Biology subjects

Liu, D.

Publications and source records attributed to Liu, D..

At least 325 records · Page 18Linked to original sources

bioRxiv2021

Structure Insight into Photosystem I Octamer from Cyanobacteria

Diversity of photosystem oligomers is essential to understand how photosynthetic organisms adopted to light conditions. Given by the structural and physiological significance, the assemblies of PSI supercomplex is of great interest in both chloroplast and cyanobacteria recently. In this study, two novel photosystem I supercomplexes were isolated for the first time from the low light incubated culture of filamentous cyanobacterium Anabaena sp. PCC 7120. These complexes were defined as PSI hexamers and octamers through biochemical and biophysical characterization. Their 77K emission spectra indicated that the red forms of chlorophylls seemed not to be affected during oligomerization. By cryo-EM single particle analysis, a near-atomic (7.0 [A]) resolution structure of PSI octamer was resolved, and the molecular assemblies of stable PSI octamer was revealed.

biophysics↗

bioRxiv2021

Dissecting tumor cell programs through group biology estimation in clinical single-cell transcriptomics

Given the growing number of clinically integrated cancer single-cell transcriptomic studies, robust differential enrichment methods for gene signatures to dissect tumor cellular states for discovery and translation are critical. Current analysis strategies neither adequately represent the hierarchical structure of clinical single-cell transcriptomic datasets nor account for the variability in the number of recovered cells per sample, leading to results potentially confounded by sample-driven biology with high false positives instead of accurately representing true differential enrichment of group-level biology (e.g., treatment responders vs. non-responders). This problem is especially prominent for single-cell analyses of the tumor compartment, because high intra-patient similarity (as opposed to inter-patient similarity) results in stricter hierarchical structured data that confounds enrichment analysis. Furthermore, to identify signatures which are truly representative of the entire group, there is a need to quantify the robustness of otherwise statistically significant signatures to sample exclusion. Here, we present a new nonparametric statistical method, BEANIE, to account for these issues, and demonstrate its utility in two cancer cohorts stratified by clinical groups to reduce biological hypotheses and guide translational investigations. Using BEANIE, we show how the consideration of sample-specific versus group biology greatly decreases the false positive rate and guides identification of robust signatures that can also be corroborated across different cell type compartments.

bioinformatics↗

bioRxiv2021

Metabolite profiling reveals organ-specific flavone accumulation in Scutellaria and identifies a scutellarin isomer isoscutellarein 8-O-β-glucuronopyranoside

Scutellaria is a genus of plants containing multiple species with well-documented medicinal effects. S. baicalensis and S. barbata are among the best-studied Scutellaria species, and previous works have established flavones to be the primary source of their bioactivity. Recent genomic and biochemical studies with S. baicalensis and S. barbata have advanced our understanding of flavone biosynthesis in Scutellaria. However, as over several hundreds of Scutellaria species occur throughout the world, flavone biosynthesis in most species remains poorly understood. In this study, we analyzed organ-specific flavone profiles of seven Scutellaria species, including S. baicalensis, S. barbata and two species native to the Americas (S. wrightii to Texas and S. racemosa to Central and South America). We found that the roots of almost all these species produce only 4-deoxyflavones, while 4-hydroxyflavones are accumulated exclusively in their aerial parts. On the other hand, S. racemosa and S. wrightii also accumulated high levels of 4-deoxyflavones in their aerial parts, different with the flavone profiles of S. baicalensis and S. barbata. Furthermore, our metabolomics and NMR study identified the accumulation of isoscutellarein 8-O-{beta}-glucuronopyranoside, a rare 4-hydroxyflavone, in the stems and leaves of several Scutellaria species including S. baicalensis and S. barbata, but not in S. racemosa and S. wrightii. Distinctive organ-specific metabolite profiles among Scutellaria species indicate the selectivity and diverse physiological roles of flavones.

plant biology↗

bioRxiv2021

KIRCLE: An Analysis of Variations in KIR Genes in The Cancer Genome Atlas and UK Biobank

BackgroundNatural killer (NK) cells represent a critical component of the innate immune systems response against cancer and viral infections, among other diseases. To distinguish healthy host cells from infected or tumor cells, killer immunoglobulin receptors (KIR) on NK cells bind and recognize Human Leukocyte Antigen (HLA) complexes on their target cells. Just like the HLAs they bind, these KIRs exhibit high allelic diversity in the human population. ResultsIn order to better understand these immunoreceptors, we have developed KIRCLE, a novel method for genotyping individual KIR genes from whole exome sequencing data, and used it to analyze approximately 60,000 patient samples in The Cancer Genome Atlas and UK Biobank. We were able to assess population frequencies for different KIR alleles and demonstrate that, similar to HLA alleles, individuals KIR alleles correlate strongly with their ethnicities. In addition, we observed associations between different KIR alleles and HLA alleles, including HLA-B*53 with KIR3DL2*013 (Fishers Exact FDR = 7.64e-51). Finally, we showcased statistically significant associations between KIR alleles and various clinical correlates, including peptic ulcer disease (Fishers Exact FDR = 0.0429) and age of onset of atopy and various KIR alleles (Mann-Whitney-U FDR = 0.0751). ConclusionsKIR polymorphism and NK cells play a critical role in many diseases, often through their interactions with HLA complexes. Peptic ulcer disease and atopy are just two diseases in which NK cells may play a role beyond their "classical" realm of anti-tumor and anti-viral responses.

bioinformatics↗

bioRxiv2021

Gene regulatory network analysis identifies key genes and regulatory mechanisms involved in acute myocardial infarction using bulk and single cell RNA-seq data

Cardiovascular and cerebrovascular diseases are leading causes of death worldwide, accounting for more than 40% of all deaths in China. Acute myocardial infarction (AMI) is a common cardiovascular disease and traditionally divided into ST-segment (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI), which are known with different prognoses and treatment strategies. However, key regulatory genes and pathways involved in AMI that may be used as potential biomarker for prognosis are unknown. In this study, we constructed weighted gene co-expression networks for differential expressed genes between STEMI and NSTEMI patients based on whole-blood RNA-seq transcriptomics. Network topological attributes (e.g., node degree, betweenness) were analyzed to identify key genes involved in different functional network modules. Furthermore, we used single-cell RNA-seq data to construct multilayer signaling network to infer regulatory mechanisms of the above key genes. PLAUR (receptor for urokinase plasminogen activator) was found to play a vital role in transducing inter-cellular signals from endothelial cells and fibroblast cells to intra-cellular pathways of myocardial cells, leading to gene expression involved in cellular response to hypoxia. Our study sheds lights on identifying molecular biomarkers for diagnosis and prognosis of AMI, and provides candidate key regulatory genes for further experimental validation.

bioinformatics↗

bioRxiv2021

Innate and adaptive immunity to transfused allogenic red blood cells in mice requires MyD88

Red blood cell (RBC) transfusion therapy is essential for the survival of patients with hematological disorders such as sickle cell anemia. A potentially fatal complication of transfusion is development of non-ABO alloantibodies to polymorphic RBC antigens, yet mechanisms of alloantibody formation remain unclear. Human and mouse RBCs acquire a "storage lesion" prior to transfusion, which in mice contributes to immunogenicity. We previously reported that mouse splenic dendritic cells (DCs) are required for RBC alloimmunization and are activated by sterile and leukoreduced mouse RBCs after storage. Yet how syngeneic RBCs activate innate immune pathways to induce DC activation is unknown. We now show that DC activation to transfused RBCs occurs regardless of alloantigen presence, suggesting that RBC damage induced during storage triggers innate immune receptors. We discovered an unexpected dependence of RBC alloimmunization on the Toll-like receptor (TLR) signaling adaptor molecule MyD88. TLRs are a class of pattern recognition receptors (PRRs) that regulate DC activation and signal through two adaptor molecules, MyD88 and TRIF. We show that the inflammatory cytokine response, DC activation, and the subsequent alloantibody response to transfused syngeneic RBCs require MyD88 but not TRIF, suggesting a restricted set of PRRs are responsible for sensing RBCs and triggering alloimmunization.

immunology↗

bioRxiv2021

A bacterium-like particle vaccine displaying Zika virus prM-E induces systemic immune responses in mice

The emergence of Zika virus (ZIKV) infection, which is an unexpectedly associated with congenital defects, has prompted the development of safe and effective vaccines. The gram-positive enhancer matrix-protein anchor (GEM-PA) display system has emerged as a versatile and highly effective platform for delivering target proteins for vaccines. In this article, we developed a bacterium-like particle vaccine ZI-{Delta}-PA-GEM based on the GEM-PA system. The fusion protein ZI-{Delta}-PA, which contains the prM-E-{Delta} protein of ZIKV (with a stem-transmembrane region deletion) and the protein anchor PA3, was expressed. The fusion protein was successfully displayed on the GEM surface, forming ZI-{Delta}-PA-GEM. Moreover, when BALB/c mice were immunized intramuscularly with ZI-{Delta}-PA-GEM combined with 201 VG and poly(I:C) adjuvants, durable ZIKV-specific IgG and protective neutralizing antibody responses were induced. Potent B cell/DC activation was also be stimulated early after immunization. Remarkably, splenocyte proliferation, the secretion of multiple cytokines, T/B cell activation and central memory T cell responses were elicited. These data indicate that ZI-{Delta}-PA-GEM is a promising bacterium-like particle vaccine candidate for ZIKV. Author summaryBecause Zika virus (ZIKV) infection is considered as an example of "disease X", the development of a safe and effective ZIKV vaccine is essential. The gram-positive enhancer matrix-protein anchor (GEM-PA) display system has been used in many vaccine studies due to its advantages. In this study, prM-E-{bigtriangleup} protein of ZIKV (with a stem-transmembrane region deletion) and the protein anchor PA3 was fusion expressed, termed ZI-{bigtriangleup}-PA. Then the fusion protein ZI-{bigtriangleup}-PA could be displayed on the surface of GEM, forming ZI-{bigtriangleup}-PA-GEM. The author evaluated the immunogenicity of ZI-{bigtriangleup}-PA-GEM with the 201 VG and poly(I:C) adjuvants. The study demonstrates that ZI-{bigtriangleup}-PA-GEM induced mice to produce neutralizing antibody and specific cellular immune responses. The author believe that the bacterium-like particle vaccine ZI-{bigtriangleup}-PA-GEM has the potential to be used as the ZIKV vaccine.

microbiology↗

bioRxiv2021

Sub-3 Angstrom cryo-EM structure of RNA enabled by engineered homomeric self-assembly

Many functional RNAs fold into intricate and precise 3D architectures, and high-resolution structures are required to understand their underlying mechanistic principles. However, RNA structural determination is difficult. Herein, we present a nanoarchitectural strategy to enable the efficient single-particle cryogenic electron microscopy (cryo-EM) analysis of RNA-only structures. This strategy, termed RNA oligomerization-enabled cryo-EM via installing kissing-loops (ROCK), involves the engineering of target RNAs by installing kissing-loop sequences onto functionally nonessential stems for the assembly into closed homomeric nanoarchitectures. Assembly with geometric restraints leads to (1) molecular weight multiplication and (2) structural flexibility mitigation, both beneficial for cryo-EM analysis. Together with construct optimization and symmetry-expansion reconstruction, ROCK yields the cryo-EM reconstruction of the Tetrahymena group I intron at an overall resolution of 2.98 [A] (2.85 [A] resolution for the core domains), enabling the de novo model building of the complete intron RNA including previously unknown peripheral domains. When applied to smaller RNAs, ROCK readily produces modest-resolution maps, revealing the conformational rearrangement of the Azoarcus group I intron and the bound ligand in the FMN riboswitch. Our work unleashes the largely unexplored potential of cryo-EM in RNA structural studies.

biophysics↗

bioRxiv2021

Pancreatic Brsk2 amplifies parasympathetic signals to promote type 2 diabetes

The parasympathetic nervous system (PNS) modulates postprandial glucose metabolism via innervating pancreas; however, its significance in the pathogenesis of type 2 diabetes (T2DM) remains unclear. Here we show that brain-specific serine/threonine-protein kinase 2 (Brsk2), accumulated in obese mouse islets, responds to PNS activation and initiates pre-absorptive insulin release. In inducible mouse models, excessive Brsk2 amplifies parasympathetic signaling to {beta} cells and increases their secretion, ensuing insulin resistance and T2DM. Conversely, Brsk2 inhibition prevents and treats HFD-induced metabolic abnormities via avoiding {beta}-cell oversecretion. Mechanistically, parasympathetic acetylcholine activates cholinergic receptor M3 (Chrm3), then Chrm3 recruits and stabilizes Brsk2, which in turn phosphorylates phospholipase A2 activating protein (Plaa). A Chrm3-Brsk2-Plaa axis stimulates {beta}-cell hypersecretion during both pre-absorptive and absorptive stages in HFD-feeding mice, thus imposing insulin resistance and {beta}-cell dysfunction. Blocking parasympathetic signaling to {beta} cells by Brsk2 protein restoration, autonomic mediation drugs, or vagotomy restricted diabetes development. Moreover, three human BRSK2 variants are associated with hyperinsulinemia, insulin resistance, and T2DM in the Chinese population. These findings reveal that Brsk2 links parasympathetic nervous system to nutrition-overload induced T2DM.

pathology↗

bioRxiv2021

Synaptic and mitochondrial plasticity associated with fear memory revealed by deep learning-based 3D reconstruction

Serial section electron microscopy (ssEM) can provide comprehensive 3D ultrastructural information of the brain with exceptional computational cost. Targeted reconstruction of subcellular structures from ssEM datasets is less computationally demanding but still highly informative. We thus developed a Region-CNN-based deep learning method to identify, segment, and reconstruct synapses and mitochondria to explore the structural plasticity of synapses and mitochondria in the auditory cortex of mice subjected to fear conditioning. Upon reconstructing over 135,000 mitochondria and 160,000 synapses, we found that fear conditioning significantly increases the number of mitochondria but decreases their size, and promotes the formation of multi-contact synapses comprising a single axonal bouton and multiple postsynaptic sites from different dendrites. Modeling indicates that such multi-contact configuration increases the information storage capacity of new synapses by over 50%. With high accuracy and speed in reconstruction, our method yields structural and functional insight into cellular plasticity associated with fear learning.

neuroscience↗

bioRxiv2021

An oligosaccharide analog exhibited antifungal activity by misleading cell wall organization via targeting PHR transglucosidases

The fungal cell wall is an ideal target for the design of antifungal drugs. In this study we used an analog of cell wall polymer, a highly deacetylated long-chain chitosan oligosaccharide (HCOS), to test its effect against pathogenic Candida strains. Results showed that HCOS was successfully incorporated into the dynamic cell wall organization process and exhibited an apparent antifungal activity against both plankton and mature fungal biofilm, by impairing the cell wall integrity. Unexpectedly, mechanistic studies suggested that HCOS exerts its activity by interfering with family members of PHR {beta}-(1,3)-glucanosyl transferases and affecting the connection and assembly of cell wall polysaccharides. Furthermore, HCOS showed great synergistic activity with different fungicides against Candida cells, especially those in biofilm. These findings indicated HCOS has a great potential as an antifungal drug or drug synergist and proposed a novel antifungal strategy with structure-specific oligosaccharides mimicking cell wall polysaccharide fragments. IMPORTANCEFungal infections have always been a puzzle in clinical medicine. Only a few antifungal drugs are available for medical usage and the widespread use of antifungal drugs increased the incidence of drug resistance. It is an urgent need for the development of novel treatment strategies against fungal infections. In this study, we proposed a novel strategy targeting to fungal cell wall against C. albicans. To our knowledge, it is the first study to show a cell wall polysaccharide fragment analog integrate into and interfere with the fungal cell wall, indicating a novel antifungal strategy using structure-specific oligosaccharides mimicking cell wall polysaccharide fragments.

microbiology↗

bioRxiv2021

Long Term Study of Motivational and Cognitive Effects of Low-intensity Focused Ultrasound Neuromodulation in the Dorsal Striatum of Nonhuman Primates

Noninvasive brain stimulation using focused ultrasound (FUS) has many potential applications as a research and clinical tool, including incorporation into neural prosthetics for cognitive rehabilitation. To develop this technology, it is necessary to evaluate the safety and efficacy of FUS neuromodulation for specific brain targets and cognitive functions. It is also important to test whether repeated long-term application of FUS to deep brain targets improves or degrades behavioral and cognitive function. To this end, we investigated the effects of FUS in the dorsal striatum of nonhuman primates (NHP) performing a visual-motor decision-making task for small or large rewards. Over the course of 2 years, we performed 129 and 147 FUS applications, respectively, in two NHP. FUS (0.5 MHz @ 0.2 - 0.8 MPa) was applied to the putamen and caudate in both hemispheres to evaluate the effects on movement accuracy, motivation, decision accuracy, and response time. Sonicating the caudate or the putamen unilaterally resulted in modest but statistically significant improvements in motivation and decision accuracy, but at the cost of slower reaction times. The effects were dose (i.e., FUS pressure) and reward dependent. There was no effect on reaching accuracy, nor was there long-term behavioral impairment or neurological trauma evident on T1-weighted, T2-weighted, or susceptibility-weighted MRI scans. Sonication also resulted in significant changes in resting state functional connectivity between the caudate and multiple cortical regions. The results indicate that applying FUS to the dorsal striatum can positively impact the motivational and cognitive aspects of decision making. The capability of FUS to improve motivation and cognition in NHPs points to its therapeutic potential in treating a wide variety of human neural diseases, and warrants further development as a novel technique for non-invasive deep brain stimulation.

neuroscience↗

bioRxiv2021

Computational saturation mutagenesis of SARS-CoV-1 spike glycoprotein: stability, binding affinity, and comparison with SARS-CoV-2

Severe Acute respiratory syndrome coronavirus (SARS-CoV-1) attaches to the host cell surface to initiate the interaction between the receptor-binding domain (RBD) of its spike glycoprotein (S) and the human Angiotensin-converting enzyme (hACE2) receptor. SARS-CoV-1 mutates frequently because of its RNA genome, which challenges the antiviral development. Here, we performed computational saturation mutagenesis of the S protein of SARS-CoV-1 to identify the residues crucial for its functions. We used the structure-based energy calculations to analyze the effects of the missense mutations on the SARS-CoV-1 S stability and the binding affinity with hACE2. The sequence and structure alignment showed similarities between the S proteins of SARS-CoV-1 and SARS-CoV-2. Interestingly, we found that target mutations of S protein amino acids generate similar effects on their stabilities between SARS-CoV-1 and SARS-CoV-2. For example, G839W of SARS-CoV-1 corresponds to G857W of SARS-CoV-2, which decrease the stability of their S glycoproteins. The viral mutation analysis of the two different SARS-CoV-1 isolates showed that mutations, T487S and L472P, weakened the S-hACE2 binding of the 2003-2004 SARS-CoV-1 isolate. In addition, the mutations of L472P and F360S destabilized the 2003-2004 viral isolate. We further predicted that many mutations on N-linked glycosylation sites would increase the stability of the S glycoprotein. Our results can be of therapeutic importance in the design of antivirals or vaccines against SARS-CoV-1 and SARS-CoV-2. Author SummarySevere acute respiratory syndrome coronavirus (SARS-CoV-1) is an RNA virus that undergoes frequent mutations, which may result in more virulent SARS-CoV-1 variants. To prevent another pandemic in the future, scientists must understand the mechanisms of viral mutations and predict if any variants could become a dominant. The infection of SARS-CoV-1 in cells is largely depending on the interactions of the viral Spike (S) and human angiotensin-converting enzyme 2 (hACE2). We applied a computational method to predict S missense mutations that will make SARS-CoV-1 more virulent. We are interested in the variants that can change SARS-CoV-1 spike protein stability and/or change the virus-receptor interactions. We mutated each residue of SARS-CoV-1 spike to all possible amino acids; we calculated the differences between the folding energy and binding energy of each variant and the wildtype and identified the target S mutations with significant effects on protein stability and protein-protein interaction. We found some viral mutations could destabilize S and weaken S-hACE2 binding of SARS-CoV-1 isolate. Our results show that the computational saturation mutagenesis is a reliable approach in the analysis and prediction of missense mutations.

bioinformatics↗

bioRxiv2021

A universal probabilistic spike count model reveals ongoing modulation of neural variability

Neural responses are variable: even under identical experimental conditions, single neuron and population responses typically differ from trial to trial and across time. Recent work has demonstrated that this variability has predictable structure, can be modulated by sensory input and behaviour, and bears critical signatures of the underlying network dynamics and computations. However, current methods for characterising neural variability are primarily geared towards sensory coding in the laboratory: they require trials with repeatable experimental stimuli and behavioural covariates. In addition, they make strong assumptions about the parametric form of variability, rely on assumption-free but data-inefficient histogram-based approaches, or are altogether ill-suited for capturing variability modulation by covariates. Here we present a universal probabilistic spike count model that eliminates these shortcomings. Our method builds on sparse Gaussian processes and can model arbitrary spike count distributions (SCDs) with flexible dependence on observed as well as latent covariates, using scalable variational inference to jointly infer the covariate-to-SCD mappings and latent trajectories in a data efficient way. Without requiring repeatable trials, it can flexibly capture covariate-dependent joint SCDs, and provide interpretable latent causes underlying the statistical dependencies between neurons. We apply the model to recordings from a canonical non-sensory neural population: head direction cells in the mouse. We find that variability in these cells defies a simple parametric relationship with mean spike count as assumed in standard models, its modulation by external covariates can be comparably strong to that of the mean firing rate, and slow low-dimensional latent factors explain away neural correlations. Our approach paves the way to understanding the mechanisms and computations underlying neural variability under naturalistic conditions, beyond the realm of sensory coding with repeatable stimuli.

neuroscience↗

bioRxiv2021

Prioritization of autoimmune disease-associated genetic variants that perturb regulatory element activity in T cells

Genome-wide association studies have uncovered hundreds of autoimmune disease-associated loci; however, the causal genetic variant(s) within each locus are mostly unknown. Here, we perform high-throughput allele-specific reporter assays to prioritize disease-associated variants for five autoimmune diseases. By examining variants that both promote allele-specific reporter expression and are located in accessible chromatin, we identify 60 putatively causal variants that enrich for statistically fine-mapped variants by up to 57.8-fold. We introduced the risk allele of a prioritized variant (rs72928038) into a human T cell line and deleted the orthologous sequence in mice, both resulting in reduced BACH2 expression. Naive CD8 T cells from mice containing the deletion had reduced expression of genes that suppress activation and maintain stemness. Our results represent an example of an effective approach for prioritizing variants and studying their physiologically relevant effects.

genetics↗

bioRxiv2021

Tmem138, a photoreceptor connecting cilium (CC) protein, is required for rhodopsin transport across the cilium and outer segment (OS) biogenesis

Photoreceptor connecting cilium (CC) is structurally analogous to the transition zone (TZ) of primary cilia and gates the molecular trafficking between the inner and the outer segment (OS). Retinal dystrophies with underlying CC defects are manifested in a broad array of syndromic conditions known as ciliopathies as well as non-syndromic retinal degenerations. Despite extensive studies, protein trafficking across the photoreceptor CC is largely unknown. Here we genetically inactivated mouse Tmem138, a gene encoding a ciliary membrane protein localized to the ciliary TZ and linked to Joubert syndrome (JBTS). Germline deletion of Tmem138 abolished OS morphogenesis followed by rapid photoreceptor degeneration. Tmem138 was found localized to the photoreceptor CC and, accordingly, the molecular compartments of the CC and axoneme of the mutant photoreceptors were altered despite ciliogenesis proceeding normally at the early stage of photoreceptor development. To gain further insights into Tmem138 function in OS biogenesis, we focused on trafficking of rhodopsin, the most abundant protein of the OS. Mislocalization of rhodopsin was readily observed as early as P5 in the mutant photoreceptors prior to growth of the OS. Ablation of Tmem138 in mature rods recapitulated the molecular changes in the germline mutants, causing well-formed outer segment discs to disintegrate accompanied by mislocalization of rhodopsin in the cell body. Furthermore, Tmem138 interacted with rhodopsin, and two additional CC compartment proteins Ahi1 and Tmem231, which were both altered in the mutant photoreceptors. Taken together, these results suggest that Tmem138 has a distinct role in gating the transport of rhodopsin and likely other OS bound proteins through formation of CC transport complex(es).

cell biology↗

bioRxiv2021

Orc6 at replication fork enables efficient mismatch repair

In eukaryotes, the Origin Recognition Complex (ORC) is required for the initiation of DNA replication. The smallest subunit of ORC, Orc6, is essential for pre-replication complex (pre-RC) assembly and cell viability in yeast and for cytokinesis in metazoans. However, unlike other ORC components, the role of human Orc6 in replication remains to be resolved. Here, we identify an unexpected role for hOrc6, which is to promote S-phase progression post pre-RC assembly and DNA damage response. Orc6 localizes at the replication fork and is an accessory factor of the mismatch repair (MMR) complex. In response to oxidative damage during S-phase, often repaired by MMR, Orc6 facilitates MMR complex assembly and activity, without which the checkpoint signaling is abrogated. Mechanistically, Orc6 directly binds to MutS and enhances the chromatin-association of MutL, thus enabling efficient mismatch repair. Based on this, we conclude that hOrc6 plays a fundamental role in genome surveillance during S-phase. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=196 SRC="FIGDIR/small/443400v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@bfdaa8org.highwire.dtl.DTLVardef@1ac791dorg.highwire.dtl.DTLVardef@436d1corg.highwire.dtl.DTLVardef@b07689_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIHuman Orc6 is dispensable for G1 licensing, but required for S-phase progression C_LIO_LIHuman Orc6 at the replication fork is an accessory factor for MMR complex C_LIO_LIDepletion of hOrc6 sensitizes cells to DNA damage and impairs ATR activation C_LIO_LIHuman Orc6 regulates MMR complex assembly and activity C_LI

molecular biology↗

bioRxiv2021

AutoGGN: A Gene Graph Network AutoML tool for Multi-Omics Research

Omics data identifies biological characteristics from genetic to phenotypic levels during the life span. Molecular interaction networks have a fundamental impact on life activities. Integrating omics data and molecular interaction networks will help researchers delve into comprehensive information underlying the data. Here, we proposed a new multimodal method called AutoGGN to aggregate multi-omics data and molecular interaction networks based on graph convolutional neural networks. We evaluated AutoGGN using two different tasks: cancer type classification and single-cell stage classification. On both tasks, AutoGGN showed better performance compared to other methods, the trend is relevant to the ability of utilizing much more information from biological data. The phenomenon indicated AutoGGN has the potential to incorporate valuable information from molecular interaction networks and multi-omics data effectively. Furthermore, in order to provide a better understanding of the mechanism of prediction results, we assessed the explanation using SHAP module and identified the key genes contributing to the prediction of classification, which will provide insights for the downstream design of biological experiments.

bioinformatics↗