, in which Ufd4 is responsible for introducing K29-linked ubiquitination to K48-linked ubiquitin chains to augment polyubiquitination. How HECT-E3 ligase Ufd4 mediates the ubiquitination event remains unclear. Here, we biochemically determine that Ufd4 preferentially catalyses K29-linked ubiquitination on K48-linked ubiquitin chains to generate K29/K48-branched ubiquitin chains and capture structural snapshots of Ub transfer cascades for Ufd4-mediated ubiquitination. The N-terminal ARM region and HECT domain C-lobe of Ufd4 are identified and characterized as key structural elements that together recruit K48-linked diUb and orient Lys29 of its proximal Ub to the active cysteine of Ufd4 for K29-linked branched ubiquitination. These structures not only provide mechanistic insights into the architecture of the Ufd4 complex but also provide structural visualization of branched ubiquitin chain formation by a HECT-type E3 ligase.

biochemistry↗

bioRxiv2023

Synergistic Integration of Deep Neural Networks and Finite Element Method with Applications for Biomechanical Analysis of Human Aorta

Motivation: Patient-specific finite element analysis (FEA) has the potential to aid in the prognosis of cardiovascular diseases by providing accurate stress and deformation analysis in various scenarios. It is known that patient-specific FEA is time-consuming and unsuitable for time-sensitive clinical applications. To mitigate this challenge, machine learning (ML) techniques, including deep neural networks (DNNs), have been developed to construct fast FEA surrogates. However, due to the data-driven nature of these ML models, they may not generalize well on new data, leading to unacceptable errors. MethodsWe propose a synergistic integration of DNNs and finite element method (FEM) to overcome each others limitations. We demonstrated this novel integrative strategy in forward and inverse problems. For the forward problem, we developed DNNs using state-of-the-art architectures, and DNN outputs were then refined by FEM to ensure accuracy. For the inverse problem of heterogeneous material parameter identification, our method employs a DNN as regularization for the inverse analysis process to avoid erroneous material parameter distribution. ResultsWe tested our methods on biomechanical analysis of the human aorta. For the forward problem, the DNN-only models yielded acceptable stress errors in majority of test cases; yet, for some test cases that could be out of the training distribution (OOD), the peak stress errors were larger than 50%. The DNN-FEM integration eliminated the large errors for these OOD cases. Moreover, the DNN-FEM integration was magnitudes faster than the FEM-only approach. For the inverse problem, the FEM-only inverse method led to errors larger than 50%, and our DNN-FEM integration significantly improved performance on the inverse problem with errors less than 1%.

bioengineering↗

bioRxiv2023

Identification of a novel MCR-1 variant displaying low level of co-resistance to β-lactam antibiotics that uncovers a potential novel antimicrobial peptide

The emerging and global spread of a novel plasmid-mediated colistin resistance gene, mcr-1, threatens human health. It is accepted that MCR-1 affects bacterial fitness, and this fitness cost correlates with bacterial membrane lipid A perturbation. However, the detailed molecular mechanism remains unclear. Here, we screened out a novel MCR-1 variant, named M6, with a two-point mutation that rendered a low level of co-resistance to {beta}-lactam antibiotics. Compared to wild-type (WT) MCR-1, this variant caused severe lipid A perturbation resulting in peptidoglycan layer remodelling and thus resulted in phenotypic co-resistance to {beta}-lactams. Moreover, we found that a lipid A loading cavity is localized at the linker domain of MCR-1 and governs colistin resistance and bacterial membrane permeability, and the mutated pocket of M6 facilitates the binding affinity of lipid A. More importantly, synthetic peptides derived from M6 achieved broad-spectrum antimicrobial activity. These findings provide insights into a potential vulnerability that could be exploited in future antimicrobial drug design.

microbiology↗

bioRxiv2023

PyTorch-FEA: Autograd-enabled Finite Element Analysis Methods with Applications for Biomechanical Analysis of Human Aorta

MotivationFinite-element analysis (FEA) is widely used as a standard tool for stress and deformation analysis of solid structures, including human tissues and organs. For instance, FEA can be applied at a patient-specific level to assist in medical diagnosis and treatment planning, such as risk assessment of thoracic aortic aneurysm rupture/dissection. These FEA-based biomechanical assessments often involve both forward and inverse mechanics problems. Current commercial FEA software packages (e.g., Abaqus) and inverse methods exhibit performance issues in either accuracy or speed. MethodsIn this study, we propose and develop a new library of FEA code and methods, named PyTorch-FEA, by taking advantage of autograd, an automatic differentiation mechanism in PyTorch. We develop a class of PyTorch-FEA functionalities to solve forward and inverse problems with improved loss functions, and we demonstrate the capability of PyTorch-FEA in a series of applications related to human aorta biomechanics. In one of the inverse methods, we combine PyTorch-FEA with deep neural networks (DNNs) to further improve performance. ResultsWe applied PyTorch-FEA in four fundamental applications for biomechanical analysis of human aorta. In the forward analysis, PyTorch-FEA achieved a significant reduction in computational time without compromising accuracy compared with Abaqus, a commercial FEA package. Compared to other inverse methods, inverse analysis with PyTorch-FEA achieves better performance in either accuracy or speed, or both if combined with DNNs.

bioengineering↗

bioRxiv2023

Comprehensive characterization of tumor microenvironment in colorectal cancer via histopathology-molecular analysis

PurposeTo explain how the tumor microenvironment (TME) contributes to biological and clinical heterogeneity of colorectal cancer (CRC). MethodsUsing multi-omics analysis, single cell transcriptomic sequencing analysis and artificial intelligence-enabled spatial analysis of whole-slide images, we performed a comprehensive characterization of TME in colorectal cancer (CCCRC). ResultsCRC samples were classified into four CCCRC subtypes with distinct TME features, namely, C1 as the proliferative subtype with low immunogenicity; C2 as the immunosuppressed subtype with the terminally exhausted immune characteristics; C3 as the immune-excluded subtype with the distinct upregulation of stromal components and a lack of T cell infiltration in tumor core; and C4 as the immunomodulatory subtype with the remarkable upregulation of anti-tumor immune components. The four CCCRC subtypes had distinct histopathological and molecular characteristics, therapeutic efficacy, and prognosis. The C1 subtype was more sensitive to chemotherapy, the C2 and C3 subtypes were more sensitive to WNT pathway inhibitor SB216763 and Hedgehog pathway inhibitor vismodegib, and the C4 subtype was suitable for ICB treatment. Finally, we established a single-sample gene classifier for identifying the CCCRC subtypes. ConclusionsOur integrative analyses ultimately established a holistic framework to thoroughly dissect the TME of CRC, and the CCCRC classification system with high biological interpretability might facilitate biomarker discoveries and clinical treatment decisions in the future.

cancer biology↗

bioRxiv2022

Taxonomic and carbon metabolic diversification of Bathyarchaeia during its co-evolution history with the early Earth surface environment

Bathyarchaeia, as one of the most abundant microorganisms on Earth, play vital roles in the global carbon cycle. However, our understanding of their origin, evolution and ecological functions remains poorly constrained. Based on the phylogeny of the present largest dataset of Bathyarchaeia metagenome assembled genome (MAG), we reclassified Bathyarchaeia into eight order-level units and corresponded to the former subgroup system. Highly diversified and versatile carbon metabolisms were discovered among different orders, particularly atypical C1 metabolic pathways, indicating that Bathyarchaeia represent overlooked important methylotrophs. Molecular dating results indicate that Bathyarchaeia diverged at [~]3.3 Ga, followed by three major diversifications at [~]3.0 Ga, [~]2.5 Ga and [~]1.8-1.7 Ga, likely driven by continental emergence, growth and intensive submarine volcanism, respectively. The lignin-degrading Bathyarchaeia clade emerged at [~]300 Ma and perhaps contributed to the sharply decreased carbon sequestration rate during the Late Carboniferous period. The evolutionary pathway of Bathyarchaeia potentially have been shaped by geological forces, which in turn impacted the Earths surface environment. TeaserThe origin and divergence of Bathyarchaeia linked to the early Earth tectonics and surface environment changes

microbiology↗

bioRxiv2022

Autism-associated transcriptional regulators target shared loci proximal to brain-expressed genes.

Many autism spectrum disorder (ASD)-associated genes act as transcriptional regulators (TRs). ChIP-seq was used to identify the regulatory targets of ARID1B, BCL11A, FOXP1, TBR1, and TCF7L2, ASD-associated TRs in the developing human and mouse cortex. These TRs shared substantial overlap in the binding sites, especially within open chromatin. The overlap within a promoter region, 1-2,000bp upstream of transcription start site, was highly predictive of brain expressed genes. This signature was observed at 96 out of 102 ASD-associated genes. In vitro CRISPRi against ARID1B and TBR1 delineated downstream convergent biology in mouse cortical cultures. After eight days, NeuN+ and CALB+ cells were decreased, GFAP+ cells were increased, and transcriptomic signatures correlated with the postmortem brain samples from individuals with ASD. We suggest functional convergence across five ASD-associated TRs leads to shared neurodevelopmental outcomes of haploinsufficient disruption.

genomics↗

bioRxiv2022

Deleterious Mechanical Deformation Selects Mechanoresilient Cancer Cells with Enhanced Proliferation and Chemoresistance

Cancer cells derived from secondary tumors can form new distant metastases more efficiently as compared to their primary tumor counterparts. This is partially due to the unfavorable microenvironments encountered by metastasizing cancer cells that result in the survival of a more metastatic phenotype from the original population. However, it is unclear how cancer cells may acquire such metastatic competency after overcoming deleterious mechanical stresses. Here, by forcing cancer cells to flow through small capillary-sized constrictions, we demonstrate that mechanical deformation can select a tumor cell subpopulation that exhibits resilience to mechanical squeezing-induced cell death. Transcriptomic profiling reveals up-regulated proliferation and DNA damage response pathways in this subpopulation, which are further translated into a more proliferative and chemotherapy-resistant phenotype. Our results highlight a potential link between the microenvironmental physical barriers and the enhanced malignancy of metastasizing cancer cells which may potentially be utilized for novel therapeutic strategies in preventing the metastatic spread of cancer cells.

cancer biology↗

bioRxiv2022

The fitness landscape of the mobilized colistin resistance gene mcr-1

The emergence and global discovery of the mobilized colistin resistance gene, mcr-1, limits the clinical effectiveness of colistin as last-resort antibiotic against multiple-drug resistant bacteria. Although MCR-1 exhibits low levels of colistin resistance in E. coli, it is currently unknown whether mcr-1 may potentially evolve a high level of colistin resistance in the future. Here, we generated mcr-1 mutant library that included 27,965 variants, covering 94.44% of the single-nucleotide mutations. We quantified the relative growth of these variant strains under colistin exposure. Notably, most mutations in the catalytic domain, but not in the transmembrane domain, reduce colistin resistance. The structural basis for the mutational effects revealed that the transmembrane domain may contribute to MCR-1 evolution. Altogether, our data shed light on the prediction of MCR-1 evolution, which could be useful for designing novel treatment strategies.

evolutionary biology↗

bioRxiv2022

Longitudinal Urine Metabolic Profiling and Gestational Age Prediction in Pregnancy

Pregnancy is a critical time that has long-term impacts on both maternal and fetal health. During pregnancy, the maternal metabolome undergoes dramatic systemic changes, although correlating longitudinal changes in maternal urine remain largely unexplored. We applied an LCMS-based untargeted metabolomics profiling approach to analyze 346 longitudinal maternal urine samples collected throughout pregnancy for 36 women from diverse ethnic backgrounds with differing clinical characteristics. We detected 20,314 metabolic peaks and annotated 875 metabolites. Altered metabolites include a broad panel of glucocorticoids, lipids, and amino acid derivatives, which revealed systematic pathway alterations during pregnancy. We also developed a machine-learning model to precisely predict gestational age (GA) at time of sampling using urine metabolites that provides a non-invasive method for pregnancy dating. This longitudinal maternal urine study demonstrates the clinical utility of using untargeted metabolomics in obstetric settings. One Sentence SummaryMachine-learning based gestational age and due date using longitudinal urine samples of pregnancy.

systems biology↗

bioRxiv2022

Deep Learning-based Pseudo-Mass Spectrometry Imaging Analysis for Precision Medicine

Liquid chromatography-mass spectrometry (LC-MS) based untargeted metabolomics provides systematic profiling of metabolic. Yet its applications in precision medicine (disease diagnosis) have been limited by several challenges, including metabolite identification, information loss, and low reproducibility. Here, we present the deepPseudoMSI project (https://www.deeppseudomsi.org/), which converts LC-MS raw data to pseudo-MS images and then processes them by deep learning for precision medicine, such as disease diagnosis. Extensive tests based on real data demonstrated the superiority of deepPseudoMSI over traditional approaches and the capacity of our method to achieve an accurate individualized diagnosis. Our framework lays the foundation for future metabolic-based precision medicine.

bioinformatics↗

bioRxiv2022

A Standardized Framework for Taxonomy Analysis in Bacterial Kingdom based on Protein Domain

The taxonomy research on the bacterial kingdom is important and can be usually conducted by the analysis on conserved genes, 16s rRNA, protein domain, and so on. Comparatively, the protein domains maintain a most direct relationship with phenotypes. In this paper, based on the protein domain, we propose a 3-step framework to standardize the classification process of bacteria. Different model candidates are involved and discussed in each step. By comparing the classification results with existing taxonomy, we select the most appropriate candidate to improve the framework, and furthermore, discuss their biological significance. Finally, we put forward taxonomy suggestions based on the best classification results. ImportanceWe standardize a 3-step framework to carry out bacterial taxonomy research based on protein domain. Furthermore, we filter out the best solution in each step that can together generate the most appropriate classification result, and at the same time, we discuss the biological significant it indicates. Finally, we propose suggestions on NCBI bacterial taxonomy based on the classification results.

bioinformatics↗