Biology subjects

Guo, H.

Publications and source records attributed to Guo, H..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

Multi-Modal Large Language Model Enables Protein Function Prediction

Predicting the functions of proteins can greatly accelerate biological discovery and applications, where deep learning methods have recently shown great potential. However, these methods predominantly predict protein functions as discrete categories, which fails to capture the nuanced and complex nature of protein functions. Furthermore, existing methods require the development of separate models for each prediction task, a process that can be both resource-heavy and time-consuming. Here, we present ProteinChat, a versatile, multi-modal large language model that takes a proteins amino acid sequence as input and generates comprehensive narratives describing its function. ProteinChat is trained using over 1,500,000 (protein, prompt, answer) triplets curated from the Swiss-Prot dataset, covering diverse functions. This novel model can universally predict a wide range of protein functions, all within a single, unified framework. Furthermore, ProteinChat supports interactive dialogues with human users, allowing for iterative refinement of predictions and deeper exploration of protein functions. Our experimental results, evaluated through both human expert assessment and automated metrics, demonstrate that ProteinChat outperforms general-purpose LLMs like GPT-4, one of the flagship LLMs, by over ten-fold. In addition, ProteinChat exceeds or matches the performance of task-specific prediction models.

bioinformatics↗

bioRxiv2024

Interplay of Anchor and Latch Residues at Enzyme Active Site in Preserving Induced Fit Configurations for Efficient Catalysis: A Case Study of CARNMT1 for Histidine Methylation

Determining the origin of high catalytic efficiency of enzymes has been a central goal in biochemical research. But our understanding of the mechanisms by which enzymes achieve enormous rate enhancements is still incomplete. One of wildly accepted strategies to achieve rate enhancements by enzymes is to position catalytic residues precisely in enzyme-substrate complexes and form reactive conformations for catalysis. Such catalytic strategy through positioning may also serve as the basis for transition state stabilization. Although considerable efforts have been made to determine relationships between enzyme activities and the formation of reactive conformations of enzyme-substrate complexes, there is considerable uncertainty concerning the ability of enzymes to preserve reactive conformations during enzyme-catalyzed reactions. The failure of properly maintaining reactive conformations during reactions may prevent residues from exerting catalytic effects and lead to significant reductions of activities. Here QM/MM MD and free energy simulations are performed for CARNMT1 to determine the importance and requirements for preservation of catalytic competent reactive conformations during enzyme-catalyzed reactions. For CARNMT1, the existence of wild-type reactive conformation is directly related to the conformation of His347. Therefore, the conformation of His347 can be used to monitor preservation or collapse of the reactive conformation during catalysis. It is found that for wild-type the reactive conformation can not only be formed in the enzyme-substrate complex but also be preserved well after the reaction passes TS. For the Tyr386Ala, Tyr396Asp and Tyr398Ala mutants, the wild-type like reactive conformations can be formed in the mutant-substrate complexes but collapse in the early stage of reaction. Such pre-mature collapse of the reactive conformation in the mutants prevents the residues to fully exert catalytic effects and leads to a significant reduction of catalytic efficiency. The results suggest that the ability of enzymes to preserve reactive conformations with well-positioned catalytic residues during enzyme-catalyzed reactions can be an important factor for efficient catalysis, and this property of enzymes deserves attention.

biochemistry↗

bioRxiv2024

Smooth muscle expression of RNA editing enzyme ADAR1 controls vascular integrity and progression of atherosclerosis

Mapping the genomic architecture of complex disease has been predicated on the understanding that genetic variants influence disease risk through modifying gene expression. However, recent discoveries have revealed that a significant burden of disease heritability in common autoinflammatory disorders and coronary artery disease (CAD) is mediated through genetic variation modifying post-transcriptional modification of RNA through adenosine-to-inosine (A-to-I) RNA editing. This common RNA modification is catalyzed by ADAR enzymes, where ADAR1 edits specific immunogenic double stranded RNA (dsRNA) to prevent activation of the double strand RNA (dsRNA) sensor MDA5 (IFIH1) and stimulation of an interferon stimulated gene (ISG) response. Multiple lines of human genetic data indicate impaired RNA editing and increased dsRNA sensing by MDA5 to be an important mechanism of CAD risk. Here, we provide a crucial link between observations in human genetics and mechanistic cell biology leading to progression of CAD. Through analysis of human atherosclerotic plaque and culture of human coronary artery vascular smooth muscle cells (SMCs) we implicate the SMC to have a distinct requirement for RNA editing, and that MDA5 activation regulates SMC phenotypic modulation. Through generation of a conditional SMC specific Adar1 deletion mouse model on a pro-atherosclerosis background with additional constitutive deletion of MDA5 (Ifih1), and with incorporation of single cell RNA sequencing cellular profiling, we further show that Adar1 controls SMC phenotypic state by regulating Mda5 activation, is required to maintain vascular integrity, and controls progression of atherosclerosis and vascular calcification. Finally, we further corroborate our findings in a large human carotid endarterectomy dataset (Athero-Express) where we show that ISG activation is strongly associated with decreased plaque stability, increased SMC phenotypic modulation, and increased plaque calcification. Through this work, we describe a fundamental mechanism of CAD, where cell type and context specific RNA editing and sensing of dsRNA mediates disease progression, bridging our understanding of human genetics and disease causality. One Sentence SummarySmooth muscle expression of RNA editing enzyme ADAR1 regulates activation of double strand RNA sensor MDA5 in novel mechanism of atherosclerosis.

genomics↗

bioRxiv2024

Reversible ubiquitination of integrated domain controls paired NLR immune receptor complex homeostasis

AbstractPlant intracellular NLR immune receptors can function individually or in pairs to detect pathogen effectors and activate immune responses. NLR homeostasis has to be tightly regulated to ensure proper defense without triggering autoimmunity. However, in contrast to singleton NLRs, the mechanisms controlling the paired NLRs complex homeostasis are less understood. The paired Arabidopsis RRS1/RPS4 immune receptor complex confers disease resistance through effector recognition mediated by the integrated WRKY domain of RRS1. Here, through proximity labelling, we reveal a ubiquitination-deubiquitination cycle that controls the homeostasis of the RRS1/RPS4 complex. E3 ligase RARE directly binds and ubiquitinates RRS1s WRKY domain to promote its proteasomal degradation, thereby destabilizing RPS4 indirectly and compromising the stability and function of the RRS1/RPS4 complex. Conversely, the deubiquitinating enzymes UBP12/UBP13 deubiquitinate RRS1s WRKY domain, counteracting RAREs effects. Interestingly, the abundance of WRKY transcription factors WRKY70 and WRKY41 is also regulated by RARE and UBP12/UBP13. Phylogenetic analysis suggests this regulation likely transferred from WRKY70/WRKY41 to RRS1 upon WRKY domain integration. Our findings improve our understanding of homeostatic regulation of paired NLR complex and uncover a new paradigm whereby domain integration can co-opt preexisting post-translational modification to regulate novel protein functions.

plant biology↗

bioRxiv2024

GeneLLM: A Large cfRNA Language Model for Cancer Screening from Raw Reads

We present GeneLLM, a novel large language model that offers a transformative approach to non-invasive cancer detection and biomarker discovery by directly interpreting plasma cell-free RNA (cfRNA) sequences. Unlike traditional annotation-dependent methods, GeneLLM operates without prior knowledge, achieving significantly improved multi-cancer detection accuracy. Critically, GeneLLM identifies novel cfRNAs ( pseudo-biomarkers) originating from previously unannotated genomic regions-overlooked by existing methods-offering new therapeutic targets and insights into intercellular communication. This innovative, cost-effective approach bypasses traditional bioinformatics tools, generating novel pseudo-biomarkers that outperform existing methods even with low-depth sequencing data. Consequently, GeneLLM opens new avenues for biomarker discovery and expands our understanding of the extracellular transcriptomes role in cancer development.

bioinformatics↗

bioRxiv2024

The maternal vGluT2 and embryonic mGluR3 signaling relay system controls offspring wing dimorphism in pea aphid

Transgenerational phenotypic plasticity (TPP) refers to the phenomenon that environmental conditions experienced by one generation can influence the phenotype of subsequent generations to adapt to the environment without modification of their DNA sequences. Aphid wing dimorphism is a textbook example of TPP by which a maternal aphid perceives the environmental cues to decide the wing morph of her offspring. However, the signaling mechanism from mother to daughter remains unclear. In this study, we showed that the population density and physical contact caused high proportion of winged offspring in the pea aphid Acyrthosiphon pisum. Its vesicular glutamate transporter 2 (ApvGluT2) and metabotropic glutamate receptor 3 (ApmGluR3) were identified by tissue-specific RNA-seq as differentially expressed genes in the head and embryo respectively between solitary and more densely housed maternal aphids. Elevated expression of brain ApvGluT2 and embryonic ApmGluR3 led to increases in the winged proportion. Knockdown of either gene inhibited phosphorylation of ApFoxO in embryos. Furthermore, EMSA showed that dephosphorylated ApFoxO directly bound to the promotor of hedgehog (ApHh), a morphogen gene for wing development, to repress its transcription in stage 20 embryos, causing a lower winged proportion. Our results demonstrated that brain vGluT2 and embryonic mGluR3 coordinately relayed the maternal physical contact signals and control wing development in offspring, showcasing a novel regulatory mechanism underlying physical contact-dependent, transgenerational wing dimorphism in aphids.

zoology↗

bioRxiv2024

Synthetic organelles enable protein purification in a single operation

Protein purification is crucial for various applications in life sciences research and biotechnological industry, yet traditional chromatography methods are often complex and suffer from limited scalability and sustainability. Here we report a biological approach utilizing synthetic organelles for protein purification, termed Program Architecture of Nano-Device Actions for Purification (PandaPure). PandaPure includes a biomimetic mechanism of sorting proteins of interest into organelles through signal sequence domains during expression, and subsequently releasing said proteins via cleavage of organelle-locating signals in a single operation. In the commonly-used expression host Escherichia coli, PandaPure enables high-yield, high-purity production of target proteins, and significantly reducing environmental impact. We demonstrate its scalability and versatility with different designs, scales, and across diverse proteins, promising wide-ranging benefits in research and industrial settings.

bioengineering↗

bioRxiv2024

Super homotypic targeting by exosome surface engineering

Homotypic targeting is the inherent ability of cells for preferential interaction with cells of similar or identical types, a phenomenon commonly seen in cell adhesion, tissue formation, and immune responses. Unfortunately, its full potential remains largely untapped. Here we introduce an approach to drastically boost the homotypic targeting capabilities of cells via exosomes (nanoscale extracellular vesicles secreted by cells). By engineering exosome surfaces with lanthanides, we amplify specific cell-exosome interactions by more than 25-fold, significantly accelerating the selective capture of exosomes by cells of the same lineage. This substantial enhancement in cellular homophilicity opens up an entirely new class of applications, two of which we showcase here with unprecedented performance: using cells to detect specific exosomes and using exosomes to detect specific cells. The concept of "super homotypic targeting" offers enormous potential to transform cancer diagnostics, immunotherapy, targeted drug delivery, tissue engineering, and vaccine development.

cell biology↗

bioRxiv2024

Accurate estimation of SNP genotypes and genetic relatedness from DNA methylation data

Epigenome-wide association studies (EWAS) are susceptible to widespread confounding caused by population structure and genetic relatedness. Nevertheless, kinship estimation is challenging in EWAS without genotyping data. We propose MethylGenotyper, a method that for the first time enables accurate genotyping at thousands of SNPs directly from commercial DNA methylation microarrays. We model the intensities of methylation probes near SNPs with a mixture of three beta distributions corresponding to different genotypes and estimate parameters with an expectation-maximization algorithm. We conduct extensive simulations to demonstrate the performance of the method. When applying MethylGenotyper to Infinium EPIC array data of 4,662 Chinese, we obtain genotypes at 4,319 SNPs with a concordance rate of 98.26%, enabling the identification of 255 pairs of close relatedness. Furthermore, we show that MethylGenotyper allows for the estimation of both population structure and cryptic relatedness among 702 Australians of diverse ancestry. We have implemented MethylGenotyper in a publicly available R package to facilitate future large-scale EWAS.

bioinformatics↗

bioRxiv2024

Prioritizing disease-related rare variants by integrating gene expression data

Rare variants, comprising a vast majority of human genetic variations, are likely to have more deleterious impact on human diseases compared to common variants. Here we present carrier statistic, a statistical framework to prioritize disease-related rare variants by integrating gene expression data. By quantifying the impact of rare variants on gene expression, carrier statistic can prioritize those rare variants that have large functional consequence in the diseased patients. Through simulation studies and analyzing real multi-omics dataset, we demonstrated that carrier statistic is applicable in studies with limited sample size (a few hundreds) and achieves substantially higher sensitivity than existing rare variants association methods. Application to Alzheimers disease reveals 16 rare variants within 15 genes with extreme carrier statistics. The carrier statistic method can be applied to various rare variant types and is adaptable to other omics data modalities, offering a powerful tool for investigating the molecular mechanisms underlying complex diseases.

genetics↗

bioRxiv2024

Engineering customized viral receptors for various coronaviruses

Coronaviruses display versatile receptor usage, yet in-depth characterization of coronaviruses lacking known receptor identities has been impeded by the absence of feasible infection models1,2. Here, we developed an innovative strategy to engineer functional customized viral receptors (CVRs). The modular design relies on building receptor frameworks comprising various function modules and generating specific epitope-targeting viral binding domains. We showed the key factors for CVRs to efficiently facilitate spike cleavage, membrane fusion, pseudovirus entry, and authentic virus propagation for various coronaviruses, resembling their native receptors. Applying this strategy, we delineated the accessible receptor binding epitopes for functional SARS-CoV-2 CVR design and elucidated the mechanism of entry supported by an amino-terminus domain (NTD) targeting S2L20-CVR. Furthermore, we created CVR-expressing cells for assessing antibodies and inhibitors against 12 representative coronaviruses from six subgenera, most of which lacking known receptors. Notably, a pan-sarbecovirus CVR supported entry of various sarbecoviruses, as well as propagation of a replicable HKU3 pseudovirus and the authentic strain RsHuB2019A3. Through combining an HKU5-specific CVR with reverse genetics, we successfully rescued and cultured wild-type and fluorescence protein-incorporated HKU5, a receptor-unidentified merbecovirus. Our study demonstrated the great potential of CVR strategy in establishing native receptor-independent infection models, paving the way for studying various viruses that are challenging to culture due to the lack of susceptible cells. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=162 SRC="FIGDIR/small/583237v1_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@7cb9ccorg.highwire.dtl.DTLVardef@8a2855org.highwire.dtl.DTLVardef@5e14f0org.highwire.dtl.DTLVardef@b0b993_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphic abstractC_FLOATNO C_FIG

microbiology↗

bioRxiv2024

Near telomere-to-telomere genome assemblies of two Chlorella species unveil the composition and evolution of centromeres in green algae

BackgroundCentromeres play a crucial and conserved role in cell division, although their composition and evolutionary history in green algae, the evolutionary ancestors of land plants, remains largely unknown. ResultsWe constructed near telomere-to-telomere (T2T) assemblies for two Trebouxiophyceae species, Chlorella sorokiniana NS4-2 and Chlorella pyrenoidosa DBH, with chromosome numbers of 12 and 13, and genome sizes of 58.11 Mb and 53.41 Mb, respectively. We identified and validated their centromere sequences using CENH3 ChIP-seq and found that, similar to humans and higher plants, the centromeric CENH3 signals of green algae display a pattern of hypomethylation. Interestingly, the centromeres of both species largely comprised transposable elements, although they differed significantly in their composition. Species within the Chlorella genus display a more diverse centromere composition, with major constituents including members of the LTR/Copia, LINE/L1, and LINE/RTEX families. This is in contrast to green algae including Chlamydomonas reinhardtii, Coccomyxa subellipsoidea, and Chromochloris zofingiensis, in which centromere composition instead has a pronounced single-element composition. Moreover, we observed significant differences in the composition and structure of centromeres among chromosomes with strong collinearity within the Chlorella genus, suggesting that centromeric sequence evolves more rapidly than sequence in non-centromeric regions. ConclusionsThis study not only provides high-quality genome data for comparative genomics of green algae but gives insight into the composition and evolutionary history of centromeres in early plants, laying an important foundation for further research on their evolution.

genomics↗

bioRxiv2024

Liver cancer initiation is dependent on metabolic zonation but decoupled from premalignant clonal expansion

The origin of cancer is poorly understood because cells that obtain truncal mutations are rarely fate mapped in their native environments. A defining feature of the liver is zonation, or the compartmentalization of metabolic functions in hepatocytes located in distinct regions of the lobule 1. However, it is unknown if cancers develop in some zones but not others, and if there are metabolic determinants of cancer risk that track with cellular position. To study cancer initiation, we examined the effect of activating mutations in Ctnnb1 and loss of function mutations in Arid2, two of the most commonly co-mutated genes in hepatocellular carcinoma (HCC) 2. We exploited glutamine synthetase (GS) as a faithful fate mapping marker of Ctnnb1 mutant hepatocytes. By introducing mutations in distinct zones in a mosaic fashion, we showed that position and metabolic context regulate clone expansion. Mutant clones were maintained in zone 1 but largely outcompeted in zone 3. Paradoxically, clonal maintenance was anti-correlated with cancer initiation, as zone 3 mutant livers showed increased tumorigenesis. To define mechanisms, we individually deleted eleven zone specific genes in HCC mouse models, revealing that Gstm2 and Gstm3 were required for efficient HCC initiation in zone 3. These data indicate that liver cancer initiation is dependent on zonation but independent of clonal expansion.

cancer biology↗

bioRxiv2024

Target-aware Molecule Generation for Drug Design Using a Chemical Language Model

Generative drug design facilitates the creation of compounds effective against pathogenic target proteins. This opens up the potential to discover novel compounds within the vast chemical space and fosters the development of innovative therapeutic strategies. However, the practicality of generated molecules is often limited, as many designs focus on a narrow set of drug-related properties, failing to improve the success rate of subsequent drug discovery process. To overcome these challenges, we develop TamGen, a method that employs a GPT-like chemical language model and enables target-aware molecule generation and compound refinement. We demonstrate that the compounds generated by TamGen have improved molecular quality and viability. Additionally, we have integrated TamGen into a drug discovery pipeline and identified 7 compounds showing compelling inhibitory activity against the Tuberculosis ClpP protease, with the most effective compound exhibiting a half maximal inhibitory concentration (IC50) of 1.9 M. Our findings underscore the practical potential and real-world applicability of generative drug design approaches, paving the way for future advancements in the field.

biochemistry↗

bioRxiv2023

ROS-induced translational regulation--through spatiotemporal differences in codon recognition--is a key driver of brown adipogenesis

The role of translational regulation in brown adipogenesis is relatively unknown. Localized translation of mRNAs encoding mitochondrial components enables swift mitochondrial responses, but whether this occurs during brown adipogenesis, which involves massive mitochondrial biogenesis, has not been explored. Here, we used ribosome profiling and RNA-Seq, coupled with cellular fractionation, to obtain spatiotemporal insights into translational regulation. During brown adipogenesis, a translation bias towards G/C-ending codons is triggered first in the mitochondrial vicinity by reactive oxygen species (ROS), which later spreads to the rest of the cell. This translation bias is induced through ROS modulating the activity of the tRNA modification enzyme, ELP3. Intriguingly, functionally relevant mRNAs, including those encoding ROS scavengers, benefit from this bias; in so doing, ROS-induced translation bias both fuels differentiation and concurrently minimizes oxidative damage. These ROS-induced changes could enable sustained mitochondrial biogenesis during brown adipogenesis, and explain in part, the molecular basis for ROS hormesis.

molecular biology↗

bioRxiv2023

Linking root-associated fungal and bacterial functions to root economics

Tree roots form symbioses with soil microbes to acquire nutrients, but the relationships between root nutrient acquisition strategies and microbial community composition remain poorly understood. Here, we measured root traits and root-associated fungal and bacterial guilds in 336 trees of 52 species from a subtropical forest. We found a fungal gradient from ectomycorrhizal to saprotrophic dominance, which corresponded with a shift from organic to mineral nutrient economics. This fungal gradient was aligned with the increase of root nitrogen concentration, suggesting a linkage from simple root trait to fungal-mediated carbon-nutrient cycling. We also found that the functional composition of fungal and bacterial communities was closely correlated with host root-zone pH, which often varied among coexisting trees. Root-zone pH was independent of the common root traits, underpinning a potential new gradient in the root trait space. Our findings integrate microbial functions into the root economics framework, thereby advancing the understanding of diversity of nutrient acquisition strategies across forest trees.

ecology↗

bioRxiv2023

PANAMA enabled high sensitivity dual nanoflow LC/MS metabolomics and proteomics analysis

High sensitivity nanoflow liquid chromatography (nLC) is seldom employed in untargeted metabolomics because current sample preparation techniques are inefficient to prevent nanocapillary column performance degradation. Here, we describe an nLC-based tandem mass spectrometry workflow that enables seamless joint analysis and integration of metabolomics (including lipidomics) and proteomics from the same samples without instrument duplication. This workflow is based on robust solid phase micro-extraction step for routine sample clean-up and bioactive molecule enrichment. Our method, termed PANAMA, improves compound resolution and detection sensitivity without compromising depth of coverage as compared with existing widely used analytical procedures. Notably, PANAMA can be applied to a broad array of specimens including biofluids, cell line and tissue samples. It generates high quality, information rich metabolite-protein datasets while bypassing the need for specialized instrumentation. MotivationThe ability to routinely, sensitively and reproducibly analyze both cellular proteins and metabolite mixtures from the same biospecimens can enhance the discovery of biomolecules associated with basic biochemical processes and pathobiological states. Yet existing mass spectrometry-based profiling methods rely on specialized protocols and duplicated instrumentation platforms, resulting in increased time, sample consumption and costs. We sought to generate an effective platform for both metabolomic and proteomic studies on the same samples by enabling nanoflow liquid chromatography for small molecules. The resulting approach was extensively optimized and benchmarked to provide in depth molecular coverage, along with improved chromatographic separations, sensitivity and reliability as compared to existing methods. The cost benefit ratio of PANAMA is substantial because the platform bypasses the need for specialized instrumentation stemming from incompatible procedures.

systems biology↗

bioRxiv2023

Distinct eLPB ChAT projections for methamphetamine anxiety and relapse

Choline acetyltransferase-positive neurons in the external lateral parabrachial nucleus (eLPBChAT) send projections to PKC{delta}-positive (PKC{delta}+) neurons in lateral portion of central nucleus of amygdala (lCeAPKC{delta}) and oval portion of bed nucleus of the stria terminalis (ovBNSTPKC{delta}), forming eLPBChAT-lCeAPKC{delta} and eLPBChAT-ovBNSTPKC{delta} pathways. At least in part, the eLPBChAT neurons positively innervate lCeAPKC{delta} and ovBNSTPKC{delta} through regulating synaptic elements of presynaptic acetylcholine (Ach) release and postsynaptic nicotinic acetylcholine receptors (nAChRs). Methamphetamine (METH) withdrawal anxiety and METH-primed reinstatement of conditioned place preference (CPP) recruit eLPBChAT-lCeAPKC{delta} pathway and eLPBChAT-ovBNSTPKC{delta} pathway in male METH-exposed mice, respectively.

neuroscience↗