Biology subjects

Liao, X.

Publications and source records attributed to Liao, X..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

Development of connectome dynamics at birth predicts neurocognitive outcomes at age 2

The functional connectome of the human brain comprises time-varying network structure that facilitates efficient inter-module communication and support flexible cognitive functions. However, little is known about how the connectome dynamics of the brain emerges and develops at very early stages of human life and whether this dynamics is predictive of neurocognitive outcomes later in life. Here, we employed resting-state functional MRI data from 39 infants (31 to 42 postmenstrual weeks) and a multilayer network model to characterize the development of connectome dynamics during the third trimester and its critical role in predicting future neurocognitive outcomes at 2 years of age. We observed that the modular architecture of baby functional connectomes spontaneously reconfigures over time, with lower network module switching across time primarily in the primary regions and higher module switching mainly in the association areas. With development, the dynamic switching between the brain modules was significantly decreased, primarily located in the lateral precentral gyrus, medial temporal lobe, and subcortical areas. The clustering analysis further revealed that the primary areas displayed a higher developmental rate than the higher-order systems. Using the support vector regression approach, we found that brain connectome dynamics at birth significantly predicted cognitive and language performance at 2 years of age. Our findings highlight the emergence and spatially inhomogeneous maturation of the neonate connectome dynamics, laying a critical neural foundation for the development of cognitive and language skills later in life.

neuroscience↗

bioRxiv2023

Extraordinary preservation of gene collinearity over three hundred million years revealed in homosporous lycophytes

Homosporous lycophytes (Lycopodiaceae) are a deeply diverged lineage in the plant tree of life, having split from heterosporous lycophytes (Selaginella and Isoetes) [~]400 million years ago (MYA). Compared to the heterosporous lineage, Lycopodiaceae has markedly larger genome sizes and remains the last major plant clade for which no genomic data has been available. Here, we present chromosomal genome assemblies for two homosporous lycophyte species, the allotetraploid Huperzia asiatica and the diploid Diphasiastrum complanatum. Remarkably, despite that the two species diverged [~]350 MYA, around 30% of the genes are still in syntenic blocks. Furthermore, both genomes had undergone independent whole genome duplications and the resulting intra-genomic syntenies have likewise been preserved relatively well. Such slow genome evolution over deep time is in stark contrast to heterosporous lycophytes and is correlated with a decelerated rate of nucleotide substitution. Together, the genomes of H. asiatica and D. complanatum not only fill a crucial gap in the plant genomic landscape, but also uncover a possibly unique genomic contrast between homosporous and heterosporous species.

genomics↗

bioRxiv2023

Leading Basic Modes of Spontaneous Activity Drive Individual Functional Connectivity Organization in the Resting Human Brain

Spontaneous activity of the human brain provides a window to explore intrinsic principles of functional organization. However, most studies have focused on interregional functional connectivity. The principles underlying rich repertoires of instantaneous activity remain largely unknown. We apply a novel eigen-microstate analysis to three resting-state functional MRI datasets to identify basic modes that represent fundamental activity patterns that coexist over time. We identify a few (i.e., five) leading basic modes that dominate activity fluctuations. Each of these modes exhibits a distinct functional system-dependent coactivation pattern and corresponds to specific cognitive profiles. In particular, the spatial pattern of the first leading basis mode shows the separation of activity between the default-mode and primary and attention regions. We further reconstruct individual functional connectivity as the weighted contribution of these leading basic modes based on theoretical modelling. Moreover, these leading basic modes capture sleep deprivation-induced changes in brain activity and interregional connectivity, primarily involving the default-mode and task-positive regions. Our findings reveal a dominant set of basic modes of spontaneous activity that reflect multiplexed interregional coordination and drive conventional functional connectivity, furthering the understanding of the functional significance of spontaneous brain activity.

neuroscience↗

bioRxiv2023

AB-Gen: Antibody Library Design with Generative Pre-trained Transformer and Deep Reinforcement Learning

Antibody leads must fulfill multiple desirable properties to be clinical candidates. Primarily due to the low throughput in the experimental procedure, the need for such multi-property optimization causes the bottleneck in preclinical antibody discovery and development, because addressing one issue usually causes another. We developed a reinforcement learning (RL) method, named AB-Gen, for antibody library design using a generative pre-trained Transformer (GPT) as the policy network of the RL agent. We showed that this model can learn the antibody space of heavy chain complementarity determining region 3 (CDRH3) and generate sequences with similar property distributions. Besides, when using HER2 as the target, the agent model of AB-Gen was able to generate novel CDRH3 sequences that fulfill multi-property constraints. 509 generated sequences were able to pass all property filters and three highly conserved residues were identified. The importance of these residues was further demonstrated by molecular dynamics simulations, which consolidated that the agent model was capable of grasping important information in this complex optimization task. Overall, the AB-Gen method is able to design novel antibody sequences with an improved success rate than the traditional propose-then-filter approach. It has the potential to be used in practical antibody design, thus empowering the antibody discovery and development process.

bioinformatics↗

bioRxiv2023

Audit to Forget: A Unified Method to Revoke Patients' Private Data in Intelligent Healthcare

Revoking personal private data is one of the basic human rights, which has already been sheltered by several privacy-preserving laws in many countries. However, with the development of data science, machine learning and deep learning techniques, this right is usually neglected or violated as more and more patients data are being collected and used for model training, especially in intelligent healthcare, thus making intelligent healthcare a sector where technology must meet the law, regulations, and privacy principles to ensure that the innovation is for the common good. In order to secure patients right to be forgotten, we proposed a novel solution by using auditing to guide the forgetting process, where auditing means determining whether a dataset has been used to train the model and forgetting requires the information of a query dataset to be forgotten from the target model. We unified these two tasks by introducing a new approach called knowledge purification. To implement our solution, we developed AFS, a unified open-source software, which is able to evaluate and revoke patients private data from pre-trained deep learning models. We demonstrated the generality of AFS by applying it to four tasks on different datasets with various data sizes and architectures of deep learning networks. The software is publicly available at https://github.com/JoshuaChou2018/AFS.

bioinformatics↗

bioRxiv2023

Osteoblast-intrinsic defect in glucose metabolism impairs bone formation in type II diabetic mice

Skeletal fragility is associated with type 2 diabetes mellitus (T2D), but the underlying mechanism is not well understood. Here, in a mouse model for youth-onset T2D, we show that both trabecular and cortical bone mass are reduced due to diminished osteoblast activity. Stable isotope tracing in vivo with 13C-glucose demonstrates that both glycolysis and glucose fueling of the TCA cycle are impaired in diabetic bones. Similarly, Seahorse assays show suppression of both glycolysis and oxidative phosphorylation by diabetes in bone marrow mesenchymal cells as a whole, whereas single-cell RNA sequencing reveals distinct modes of metabolic dysregulation among the subpopulations. Metformin not only promotes glycolysis and osteoblast differentiation in vitro, but also improves bone mass in diabetic mice. Finally, targeted overexpression of Hif1a or Pfkfb3 in osteoblasts of T2D mice averts bone loss. The study identifies osteoblast-intrinsic defects in glucose metabolism as an underlying cause of diabetic osteopenia, which may be targeted therapeutically.

physiology↗

bioRxiv2023

RNA sequencing identifies lung cancer lineage and facilitates drug repositioning

Breakthrough therapies recently improve survival in lung adenocarcinoma (LUAD), yet we still lack a paradigm to support prospective confirmation. To classify three clusters including bronchioid, neuroendocrine, and squamoid, the non-negative matrix factorization (NMF) algorithm was first performed at The Cancer Genome Atlas (TCGA), Clinical Proteomic Tumor Analysis Consortium (CPTAC), Gene Expression Omnibus (GEO) and preclinical models. In terms of prognostic value, the squamoid cluster is of poor prognostic factor. The neuroendocrine cluster is characterized by STK11 mutations and 14q13.3 amplifications. From an immunological perspective, the bronchioid cluster is considered an immune activation because of the highest immune-related genetic perturbation. Further analysis is the estimation of the relative cell abundance of the tumor microenvironment (TME), specific cell types can be reflected among three clusters. Meanwhile, the higher portion of immune cell infiltration belonged to bronchioid and squamous, not neuroendocrine cluster. Taken together, the neuroendocrine cluster show resistance to PD-L1 blockade. While pemetrexed or platinum-based therapies are suitable for bronchioid and squamoid clusters, respectively. Our emphasis was on phenotype-based action to explore compounds. Large-scale drug sensitivity databases including ConnectivityMap (CMAP), Cancer Cell Line Encyclopedia (CCLE), and Genomics of Drug Sensitivity in Cancer (GDSC) were analyzed. MEK inhibitors exhibited resistance in the bronchioid, while sensitive to the squamous cluster. Dinaciclib and alvocidib showed similar activity and sensitivity in the neuroendocrine cluster. A lineage factor named KLF5 recognized by two networks could be suppressed by verteporfin. This work adds to the knowledge of the lung cancer lineage and facilitates drug repositioning.

cancer biology↗

bioRxiv2022

Hypothalamic supramammillary neurons that project to the medial septum control wakefulness

The hypothalamic supramammillary nucleus (SuM) plays a key role in controlling wakefulness, but the downstream target regions participating in this control process remain unknown. Here, using circuit-specific fiber photometry and single-neuron electrophysiology together with electroencephalogram, electromyogram and behavioral recordings, we find approximately half of SuM neurons that project to the medial septum (MS) are wake-active. Optogenetic stimulation of axonal terminals of SuM-MS projection induces a rapid and reliable transition to wakefulness from NREM or REM sleep, and chemogenetic activation of SuMMS projecting neurons significantly increases wakefulness time and prolongs latency to sleep. Consistently, chemogenetically inhibiting these neurons significantly reduces wakefulness time and latency to sleep. Therefore, these results identify the MS as a functional downstream target of SuM and provide evidence for a causal role for this hypothalamic-septal projection in wakefulness control.

neuroscience↗

bioRxiv2022

Structural connectome architecture shapes the maturation of cortical morphology from childhood to adolescence

Cortical thinning is an important hallmark of the maturation of brain morphology during childhood and adolescence. However, the connectome-based wiring mechanism that underlies cortical maturation remains unclear. Using neuroimaging, connectome, transcriptome, and computational modeling, we mapped cortical thinning patterns primarily located in lateral frontal and parietal heteromodal nodes during childhood and adolescence, which is structurally constrained by white matter network architecture and is particularly represented using a network-based diffusion model. Furthermore, connectome-based constraints are regionally heterogeneous, with the largest constraints residing in frontoparietal nodes, and are associated with gene expression signatures of microstructural neurodevelopmental events. These results are highly reproducible while using another independent dataset. Our findings advance our understanding of network-level mechanisms and the associated genetic basis that underlies the maturational process of cortical morphology during childhood and adolescence.

neuroscience↗

bioRxiv2022

The Cul5 E3 Ligase Complex Is a Key Negative Feedback Regulator of TCR/IL2 Signaling and Anti-Tumor Activity in CD8+ T Cells

CD8+ T cells play an important role in tumor immune surveillance and control. Better understanding of the regulation of their anti-tumor actions and improving their cytotoxic function and persistence will help advancing cancer immunotherapies. Here, we report the development of a step-wise CRISPR knockout (KO) screening strategy under the selection of TGF-{beta}, a clinically relevant immunosuppressive pressure. The screen identifies Cul5 as a negative-feedback regulator of the core signaling pathways, differentiation, and persistence of CD8+ T cell. Cul5 KO in mouse CD8+ T cells significantly improves their tumor control ability in vitro and in vivo with significant proteomic alterations that generally enhance TCR and cytokine signaling, effector function, stemness, and survival of CD8+ T cell. Mechanistically, Cul5, whose protein content and active, neddylated form increase upon TCR-stimulation, interacts with SOCS-box-containing Pcmtd2 and negatively regulates TCR and IL2/STAT5 signaling by decreasing TCR and IL2 signaling molecules. Moreover, Cul5 KO in human CD8+ T cells phenocopies that in mouse CD8+ T cells. Furthermore, KO of CTLA4 that is markedly upregulated by Cul5 KO in mouse and human CD8+ cells further enhances anti-tumor effect of Cul5 KO, and a neddylation inhibitor enhances CD8 effector activities largely dependently of Cul5. These results together not only reveal a previously unknown negative-feedback regulatory mechanism for CD8+ T cells, but also have strong translational implications in cancer immunotherapy.

immunology↗

bioRxiv2022

Genome-scale mapping of functional genes and loci in bacteria for industrial phenotypes

Base editing, the targeted introduction of point mutations into cellular DNA, holds promise for improving genome-scale functional genome screening to single-nucleotide resolution. Current efforts in prokaryotes, however, remain confined to loss-of-function screens using the premature stop codons-mediated gene inactivation library, which falls far short of fully releasing the potential of base editors. Here, we developed a base editor-mediated functional single nucleotide variant screening pipeline in E. coli. We constructed a library with 31,123 sgRNAs targeting 462 stress response-related genes in E. coli, and screened for adaptive mutations under isobutanol and furfural selective conditions. Guided by the screening results, we successfully identified several known and novel functional mutations. Our pipeline might be expanded to the optimization of other phenotypes or the strain engineering in other microorganisms.

bioengineering↗

bioRxiv2022

Utilizing artificial intelligence system to build the digital structural proteome of reef-building corals

Reef-building corals play an important role in the marine ecosystem, and analyzing their proteomes from a structural perspective will exert positive effects on exploring their biology. Here we integrated mass spectrometry with newly published ColabFold to obtain digital structural proteomes of dominant reef-building corals. 8,382 proteins co-expressed in A. muricata, M. foliosa and P. verrucosa were identified, then 8,166 of them got predicted structures after around 4,060 GPU hours of computation. The resulting dataset covers 83.6% of residues with a confident prediction, while 25.9% have very high confidence. Our work provides insight-worthy predictions for coral research, confirms the reliability of ColabFold in practice, and is expected to be a reference case in the impending high-throughput era of structural proteomics.

bioinformatics↗

bioRxiv2022

Probabilistic embedding and clustering with alignment for spatial transcriptomics data integration with PRECAST

Spatially resolved transcriptomics involves a set of emerging technologies that enable the transcriptomic profiling of tissues with the physical location of expressions. Although a variety of methods have been developed for data integration, most of them are for single-cell RNA-seq datasets without consideration of spatial information. Thus, methods that can integrate spatial transcriptomics data from multiple tissue slides, possibly from multiple individuals, are needed. Here, we present PRECAST, a data integration method for multiple spatial transcriptomics datasets with complex batch effects and/or biological effects between slides. PRECAST unifies spatial factor analysis simultaneously with spatial clustering and embedding alignment, while requiring only partially shared cell/domain clusters across datasets. Using both simulated and four real datasets, we show improved cell/domain detection with outstanding visualization, and the estimated aligned embeddings and cell/domain labels facilitate many downstream analyses. We demonstrate that PRECAST is computationally scalable and applicable to spatial transcriptomics datasets from different platforms.

genomics↗

bioRxiv2022

Full-length transcriptome maps of reef-building coral illuminate the molecular basis of calcification, symbiosis, and circadian genes

BackgroundReef-building corals are critical species for sustaining coral reefs and are highly threatened by global climate change. However, relevant transcriptomic data largely rely on short-read sequencing, which severely limits the understanding of coral molecular mechanisms and leaves many important biological questions unresolved. ResultsWe sequenced the full-length transcriptomes of four common and frequently dominant reef-building corals, including two Robusta clade species, Pocillopora damicornis and Pocillopora verrucosa, and two Complexa clade species, Acropora muricata and Montipora foliosa, using the PacBio Sequel II platform. We obtained information on gene functions, structures and expression profiles. Among them, a comparative analysis of biomineralization-related genes provided insights into the molecular basis of coral skeletal density. The gene expression profiles of the symbiote Symbiodiniaceae were also isolated and annotated from the holobiont sequence data; these profiles showed more highly convergent traits related to gene structure and expression level than those of coral hosts. Interestingly, we observed that intracellular algal cells share some evolutionary convergence between intracellular symbiosis in corals and intracellular digestion in amphioxus. Finally, a phylogenetic analysis of key circadian clock genes among 27 evolutionarily representative species indicated that there are four key members in early metazoans, including cry genes; Clock or Npas2; cyc or Arntl; and tim, while per, as the fifth member, occurs in Bilateria. ConclusionsOur work overcomes the incompleteness of short-read sequencing and illuminates the molecular basis of calcification, symbiosis, and circadian genes, thus providing a foundation for further work on the manipulation of skeleton production or symbiosis to promote the survival of these important organisms.

evolutionary biology↗

bioRxiv2022

Genome-Wide DNA Methylation Profiling of the Failing Human Heart with Mechanical Unloading Identifies LINC00881 as an Essential Regulator of Calcium Handling in the Cardiomyocyte

BackgroundHuman heart failure is characterized by global alterations in the myocardial DNA methylation profile, yet little is known about epigenetic regulation of non-coding transcripts and potential reversibility of DNA methylation with left ventricular assist device (LVAD) support. MethodGenome-wide mapping of myocardial DNA methylation was performed in 36 patients with end-stage heart failure at the time of LVAD implant, 8 patients at the time of LVAD explant, and 7 non-failing controls using high-density bead array platform. Transcriptomic and functional studies were performed in human induced pluripotent stem cell derived cardiomyocytes (iPSCs). ResultsEtiology-specific analysis revealed 2079 differentially methylated positions (DMPs) in ischemic cardiomyopathy (ICM) and 261 DMPs in non-ischemic cardiomyopathy (NICM). 192 DMPs were common to ICM and NICM. Analysis of paired samples before and after LVAD support demonstrated reverse methylation of only 3.2% of HF-specific DMPs. Methylation-expression correlation analysis yielded several protein-coding genes that are hypomethylated and upregulated (HTRA1, FAM65A, FBXO16, EFCAB13, AKAP13, RPTOR) or hypermethylated and downregulated (TBX3) in ICM and NICM patients. A novel cardiac-specific super-enhancer lncRNA (LINC00881) is hypermethylated and downregulated in the failing human heart. LINC00881 is an upstream regulator of sarcomere and calcium channel gene expression including MYH6, CACNA1C, and RYR2. LINC00881 knockdown significantly reduced peak calcium amplitude in the beating human iPSCs. ConclusionsFailing human heart exhibits etiology-specific changes in DNA methylation including coding and non-coding regions, which are minimally reversible with mechanical unloading. Epigenetic reprogramming may be necessary to achieve transcriptional normalization and sustained clinical recovery from heart failure.

genomics↗

bioRxiv2022

Structural insight into the individual variability architecture of the functional brain connectome

Human cognition and behaviors depend upon the brains functional connectomes, which vary remarkably across individuals. However, whether and how the functional connectome individual variability architecture is structurally constrained remains largely unknown. Using tractography- and morphometry-based network models, we observed the spatial convergence of structural and functional connectome individual variability, with higher variability in heteromodal association regions and lower variability in primary regions. We demonstrated that functional variability is significantly predicted by a unifying structural variability pattern and that this prediction follows a primary-to-heteromodal hierarchical axis, with higher accuracy in primary regions and lower accuracy in heteromodal regions. We further decomposed group-level connectome variability patterns into individual unique contributions and uncovered the structural-functional correspondence that is associated with individual cognitive traits. These results advance our understanding of the structural basis of individual functional variability and suggest the importance of integrating multimodal connectome signatures for individual differences in cognition and behaviors.

neuroscience↗

bioRxiv2021

Joint dimension reduction and clustering analysis for single-cell RNA-seq and spatial transcriptomics data

Dimension reduction and (spatial) clustering is usually performed sequentially; however, the low-dimensional embeddings estimated in the dimension-reduction step may not be relevant to the class labels inferred in the clustering step. We therefore developed a computation method, Dimension-Reduction Spatial-Clustering (DR-SC), that can simultaneously perform dimension reduction and (spatial) clustering within a unified framework. Joint analysis by DR-SC produces accurate (spatial) clustering results and ensures the effective extraction of biologically informative low-dimensional features. DR-SC is applicable to spatial clustering in spatial transcriptomics that characterizes the spatial organization of the tissue by segregating it into multiple tissue structures. Here, DR-SC relies on a latent hidden Markov random field model to encourage the spatial smoothness of the detected spatial cluster boundaries. Underlying DR-SC is an efficient expectation-maximization algorithm based on an iterative conditional mode. As such, DR-SC is scalable to large sample sizes and can optimize the spatial smoothness parameter in a data-driven manner. With comprehensive simulations and real data applications, we show that DR-SC outperforms existing clustering and spatial clustering methods: it extracts more biologically relevant features than conventional dimension reduction methods, improves clustering performance, and offers improved trajectory inference and visualization for downstream trajectory inference analyses.

genomics↗

bioRxiv2021

A genetic disorder reveals a hematopoietic stem cell regulatory network co-opted in leukemia

The molecular regulation of human hematopoietic stem cell (HSC) maintenance is therapeutically important, but limitations in experimental systems and interspecies variation have constrained our knowledge of this process. Here, we have studied a rare genetic disorder due to MECOM haploinsufficiency, characterized by an early-onset absence of HSCs in vivo. By generating a faithful model of this disorder in primary human HSCs and coupling functional studies with integrative single-cell genomic analyses, we uncover a key transcriptional network involving hundreds of genes that is required for HSC maintenance. Through our analyses, we nominate cooperating transcriptional regulators and identify how MECOM prevents the CTCF-dependent genome reorganization that occurs as HSCs differentiate. Strikingly, we show that this transcriptional network is co-opted in high-risk leukemias, thereby enabling these cancers to acquire stem cell properties. Collectively, we illuminate a regulatory network necessary for HSC self-renewal through the study of a rare experiment of nature.

cell biology↗