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Liu, Y.

Publications and source records attributed to Liu, Y..

At least 1,009 records · Page 56Linked to original sources
bioRxiv2024

Machine learning engineered PoLixNano nanoparticles overcome delivery barriers for nebulized mRNA therapeutics

There continues to be a dearth of competent inhalable mRNA delivery although it holds great potential for addressing a wide variety of refractory diseases. The huge advances seen with parenteral-administered lipid nanoparticle (LNP) have not been translated into nebulized mRNA delivery due to the aggressive nebulization process and insurmountable barriers inherent to respiratory mucosa. Here, we show amphiphilic block copolymers revealed by machine learning (ML) can spontaneously form stabilized nanoparticles (PoLixNano) with the lipids components of LNP and simultaneously impart the PoLixNano with "shield" (shear force-resistant) and "spear" (pulmonary barriers-penetrating abilities) capabilities. We present a ML approach that leverages physicochemical properties and inhaled mRNA transfection profiles of a chemically diverse library of polymeric components to validate the integration of "shield" and "spear" properties as highly predictive indicators of transfection efficiency. This quantitative structure-mRNA transfection prediction (QSMTP) model identifies top-performing amphiphilic-copolymers from more than 10000 candidates and suggests their mucus-penetrating ability outweights the shear force-resistant property in contributing to efficient mRNA transfection. The optimized PoLixNano substantially outperforms the LNP counterpart and mediates up to 1114-times higher levels of mRNA transfection in animal models with negligible toxicities. The PoLixNano promotes overwhelming SARS-CoV-2 antigen-specific sIgA antibody secretion and expansion of TRM cells which collectively confers 100% protection in mice against lethal SARS-CoV-2 challenges and blocks the transmission of Omicron variant between hamsters. PoLixNano also displays versatile therapeutic potential in lung carcinoma and cystic fibrosis models. Our study provides new insights for designing delivery platforms of aerosol-inhaled mRNA therapeutics with clinical translation potential.

synthetic biology↗
bioRxiv2024

Positive impact of Type-A and -C response regulator genes on growth and panicle architecture in rice

Cytokinin signal transduction occurs through a "two-component system." Type-A and -C response regulators (RRs) are groups of proteins of similar structures constituting significant components of cytokinin signal transduction. In rice, 13 (Type-A) and two (Type-C) RRs have been identified to date; however, their functions remain partially known. In this study, we examined the expression patterns of Type-A and Type-C RRs in rice using RNA-Seq and confirmed their functions by constructing mutants of the 15 genes with CRISPR/Cas9. Almost all Type-A RRs played positive roles in the development of secondary branches and secondary spikelets, particularly RR2 and RR4. Notably, rr1 rr2 and rr8 rr12 rr13 higher-order mutants displayed small panicle sizes and decreased plant height. Additionally, both Type-C RRs played positive roles in regulating heading date. RNA-seq revealed several genes with significantly altered expression in the rr2 and rr4 mutants, with almost half of the differentially expressed genes (DEGs) overlapping between the two mutants. Many of the DEGs were associated with the cytokinin and abscisic acid pathways. Our findings provide new insights into the functions of Type-A and -C RRs in rice growth and may serve as a foundation for future studies focusing on cytokinin signaling.

plant biology↗
bioRxiv2024

The microbiome diversifies N-acyl lipid pools - including short-chain fatty acid-derived compounds

N-acyl lipids are important mediators of several biological processes including immune function and stress response. To enhance the detection of N-acyl lipids with untargeted mass spectrometry-based metabolomics, we created a reference spectral library retrieving N-acyl lipid patterns from 2,700 public datasets, identifying 851 N-acyl lipids that were detected 356,542 times. 777 are not documented in lipid structural databases, with 18% of these derived from short-chain fatty acids and found in the digestive tract and other organs. Their levels varied with diet, microbial colonization, and in people living with diabetes. We used the library to link microbial N-acyl lipids, including histamine and polyamine conjugates, to HIV status and cognitive impairment. This resource will enhance the annotation of these compounds in future studies to further the understanding of their roles in health and disease and highlight the value of large-scale untargeted metabolomics data for metabolite discovery.

bioinformatics↗
bioRxiv2024

IKAROS facilitates antigen escape in the face of CD19- and CD22-targeted therapies for B-cell acute lymphoblastic leukemia

Relapse due to antigen escape is a major cause of treatment failure for patients with B-cell malignancies following targeted immunotherapies, including CD19- and CD22-directed chimeric antigen receptor T (CAR T) cells. To identify tumor intrinsic factors associated with antigen loss, we performed single-cell analyses on 61 primary patient samples or patient-derived xenografts from patients with B-cell acute lymphoblastic leukemia (B-ALL) treated with CAR T cells. We identified that low levels of the transcription factor IKAROS in pro-B-like B-ALL cells before CAR T treatment are associated with antigen escape. We demonstrate that IKAROSlow B-ALL cells lose features of B cell identity and resemble progenitor cells based on their epigenetic and transcriptional state, resulting in the downregulation of B-cell immunotherapy antigens, including surface expression of CD19 and CD22. We find that modulation of CD19 and CD22 protein expression is IKAROS dose-dependent and reversible. Further, we demonstrate that IKAROSlow cells are resistant to CD19- and CD22-targeted therapies. Together, we describe a novel role for IKAROS in the regulation of B-cell immunotherapy targets and the risk of antigen escape relapse, identifying it as a potential prognostic target. HighlightsO_LIIKAROSlow pro-B-like B-ALL cells are associated with CD19neg relapse C_LIO_LIIKAROSlow B-ALL cells resemble progenitor cells and have lower B-cell commitment C_LIO_LIIKAROS modulates CD19 and CD22 surface expression in a dose-dependent and reversible manner C_LIO_LIIKAROSlow B-ALL cells are more resistant to CD19- and CD22-targeted therapies C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/621347v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@109f75eorg.highwire.dtl.DTLVardef@14f41fborg.highwire.dtl.DTLVardef@74e428org.highwire.dtl.DTLVardef@2f275c_HPS_FORMAT_FIGEXP M_FIG C_FIG Before immunotherapy, IKAROSlow pro-B-like B-ALL cells possess chromatin and gene expression states poised for loss of B-cell identity while maintaining expression of CD19 and CD22. Under immune pressure, IKAROShigh cells maintain their antigen expression, making them more susceptible to T cell-mediated killing. Conversely, IKAROSlow cells are more likely to downregulate their antigen expression, giving them a relative advantage to escape immunotherapies, resulting in antigen escape relapse.

cancer biology↗
bioRxiv2024

Self-Authenticating Genomic Materials with Advanced Genome Signatures

The authenticity and integrity of synthetic genomic materials containing valuable intellectual property are essential for advancing scientific knowledge and enhancing biosafety. Existing DNA tags and watermarks, however, have limited efficacy due to low mutation tolerance and inadequate digital encoding capacity. Here, we present "Genome Signature", a biochemically stable and tamper-resistant DNA labeling system that enables the creation of self-authenticating genomes. Central to this system is a novel Golomb-ruler-derived Genome-Comb, which efficiently maps extensive nucleotide sequences onto limited codons within endogenous genes, significantly improving error correction and data encoding across millions of nucleotides. Our method successfully recorded a 4.5 million-nucleotide genome in living E. coli. The Genome Signature autonomously identifies and corrects mutations and effectively encodes data within codon orders, ensuring genome integrity and authenticity. Furthermore, it allows precise tracking of sequences across different cells, potentially revolutionizing the development of reliable genomic materials in synthetic biology.

synthetic biology↗
bioRxiv2024

The Whole Proteome, Phosphoproteome, and Glycoproteome Landscape of Pan-Cancer Cell Lines Profiled by Mass Spectrometry and Reverse Phase Protein Array

Mammalian cancer cell lines are essential model systems in biomedical research. We conducted multi-level proteomics analyses on 54 widely used cancer cell lines derived from various tissue-of-origins using two prominent proteomics technologies: mass spectrometry (MS) and reverse-phase protein array (RPPA). Our analysis identified 10,088 proteins, 33,609 phosphorylation sites across 7,289 phosphoproteins, and 56,350 site-specific glycans on 16,296 glycosylation sites from 5,966 glycoproteins, along with 305 drug-relevant protein and phosphoprotein targets. Our results reveal both consistent and distinct patterns in protein expression and modification between MS and RPPA, underscoring their complementary strengths as discovery tools. Additionally, we identified protein features that distinguish tissue origins across different cell line lineages. This dataset supports model system selection for drug target-related studies in vitro and provides valuable insights into key signaling pathways. Overall, this comprehensive resource enables new opportunities for exploration in cancer biology and offers significant value to research communities focused on biomarker profiling, drug target discovery, and understanding mechanisms across diverse cancer types.

cancer biology↗
bioRxiv2024

NuclampFISH enables cell sorting based on nuclear RNA expression for chromatin analysis

Transcriptional bursts refer to periods when RNA polymerase interacts with a DNA locus, leading to active gene transcription. This bursting activity can vary across individual cells, and analyzing the differences in transcription sites can help identify key drivers of gene expression for a specific target. Scaffolding methods based on fluorescence in situ hybridization (FISH) have been widely used to amplify the fluorescent signal of mRNAs and sort cells based on mRNA expression levels. However, these methods are inefficient at targeting nuclear RNA, including transcription sites, due to the probes limited accessibility through cellular compartment membranes and crosslinked proteins. Additionally, the required formaldehyde fixation interferes with downstream analysis of chromatin and protein-binding interactions. To address these challenges, a platform that integrates amplified FISH with reversible crosslinkers and allows access to the nucleus is needed. In response, we developed nuclear clampFISH (nuclampFISH). This method amplifies the fluorescent signal of mRNAs using a reversible crosslinker, enabling the sorting of cells based on nuclear RNA expression and compatible with downstream biochemical analysis. This assay demonstrates that transcriptionally active cells have more accessible chromatin for a respective gene. Notably, the tools developed are highly accessible and do not require specialized computation or equipment.

genomics↗
bioRxiv2024

A Comprehensive and Robust Multiplex-DIA Workflow Profiles Protein Turnover Regulations Associated with Cisplatin Resistance

Measuring protein turnover is essential for understanding cellular biological processes and advancing drug discovery. The multiplex DIA mass spectrometry (DIA-MS) approach, combined with dynamic SILAC labeling (pulse-SILAC, or pSILAC), has proven to be a reliable method for analyzing protein turnover and degradation kinetics. Previous multiplex DIA-MS workflows have employed various strategies, including leveraging the highest isotopic labeling channels of peptides to enhance the detection of isotopic MS signal pairs or clusters. In this study, we introduce an improved and robust workflow that integrates a novel machine learning strategy and channel-specific statistical filtering, enabling dynamic adaptation to systematic or temporal variations in channel ratios. This allows comprehensive profiling of protein turnover throughout the pSILAC experiment without relying solely on the highest channel signals. Additionally, we developed KdeggeR, a data processing and analysis package optimized for pSILAC-DIA experiments, which estimates and visualizes peptide and protein degradation rates and dynamic profiles. Our integrative workflow was benchmarked on both 2-channel and 3-channel standard DIA datasets and workflow to an aneuploid cancer cell model before and after cisplatin resistance development demonstrated a strong negative correlation between transcript regulation and protein degradation for major protein complex subunits. We also identified specific protein turnover signatures associated with cisplatin resistance.

systems biology↗
bioRxiv2024

Cytokine-induced reprogramming of human macrophages toward Alzheimer's disease-relevant molecular and cellular phenotypes in vitro

Myeloid cells including brain-resident (microglia) and peripheral macrophages play a crucial role in various pathological conditions, including neurodegenerative disorders like Alzheimers disease (AD). They respond to disruption of tissue homeostasis associated with disease conditions by acquiring various transcriptional and functional states. Experimental investigation of these states is hampered by the lack of tools that enable accessible and robust reprogramming of human macrophages toward Alzheimers disease-relevant molecular and cellular phenotypes in vitro. In this study, we investigated the ability of a cytokine mix, including interleukin-4 (IL4), colony stimulating factor 1 (CSF1/MCSF), interleukin 34 (IL34) and transforming growth factor beta (TGF{beta}), to induce reprogramming of cultured human THP-1 macrophages. Our results indicate this treatment led to significant transcriptomic changes, driving THP-1 macrophages towards a transcriptional state reminiscent of disease-associated microglia (DAM) and lipid-associated macrophages (LAM) collectively referred to as DLAM. Transcriptome profiling revealed gene expression changes related to oxidative phosphorylation, lysosome function, and lipid metabolism. Single-cell RNA sequencing revealed an increased proportion of DLAM clusters in cytokine mix-treated THP-1 macrophages. Functional assays demonstrated alterations in cell motility, phagocytosis, lysosomal activity, and metabolic and energetic profiles. Our findings provide insights into the cytokine-mediated reprogramming of macrophages towards disease-relevant states, highlighting their role in neurodegenerative diseases and potential for therapeutic development.

immunology↗
bioRxiv2024

Differential gene expression analysis identifies a group of defensin like peptides from Solanum chacoense ovules with in vitro pollen tube attraction activity

Solanum chacoense is a wild potato species with superior genetic resistance to diseases and pests that has been extensively used for introgression into cultivated potato. One determinant of crossing success between wild and cultivated potato species is the effective ploidy of the parents. However, little is known about whether other, prezygotic level, breeding barriers exist. We hypothesize ovular pollen tube guidance may serve as such a checkpoint. Tests for species-specific pollen tube guidance using semi-in vivo assays suggested a positive correlation between species-specificity and taxonomic distance. RNA-seq of ovules hand dissected from wild type plants at anthesis and two days before anthesis, as well as from a frk1 mutant lacking an embryo sac identified a list of 284 embryo sac-dependent genes highly expressed in mature ovules and poorly expressed in all other samples. Among these are 17 Solanum chacoense cysteine-rich proteins (ScCRPs), considered to be good candidates since CRPs are ovular pollen tube attractants in other species. A group of three cloned and purified ScCRP2 sequences belonging to the DEFL protein family showed moderate levels of in vitro pollen tube attraction activity in functional assays. We conclude that ScCRP2s are good candidates for ovular pollen tube guidance in S. chacoense. HighlightsThis work introduces key characteristics of pollen tube guidance in Solanum chacoense, identifies candidate attractants through transcriptome subtraction and reports in vitro pollen tube attraction activity for three defensin-like peptides.

plant biology↗
bioRxiv2024

Irx3/5 define the cochlear sensory domain and regulate vestibular and cochlear sensory patterning in the mammalian inner ear

The mammalian inner ear houses the vestibular and cochlear sensory organs dedicated to sensing balance and sound, respectively. These distinct sensory organs arise from a common prosensory region, but the mechanisms underlying their divergence remain elusive. Here, we showed that two evolutionarily conserved homeobox genes, Irx3 and Irx5, are required for the patterning and segregation of the saccular and cochlear sensory domains, as well as for the formation of auditory sensory cells. Irx3/5 were highly expressed in the cochlea, their deletion resulted in a significantly shortened cochlea with a loss of the ductus reuniens that bridged the vestibule and cochlea. Remarkably, ectopic vestibular hair cells replaced the cochlear non-sensory structure, the Greater Epithelial Ridge. Moreover, most auditory sensory cells in the cochlea were transformed into hair cells of vestibular identity, with only a residual organ of Corti remaining in the mid-apical region of Irx3/5 double knockout mice. Conditional temporal knockouts further revealed that Irx3/5 are essential for controlling cochlear sensory domain formation before embryonic day 14. Our findings demonstrate that Irx3/5 regulate the patterning of vestibular and cochlear sensory cells, providing insights into the separation of vestibular and cochlear sensory organs during mammalian inner ear development.

developmental biology↗
bioRxiv2024

Chromosomal instability promotes cell migration and invasion via EFEMP1 in extracellular vesicles

Triple-negative breast cancer (TNBC) is characterised by high rates of chromosomal instability (CIN) and a tumour microenvironment (TME) modulated by extracellular vesicles (EVs). To assess how CIN might affect the TME in TNBC, we studied the EV landscape of TNBC cell lines with induced CIN. We find that CIN leads to increased secretion of EVs and that these EVs promote cell migration of recipient cells. EVs are enriched for extracellular matrix (ECM) proteins, including EFEMP1. Indeed, modulation of EFEMP1 levels in EVs significantly alters migration behaviour of EV-treated cells. We show that EFEMP1 expression is regulated by STAT1, and that EVs from STAT1-deficient cells no longer promote migration, which can be rescued by overexpression of EFEMP1 in STAT1-null cells. Xenografting TNBC cells with EFEMP1 enriched cells promotes migration in zebrafish embryos, suggesting that EFEMP1 expression is a factor that promotes metastasis. Together our results uncover a novel role for CIN in shaping the TME of TNBC and identify EFEMP1 as a potential therapeutic target to prevent cell migration within the TME.

cancer biology↗
bioRxiv2024

Clinical characteristics, drug-resistance genes and virulence analysis of carbapenem-resistant Klebsiella pneumoniae

OBJECTIVEThe aim was to investigate the clinical infection characteristics, risk factors and convergence of carbapenem-resistant and hypervirulent Klebsiella pneumoniae(hv-CRKP) in our hospital, in order to provide scientific basis for the rational use of antibiotics in the clinic. METHODSCRKP strains were isolated from clinical specimens of 44 patients in central intensive care unit (CICU), neurosurgery intensive care unit (NICU) and emergency intensive care unit (EICU) of our hospital in 41 months. The clinical manifestations of the patients were analyzed, and the hypermucoviscous phenotype was defined by string test. The drug resistance gene, virulence gene and capsular specific serotype of the isolated strains were detected by polymerase chain reaction (PCR) technology, and the gene of CRKP producing KPC enzyme was sequence. RESULTSThe incidence of sepsis in 44 patients with CRKP infection was 25.0%, and the overall treatment failure rate was 38.6%. All the 44 strains of CRKP produced KPC enzyme, and all of them were blaKPC-2 (100%);14 strains (31.8%) were positive in string test; 23 strains (52.3%) were found to have virulence related genes, including 10 strains (22.7%) of rmpA, 16 strains (36.4%) of iucA and 19 strains (43.2%) of peg-344. 5 strains (11.4%) were capsule-specific serotypes and 13 strains (29.5%) were identified as hv-CRKP. CONCLUSIONThe mechanism of CRKP resistance in our hospital is blaKPC-2, the detection rates of virulence gene, string test positive and hypervirulent capsular specific serotype are all relatively high in CRKP, there are not a few Klebsiella pneumoniae with carbapenem-resistant and hypervirulent.

microbiology↗
bioRxiv2024

Human-mouse proteomics reveals the shared pathways in Alzheimer's disease and delayed protein turnover in the amyloidome

Murine models of Alzheimers disease (AD) are crucial for elucidating disease mechanisms but have limitations in fully representing AD molecular complexities. We comprehensively profiled age-dependent brain proteome and phosphoproteome (n > 10,000 for both) across multiple mouse models of amyloidosis. We identified shared pathways by integrating with human metadata, and prioritized novel components by multi-omics analysis. Collectively, two commonly used models (5xFAD and APP-KI) replicate 30% of the human protein alterations; additional genetic incorporation of tau and splicing pathologies increases this similarity to 42%. We dissected the proteome-transcriptome inconsistency in AD and 5xFAD mouse brains, revealing that inconsistent proteins are enriched within amyloid plaque microenvironment (amyloidome). Determining the 5xFAD proteome turnover demonstrates that amyloid formation delays the degradation of amyloidome components, including A{beta}-binding proteins and autophagy/lysosomal proteins. Our proteomic strategy defines shared AD pathways, identify potential new targets, and underscores that protein turnover contributes to proteome-transcriptome discrepancies during AD progression.

biochemistry↗
bioRxiv2024

Global test of the enemy release hypothesis reveals similar patterns of herbivory across native and non-native plants

The Enemy Release Hypothesis (ERH) proposes that non-native plants escape their co-evolved herbivores and benefit from reduced herbivory in their introduced ranges. Numerous studies have tested this hypothesis, with conflicting results, but previous studies focus on average levels of herbivory and overlook the substantial within-population variability in herbivory, which may provide unique insights into the ERH. We tested differences in mean herbivory and added a novel approach to the ERH by comparing within-population variability in herbivory between native and non-native plant populations. We include several covariates that might mask an effect of enemy release, including latitude, regional plant richness, plant growth form and plant cover. We use leaf herbivory data collected by the Herbivory Variability Network for 788 plant populations (616 native range populations and 172 introduced range populations) of 503 different native and non-native species distributed worldwide. We found no overall differences in mean herbivory or herbivory variability between native and non-native plant populations. Taken together, our results indicate no evidence of enemy release for non-native plants, suggesting that enemy release is not a generalized mechanism favoring the success of non-native species. OPEN RESEARCH STATEMENTData published and available for peer review at https://doi.org/10.5061/dryad.44j0zpckm

ecology↗
bioRxiv2024

Nuclear effects play an important role in determining codon usage-dependent human gene expression

Codon usage biases play a significant role in determining gene expression levels. Codon usage was thought to primarily influence translation-dependent processes. Here we show that codon usage optimality correlates genome-wide with nuclear mRNA and transcription levels in human cells, suggesting a nuclear role for codon usage. A genome-wide non-biased CRISPR-Cas9 screen was performed to identify factors involved in codon usage effects on gene expression. The identified factors include the CCR4-NOT complex subunit CNOT4 and many nuclear factors, including nuclear RNA exosome, PAXT complex components, and transcription factors. The CCR4-NOT complex has been shown to affect codon usage-dependent co-translational mRNA decay in yeast. Surprisingly, human CNOT4 was found to be highly enriched in nucleus and its influence on codon usage-dependent gene expression is largely caused by its impact on nuclear RNA levels due to transcriptional effect. On the other hand, nuclear exosome and PAXT complex, regulates nuclear mRNA stability through the RNA quality control pathway, leading to preferential cytoplasmic accumulation of mRNAs with optimal codon usage. Overall, our findings suggest that codon usage biases are due to selection on both translation-dependent and independent processes; different nuclear mechanisms play a key role in determining nucleotide composition-dependent gene expression levels in human cells.

genomics↗
bioRxiv2024

LP-Micro Offers Interpretable Disease Outcome Prediction by Leveraging Microbial Biomarkers and Their Time-Varying Effects

Information generated from longitudinally-sampled microbial data has the potential to illuminate important aspects of development and progression for many human conditions and diseases. Identifying microbial biomarkers and their time-varying effects can not only advance our understanding of pathogenetic mechanisms, but also facilitate early diagnosis and guide optimal timing of interventions. However, longitudinal predictive modeling of highly noisy and dynamic microbial data (e.g., metagenomics) poses analytical challenges. To overcome these challenges, we introduce a robust and interpretable machine-learning-based longitudinal microbiome analysis framework, LP-Micro, that encompasses: (i) longitudinal microbial feature screening via a polynomial group lasso, (ii) disease outcome prediction implemented via machine learning methods (e.g., XGBoost, deep neural networks), and (iii) interpretable association testing between time points, microbial features, and disease outcomes via permutation feature importance. We demonstrate in simulations that LP-Micro can not only identify incident disease-related microbiome taxa but also offers improved prediction accuracy compared to existing approaches. Applications of LP-Micro in two longitudinal microbiome studies with clinical outcomes of childhood dental disease and weight loss following bariatric surgery yield consistently high prediction accuracy. The identified critical early predictive time points are informative and aligned with clinical expectations.

bioinformatics↗