Biology subjects

Chen, X.

Publications and source records attributed to Chen, X..

At least 577 records · Page 32Linked to original sources

bioRxiv2024

Revealing a Correlation between Structure and in vitro Activity of mRNA Lipid Nanoparticles

mRNA-loaded lipid nanoparticles (mRNA-LNPs) represent a promising platform for disease prevention, cancer immunotherapy, and gene editing, etc. Despite the success of mRNA-LNPs based vaccines, the relationship between their structure and efficacy remains elusive. Here, we generated a series of mRNA-LNPs with varied structural properties and in vitro cellular activities by altering their processing and storage conditions to investigate the structure-activity relationship (SAR). Our findings revealed a moderate anticorrelation between particle size distribution and in vitro activity. Importantly, the intensity of a characteristic peak, as detected by small angle X-ray scattering (SAXS), demonstrated a strong correlation with in vitro activity while the encapsulation efficiency is high. Additionally, the peak width and area were moderately correlated and anticorrelated with activity, respectively. These observations suggest that a more ordered internal structure is likely associated with enhanced in vitro activity of mRNA-LNPs. Further analysis using 31P nuclear magnetic resonance indicated that lyophilization might induce phase separation of mRNA and lipids within the LNPs, leading to a diminished SAXS peak and reduced in vitro activity. Overall, our study establishes an SAR for mRNA-LNPs, highlighting that a more ordered internal structure correlates with higher efficacy, which could be instrumental in high-throughput screening of LNP libraries.

biophysics↗

bioRxiv2024

Estrus-Tracking Cortical Neurons Integrate Social cues and Reproductive states to Adaptively Control Sexually Dimorphic Sociosexual Behaviors

Female sociosexual behaviors, essential for survival and reproduction, are adaptively modulated by ovarian hormones. However, the neural mechanisms integrating internal hormonal states with external social cues to guide these behaviors remain poorly understood. Here we identified primary estrous-sensitive Cacna1h-expressing medial prefrontal (mPFCCacna1h+) neurons that orchestrate adaptive sociosexual behaviors. Bidirectional manipulation of mPFCCacna1h+ neurons drives opposite-sex-directed behavioral shifts between estrus and diestrus females. In males, these neurons serve opposite functions compared to estrus females, mediating sexually dimorphic effects via anterior hypothalamic outputs. Miniscope imaging reveals mixed-representation of self-estrous states and social target sex in distinct mPFCCacna1h+ subpopulations, with biased-encoding of opposite-sex social cues in estrus females and males. Mechanistically, ovarian hormone-driven upregulation of Cacna1h-encoded T-type calcium channels underlies estrus-specific activity changes and sexual-dimorphic function of mPFCCacna1h+ neurons. These findings uncover a prefrontal circuit that integrates internal hormonal states and target-sex information to exert sexually bivalent top-down control over adaptive social behaviors.

neuroscience↗

bioRxiv2024

Predicting the bacterial host range of plasmid genomes using the language model-based one-class SVM algorithm

The prediction of the plasmid host range is crucial for investigating the dissemination of plasmids and the transfer of resistance and virulence genes mediated by plasmids. Several machine learning-based tools have been developed to predict plasmid host ranges. These tools have been trained and tested based on the bacterial host records of plasmids in related databases. Typically, a plasmid genome in databases such as NCBI is annotated with only one or a few bacterial hosts, which does not encompass all possible hosts. Consequently, existing methods may significantly underestimate the host ranges of mobilizable plasmids. In this work, we propose a novel method named HRPredict, which employs a word vector model to digitally represent the encoded proteins on plasmid genomes. Since it is difficult to confirm which host a particular plasmid definitely cannot enter, we develop a machine learning approach for predicting whether a plasmid can enter a specific bacterium as a no negative samples learning task. Using multiple one-class SVMs that do not require negative samples for training, the HRPredict predicts the host range of plasmids across 45 families, 56 genera, and 56 species. In the benchmark test set, we constructed reliable negative samples for each host taxonomic unit via two indirect methods, and we found that the AUC, F1-score, recall, precision, and accuracy of most taxonomic unit prediction models exceeded 0.9. Among the 13 broad-host-range plasmid types, HRPredict demonstrated greater coverage than HOTSPOT and PlasmidHostFinder, thus successfully predicting the majority of hosts previously reported. Through the feature importance calculation for each SVM model, we found that genes closely related to the plasmid host range are involved in functions such as bacterial adaptability, pathogenicity, and survival. These findings provide significant insight into the mechanisms through which bacteria adjust to diverse environments through plasmids. Impact StatementPlasmids are important vectors for horizontal gene transfer and play a crucial role in regulating bacterial host adaptation to the environment. The spread of plasmid-mediated antibiotic resistance genes and virulence factors is one of the most important public health issues today. Owing to the lack of highly efficient methods for predicting the host range of newly discovered plasmids, especially broad-host-range plasmids, it is difficult to fully elucidate the regulatory role of plasmids in microbial communities and to predict the risk of antibiotic resistance transmission in clinical settings. Existing prediction tools tend to underestimate the host range of mobilizable plasmids. The current paper aims to overcome this limitation. Based on the concept of a "no negative samples learning task," we propose a new plasmid host range prediction method (i.e., HRPredict) that uses an SVM algorithm based on language models. HRPredict may be a powerful tool that will improve biologists understanding of horizontal plasmid transfer and help predict the occurrence and development of bacterial resistance. Data SummaryHRPredict is freely available via https://github.com/FengTaoSMU/HRPredict.

bioinformatics↗

bioRxiv2024

Decoding protein glycosylation by an integrative mass spectrometry-based de novo sequencing strategy

Glycoproteins, representing over 50% of human proteins and most biopharmaceuticals, are crucial for regulating various biological processes. The complexity of multiple glycosylation sites, often leading to incomplete sequence coverage and ambiguous glycan modification profiles. Here, we developed an integrative mass spectrometry-based approach for decoding unknown glycoproteins, which is featured with the combination of deglycosylation-mediated de novo sequencing with glycosylation site characterization. We utilized enzymatic deglycosylation of N-/ O-glycan to achieve comprehensive sequence coverage. Additionally, EThcD fragmentation enables the identification of high-quality long peptides, facilitating precise protein assembly. We subsequently applied this method to de novo sequencing of the highly glycosylated therapeutic fusion protein Etanercept (Enbrel(R)). We also sequenced three new tumor necrosis factor receptor (TNFR): Fc-fusion biologics with largely unknown sequences, unveiling subtle distinctions in the primary sequences. Furthermore, we characterized N- and O-glycosylation modifications of these proteins at subunit, glycopeptide, and glycan levels. This strategy bridges the gap between the de novo sequencing and glycosylation modification, providing complete information of the primary structure and glycosylation modifications for glycoproteins. Notably, our method could be a robust solution for accurate sequencing of the glycoproteins and has practical value not only in basic research but also in the biopharmaceutical industry.

biochemistry↗

bioRxiv2024

DNA methylation protects cancer cells against non-canonical senescence

Inhibitors of DNA methylation such as 5-aza-deoxycytidine are widely used in experimental and clinical settings. However, their mechanism of action is such that DNA damage inevitably co-occurs with loss of DNA methylation, making it challenging to discern their respective effects. Here we deconvolute the effects of decreased DNA methylation and DNA damage on cancer cells, by using degron alleles of key DNA methylation regulators. We report that cancer cells with decreased DNA methylation --but no DNA damage-- enter cellular senescence, with G1 arrest, SASP expression, and SA-{beta}-gal positivity. This senescence is independent of p53 and Rb, but involves p21, which is cytoplasmic and inhibits apoptosis, and cGAS, playing a STING-independent role in the nucleus. Xenograft experiments show that tumor cells can be made senescent in vivo by decreasing DNA methylation. These findings reveal the intrinsic effects of loss of DNA methylation in cancer cells and have practical implications for future therapeutic approaches.

molecular biology↗

bioRxiv2024

Telomere-to-telomere, gap-free genome of mung beans (Vigna radiata) provides insights into domestication under structural variation

Mung bean (Vigna radiata), an essential annual legume, holds substantial value in global agriculture due to its short growth cycle, low input requirements, and nutritional benefits. Despite extensive domestication, the genetic mechanisms underlying its morphological and physiological evolution remain incompletely understood. In this study, we present a gap-free, telomere-to-telomere genome assembly of the mung bean cultivar Weilv-9, achieved through the integration of PacBio HiFi, Oxford Nanopore, and Hi-C sequencing technologies. The 500 Mb assembly, encompassing 11 chromosomes and containing 28,740 protein-coding genes, reveals that 49.17% of the genome comprises repetitive sequences. Within the genome, we found the recent amplification of transposable elements significantly impacts the expression of nearby genes. Furthermore, integrating structural variation and SNP data from resequencing, we identified that the fatty acid synthesis, suberin biosynthetic, and phenylpropanoid metabolic processes have undergone strong selection during domestication. These findings provide valuable insights into the genetic mechanisms driving domestication and offer a foundation for future genetic enhancement and breeding programs in mung beans and related species.

genomics↗

bioRxiv2024

A toolbox of FRET-based c-di-GMP biosensors and its FRET-To-Sort application for genome-wide mapping of the second messenger regulatory network

C-di-GMP is a widespread second messenger, coordinating various cellular functions in bacteria. Levels of c-di-GMP can be highly dynamic and vary over a wide range of concentrations. Here we constructed a large set of FRET-based c-di-GMP biosensors, using homologues of c-di-GMP-binding effector YcgR from different bacterial species. This biosensor library was characterized using a newly established protocol to quantify FRET efficiency using flow cytometry. The resulting toolbox of 18 selected biosensors that undergo large FRET signal change upon c-di-GMP binding displays a [~]100-fold range of c-di-GMP binding affinities. We combined this toolbox with a barcoded Tn5 transposon library and cytometry-based cell sorting to develop FRET-To-Sort, a new application for systematic characterization of gene networks regulating levels of FRET-detected small molecules. Applied to planktonic E. coli cells, FRET-To-Sort identified both known and novel regulatory modules controlling c-di-GMP levels, including flagellum and fimbria biogenesis, lipid metabolism and stress response genes.

microbiology↗

bioRxiv2024

Enhancing Variant Calling in Whole Exome Sequencing (WES) Data Using Population-Matched Reference Genomes

Whole exon sequencing (WES) data are frequently used for cancer diagnosis and genome-wide association studies (GWAS), hinging upon high-coverage read mapping, informative variant calling, and high-quality reference genomes. The center position of the currently used genome assembly, GRCh38, is now challenged by two newly publicized telomere-to-telomere or T2T genomes, T2T-CHM13 and T2T-YAO, and it becomes urgent to have a comparative study to test population specificity using the three reference genomes based on real case WES data. We here report our analysis along this line for 19 tumor samples collected from Chinese patients. The primary comparison of the exon regions among the three references reveals that the sequences in up to [~]1% target regions in YAO are widely diversified from GRCh38 and may lead to off-target in sequence capture. However, YAO still outperforms GRCh38 genomes by obtaining 7.41% more mapped reads. Due to more reliable read-mapping and closer phylogenetic relationship with the samples than GRCh38, YAO reduces half of variant calls of clinical significance which are mostly benign while keeping sensitivity in identifying pathogenic variants. YAO also outperforms CHM13 in reducing calls of Chinese-specific variants. Our findings highlight the critical need for employing population-specific reference genomes in genomic analysis to ensure accurate variant analysis and the significant benefits of tailoring these approaches to the unique genetic backgrounds of each ethnic group.

genomics↗

bioRxiv2024

Low-cost and highly efficient generation of near-complete bacterial pathogen genomes by TELL-Seq

Recent evidences suggest that de novo genome assembly can provide additional insights into genomic variation landscape beyond short-read NGS analyses. Despite the advent of longread sequencing technologies, generating high-quality bacterial genome assemblies remains expensive and requires high-quality and large quantities of DNA. TELL-Seq, an emerging linked-read technology, has been reported as a low-cost alternative for producing nearcomplete genome assembly in certain bacterial species. However, a systematic assessment of its performance and characteristics in de novo bacterial genome assembly has not yet been conducted. To address this, we benchmarked TELL-Seq using a set of clinical and standard bacterial pathogens with a wide range of genome size (2.0 6.4 Mbp), GC-content (32% - 68%), genome complexity (mappability from 0.15 to 0.60) and Gram types. Our findings indicate that, with 1/6 cost and 1/15,000 of DNA compared to PacBio HiFi, TELL-Seq could generate as high quality near-complete bacterial genome assemblies. The optimal depth for assembly is around 200x, as increased depth improves contiguity and completeness, though quality plateaus at 250x. In general, genome complexity was significantly correlated with assembly quality, but GC-content was not. Nevertheless, genomes with extreme GC-content may require higher depths for accurate assembly. Our study suggests that TELL-Seq could be a scalable method for large-scale bacterial genomic surveys. The data generated from this study could serve as a benchmark dataset for further algorithm development. Impact StatementAn increasing body of literature have shown that de novo genome assembles could provide additional insights into genomic variation beyond standard short-read technologies. Its particularly useful in clinical and epidemiological studies of bacteria, due to high variable nature of their genomes. Although great advances have been made in long-read sequencing technology, its still expensive with high requirement over sample DNAs quality and quantity, limiting its adoption in large-scale studies or surveys. Linked-read technology is an inexpensive alternative which used single molecule barcoding to mark origin of reads for better scaffolding of contigs assembled from normal short reads. TELL-Seq, as one of these promising technologies, was reported to be able to inexpensively and efficiently generate near-complete bacterial de novo genomic assemblies with low DNA inputs. Theres not yet a systematic benchmarking of this technology in bacterial pathogens. In this study, a set of clinically important bacterial pathogens with a wide spectrum of GC-content, genome size, genome complexity, and Gram Type were used to investigate the performance of TELL-Seq technology in de novo genome assembly. We found that, with about 1/6 of cost and 1/15000 of DNA quantity, it could generate comparable de novo assemblies compared to standard reference genomes or PacBio HiFi assemblies, while beating conventional short-read assemblies. We found several key factors, such as genome complexity, and sequencing depth, which would impact the quality of the assembly. Our study suggests that a sequencing depth of 200x is sufficient to achieve satisfactory results. Our study has revealed characteristics of this technology in bacterial genome assembly and paved the way for its large-scale application in clinical or epidemiological surveys. Data SummaryO_LIRaw sequencing data for all isolates have been deposited to SRA, accessible through these NCBI BioProject PRJNA1133244. C_LIO_LIA full list of SRA BioSample accession numbers are available in Tab S5. C_LIO_LIAssemblies and analyses companion this paper is available at: https://github.com/x-lab/tellseq_bacteria C_LI

bioinformatics↗

bioRxiv2024

Improving the value utilization of tuna peptide powder for the cosmetics field through ozone oxidation

To improve the utilization efficiency of small molecule peptides in marine proteins and promote their application in cosmetics, this study adopts ozone oxidation to conduct deodorization research on tuna small molecule peptides. To devise a method for the ozone oxidation and deodorization of tuna peptide powder suitable for the cosmetics field, orthogonal tests were carried out. The time, ozone concentration, and temperature were adjusted to determine the optimal conditions for ozonation and deodorization of tuna peptide powder. The results showed that at 50{degrees}C and an ozone concentration of 99.10 x 103 mg/m3, wet ozone oxidation for 40 min can also significantly reduce the fishy smell. Under these conditions, the color of tuna peptide powder treated with wet ozone was lighter. In addition, the main volatile compounds were detected by gas chromatography-mass spectrometry (GC-MS). The content of the main fishy volatile substance, hexanal, decreased by 66.4%, and two octyl aldehydes were observed. The results also showed that the protein activity of tuna peptide powder after ozonation remained unchanged. Thus, this study presents an approach to the ozone oxidation of tuna peptide powder that is suitable for cosmetics.

bioengineering↗

bioRxiv2024

Bioinspired Bimetallic Ions Functionalized MOF SAzyme Nanocomposites for Synergistic Ferroptosis/Cuproptosis-Enhanced Immune Checkpoint Therapy

Immune checkpoint blockade (ICB) generates sustained responses in immunogenic cancers, but its effectiveness is limited in tumors lacking immune activity. Here, we construct a bioinspired bimetallic ions functionalized nanoscale metal-organic framework (NMOF) single-atom nanozyme (SAzyme) loaded with doxorubicin (Dox) (NMOF-Fe/Cu-Dox nanocomposite) to effectively trigger anti-tumor immune responses while addressing the immunosuppressive tumor microenvironment (TME). The NMOF-Fe/Cu-Dox nanocomposite has been demonstrated to efficiently reverse the TME by generating reactive oxygen species and oxidizing glutathione. Camouflaging NMOF-Fe/Cu-Dox nanocomposites with bioinspired cancer cell membrane (NMOF-Fe/Cu-Dox@M) enables its navigation to the tumor region through homologous targeting. The highly efficient uptaken by cancer cells selectively induced synergistic ferroptosis and cuproptosis in these cells. Furthermore, in vitro and in vivo experiments demonstrate that the ferroptosis in cancer cells can polarize tumor-associated macrophages (TAMs) towards anti-tumoral M1 phenotype and significantly diminish pro-tumoral M2 phenotype. We find that NMOF-Fe/Cu-Dox@M could induce the ferroptosis of M2 macrophages, while no effect to M1 macrophages. In addition, a significant increase of anti-tumor infiltrating CD8+ T cells, while a remarkable decrease of CD4+ regulatory T cells were observed. These findings suggested that NMOF-Fe/Cu-Dox@M could efficiently modulate TME, enhance tumoricidal immunity and elevate the therapeutic efficiency of ICB. Moreover, the combination of NMOF-Fe/Cu-Dox@M with PD-1 effectively eradicated hepatocellular carcinoma cells in vivo, outperforming the use of either NMOF-Fe/Cu-Dox@M or PD-1 alone. In summary, our study presents a therapeutic strategy that leverages coordinated ferroptosis and cuproptosis with therapeutic efficiency of ICB, underscoring the promise of combined chemoimmunotherapy.

bioengineering↗

bioRxiv2024

Simplified and Rapid Workflow Enhances Throughput of De Novo Sequencing of COVID-19 Neutralizing Antibodies

During the current COVID-19 pandemic, precise antibody sequencing is crucial for the rapid development of broad-spectrum or pan-{beta}-coronavirus neutralizing antibodies (NAbs) to prevent new variants of the coronavirus and other highly pathogenic {beta}-coronaviruses. However, mass spectrometry-based de novo sequencing remains challenging due to its high cost, low throughput, and unexpected missing of certain ion information. We developed an innovative approach using solely bottom-up to provide a rapid, robust, and refined solution for the current de novo sequencing challenges. The methodology, referred to as SP-MEGD for Single-Pot and Multi-Enzymatic Gradient Digestion, capitalizes on a five-protease gradient digestion by sampling every two hours for a total of 6 hours in an integrative reactor. The SP-MEGD method could engender numerous missed cleavage events and produce various peptide products of diverse lengths with overlapping stretches of residues, enabling efficient database-free de novo sequencing. Antibody assembly for single or mixed COVID-19-NAbs with publicly available sequences and commercial antibodies with unknown sequences was efficiently deciphered using our previously proposed optimization method, Fusion assembler. Our innovative study represents the first successful simultaneous discrimination and achieving over 99% accurate sequence coverage of a mixture containing three humanized COVID-19-NAbs (S2P6LH, BD5514LH, and BD5840LH). Furthermore, we utilized SP-MEGD and Fusion to sequence commonly used anti-CD8 and anti-CD4, and successfully confirmed their impact on immune cell clearance through in vivo experiments. Overall, our developed workflow demonstrates promise in facilitating the discovery and development of vaccines and antibody therapeutics while providing deeper insights into monoclonal antibodies (mAbs).

bioengineering↗

bioRxiv2024

Quantitative comparison of single-cell RNA sequencing versus single-molecule RNA imaging for quantifying transcriptional noise

Stochastic fluctuations (noise) in transcription generate substantial cell-to-cell variability. However, how best to quantify genome-wide noise, remains unclear. Here we utilize a small-molecule perturbation (IdU) to amplify noise and assess noise quantification from numerous scRNA-seq algorithms on human and mouse datasets, and then compare to noise quantification from single-molecule RNA FISH (smFISH) for a panel of representative genes. We find that various scRNA-seq analyses report amplified noise, without altered mean-expression levels, for [~]90% of genes and that smFISH analysis verifies noise amplification for the vast majority of genes tested. Collectively, the analyses suggest that most scRNA-seq algorithms are appropriate for quantifying noise including a simple normalization approach, although all of these systematically underestimate noise compared to smFISH. From a practical standpoint, this analysis argues that IdU is a globally penetrant noise-enhancer molecule--amplifying noise without altering mean-expression levels--which could enable investigations of the physiological impacts of transcriptional noise. MOTIVATIONCell-to-cell variability in isogenic populations is predominantly attributed to the stochastic fluctuations (i.e., noise) in transcription. However, the quantification of this noise, particularly on a genome-wide scale, remains an open question. To address this general question, here we utilize a small-molecule perturbation reported to amplify transcriptional noise. Previous single-cell RNA-sequencing (scRNA-seq) analysis indicated that the pyrimidine nucleobase 5'-iodo-2'-deoxyuridine (IdU) amplifies noise but technical drawbacks of scRNA-seq may have obscured the penetrance and degree of noise amplification. Consequently, here we assess numerous scRNA-seq algorithms, on two different scRNA-seq datasets for a human and mouse cell type, for their ability to quantify noise amplification and then compare the results to noise quantification from single-molecule RNA FISH (smFISH) imaging for a panel of representative genes. The specific questions addressed are whether IdU amplifies noise in a globally or partially penetrant manner, and what scRNA-seq algorithm is most appropriate for quantifying transcriptional noise. O_FIG O_LINKSMALLFIG WIDTH=184 HEIGHT=200 SRC="FIGDIR/small/607289v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1f9b17aorg.highwire.dtl.DTLVardef@1f2d410org.highwire.dtl.DTLVardef@1407cfaorg.highwire.dtl.DTLVardef@cd2bc9_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG

systems biology↗

bioRxiv2024

Multi-modal, Label-free, Optical Mapping of Cellular Metabolic Function and Oxidative Stress in 3D Engineered Brain Tissue Models

Brain metabolism is essential for the function of organisms. While established imaging methods provide valuable insights into brain metabolic function, they lack the resolution to capture important metabolic interactions and heterogeneity at the cellular level. Label-free, two-photon excited fluorescence imaging addresses this issue by enabling dynamic metabolic assessments at the single-cell level without manipulations. In this study, we demonstrate the impact of spectral imaging on the development of rigorous intensity and lifetime label-free imaging protocols to assess dynamically metabolic functions over time in 3D engineered brain tissue models comprised of human induced neural stem cells, astrocytes, and microglia. Specifically, we rely on multi-wavelength spectral imaging to identify the excitation/emission profiles of key cellular fluorophores within human brain cells, including NAD(P)H, LipDH, FAD, and lipofuscin. These enable the development of methods to mitigate lipofuscins overlap with NAD(P)H and flavin autofluorescence to extract reliable optical metabolic function metrics from images acquired at two excitation wavelengths over two emission bands. We present fluorescence intensity and lifetime metrics reporting on redox state, mitochondrial fragmentation, and NAD(P)H binding status in neuronal monoculture and the triculture systems to highlight the functional impact of metabolic interactions between different cell types. Our findings reveal significant metabolic differences between neurons and glial cells, shedding light on metabolic pathway utilization, including the glutathione pathway, OXPHOS, glycolysis, and fatty acid oxidation. Collectively, our studies establish a label-free, non-destructive approach to assess the metabolic function and interactions among different brain cell types relying on endogenous fluorescence and illustrate the complementary nature of the information that is gained by combining intensity and lifetime-based images. Such methods can improve understanding of physiological brain function and dysfunction that occurs at the onset of cancers, traumatic injuries and neurodegenerative diseases.

bioengineering↗

bioRxiv2024

Study on the phenotypic diversity and comprehensive evaluation analysis of 43 ornamental peonies of Sect. Paeonia.

The peony of Sect. Paeonia was a perennial herbaceous plant with numerous ornamental varieties and riched diversity in flower color and shape. It has ornamental, edible, and medicinal value and a long history of cultivation in China. The study of phenotypic diversity of plants is an important foundation for plants of Sect. Paeonia breeding. This study conducted phenotypic diversity analysis, principal component analysis, and cluster analysis on 43 varieties of Sect. Paeonia germplasm resources. Phenotypic traits included 30 qualitative traits and 7 quantitative traits. Through genetic diversity analysis, principal component analysis, comprehensive evaluation, and cluster analysis, we ultimately concluded that plant samples had relatively rich genetic phenotype traits. In principal component analysis, the first 12 principal components have covered the vast majority of information for phenotypic traits. The comprehensive evaluation results of phenotypic traits indicate that the F values of each variety in the germplasm sample were all positive number. The degree of stamen petals played a key role in determining the phenotypic diversity of plants, and the shape of the cotyledons and leaflets may determine the plants stress resistance performance, which provides a reference for breeding new varieties of peonies of Sect. Paeonia.

plant biology↗

bioRxiv2024

A Tough Biointerface in Human Knee Empowered by Dynamic Phase-transforming Minerals in Collagenous Matrix

Joining heterogeneous materials in engineered structures remains a daunting challenge because of stress concentration, often resulting in unexpected failures1,2. Studying the structures in organisms that evolved for centuries provides valuable insights that can be instrumental in addressing this mechanical challenge3-5. The human meniscus root-bone interface is a remarkable example known for its exceptional fatigue resistance, toughness and interfacial adhesion properties throughout its lifespan6-8. We studied the multiscale graded mineralization structure designs within the 30-micron soft-hard interface at the root-bone junction and examined its toughening mechanisms. This graded interface with interdigitated structures and exponential modulus increase exhibits a phase transition from amorphous calcium phosphate (ACP) to gradually matured hydroxyapatite (HAP) crystals, mediated by location-specific distributed biomolecules. In coordination with collagen fibril deformation and reorientation, ACP particles debond with collagen and slide to new positions which enable frictional energy dissipation, and HAP particles arrest cracks. The mineral in transforming phases work synergistically to provide interfacial toughening. The presented biointerface model exemplifies human musculoskeletal systems adaptations to mechanical requirements, offering a blueprint for developing tough interfaces in broad applications.

bioengineering↗

bioRxiv2024

Endocytic dynamin deficiency impairs the host colonization of phytopathogenic fungi

During host-pathogen interactions, fungal pathogens exploit the endolysosomal trafficking network to fine-tune their responses to host and environmental stimuli, thereby facilitating disease progression. However, the molecular mechanisms underlying the fungal-specific functions of the endolysosomal network require further investigation. Here, we systematically characterized the endolysosomal network in Fusarium graminearum using the dynamin-like GTPase FgVps1 as an entry point. Functional analysis revealed that FgVps1 is essential for the release of retromer- and sorting nexin-associated vesicles from endosomes, thereby facilitating the trafficking of v-SNARE protein FgSnc1 and promoting fungal development and pathogenicity. Building on this, we further discovered that the retromer core subunit FgVps35 interacts with sorting nexin FgSnx4 and identified the corresponding interaction interface, which involves residues FgVps35N383 and FgSnx4E373. In addition, the ESCRT-II component FgVps36 bridges ESCRT-I and -III and interacts with both FgVps35 and FgSnx4, thereby preventing their mislocalization to the vacuole and maintaining endolysosomal trafficking. Notably, we demonstrated that inhibition of FgVps1 function, either by blocking its GTPase activity or by disrupting actin polymerization, effectively impaired endosomal trafficking and attenuates fungal pathogenicity. Altogether, our results uncover key mechanisms underlying the function of fungal endolysosomal network and providing a promising broad-spectrum strategy for controlling phytopathogenic fungi.

microbiology↗

bioRxiv2024

Cholecystokinin modulates age-dependent Thalamocortical Neuroplasticity

The thalamocortical pathways exhibit neuroplasticity not only during the critical period but also in adulthood. In this study, we investigated how cholecystokinin (CCK) modulates age-dependent thalamocortical plasticity. Our findings demonstrated that CCK is expressed in thalamocortical neurons and that high-frequency stimulation (HFS) of the thalamocortical pathway triggers the release of CCK in auditory cortex (ACx), as detected by a CCK sensor. HFS of the medial geniculate body (MGB) induced thalamocortical long-term potentiation (LTP) in wild-type young adult mice. However, knockdown of Cck expression in MGB neurons or blockade of the CCK-B receptor (CCKBR) in the ACx abolished HFS-induced LTP. Interestingly, this LTP could not be elicited in juvenile (3-week-old) or aged mice (over 18-month-old) due to distinct mechanisms: the absence of CCKBR in juveniles and the inability to release CCK in aged mice. Notably, exogenous administration of CCK into the ACx rescued LTP in aged mice and significantly improved frequency discrimination. These findings highlight the potential of CCK as a therapeutic intervention for ameliorating neuroplasticity deficits associated with thalamocortical connectivity.

neuroscience↗