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Song, Y.

Publications and source records attributed to Song, Y..

At least 253 records · Page 14Linked to original sources
bioRxiv2022

First identification and investigation of piRNAs in the larval guts of Asian honey bee, Apis cerana

Piwi-interacting RNAs (piRNAs), a kind of small non-coding RNAs (ncRNAs), play pivotal parts in maintaining the genomic stability and modulating biological processes such as growth and development via regulation of gene expression. However, piRNAs in Asian honey bee (Apis cerana) is still largely unknown at present. In this current work, on basis of previously gained high-quality small RNA-seq datasets, piRNAs in the larval guts of Apis cerana cerana, the nominate species of A. cerana, was for the first time identified, followed by in-depth investigation of the regulatory roles of differentially expressed piRNAs (DEpiRNAs) in the developmental process of the A. c. cerana. Here, a total of 621 piRNAs were identified in the A. c. cerana larval guts, among which 499 piRNAs were shared by 4- (Ac4 group), 5- (Ac5 group), and 6-day-old (Ac6 group) larval guts, while the numbers of unique ones were 79, 37, and 11, respectively. piRNAs each group were ranged from 24 nt to 33 nt in length, and the first base of piRNAs had a cytosine (C) bias. Additionally, five up-regulated and five down-regulated piRNAs were identified in the Ac4 vs. Ac5 comparison group, 9 of which could target 9, 011 mRNAs; these targets were involved in 41 GO terms and 137 pathways. Comparatively, 22 up-regulated piRNAs were detected in the Ac5 vs. Ac6 comparison group, 21 of which could target 28, 969 mRNAs; these targets were engaged in 46 functional terms and 164 pathways. The results suggested the overall alteration of expression pattern of piRNAs during the developmental process of A. c. cerana larvae. Regulatory network analysis showed that piR-bmo-748815 and piR-bmo-512574 in the Ac4 vs. Ac5 comparison group as well as piR-bmo-716466 and piR-bmo-828146 in the Ac5 vs. Ac6 comparison group linked to the highest number of targets. Further investigation indicated that targets of DEpiRNAs in the above-mentioned two comparison groups could be annotated to several growth and development-associated pathways, such as Jak/STAT, TGF-{beta}, and Wnt signaling pathways, indicating the involvement of DEpiRNAs in modulating larval gut development via these crucial pathways. Moreover, the expression trends of six randomly selected DEpiRNAs were verified using a combination of stem-loop RT-PCR and RT-qPCR. These results not only provide a novel insight into the development of the A. c. cerana larval guts, but also lay a foundation for uncovering the epigenetic mechanism underlying the larval gut development.

molecular biology↗
bioRxiv2022

Mechanical force induces DRP1-dependent asymmetrical mitochondrial fission for quality control

Mitochondria are membrane-bound organelles that perform diverse critical biological functions. They undergo constant fission and fusion, which are important for mitochondrial inheritance, functions, and quality control. While tremendous efforts have identified many factors governing mitochondria dynamics, emerging evidence indicates the involvement of various intracellular or extracellular mechanical cues. However, how mechanical stress directly modulates mitochondrial dynamics remains largely unknown. Here utilizing an optogenetic mitochondria-specific mechanostimulator to apply pulling forces to intracellular mitochondria, we find that mechanostimulation can promote mitochondrial fission, with sustained mechanostimulation triggering fission more effectively than transient one. Asymmetrical fission can occur at different sub-mitochondrial sites after force-induced mitochondrial elongation. Such force-induced fission is dependent on DRP1 and involves the wrapping of ER tubules. Moreover, mechanical force generates mitochondrial fragments without mtDNA which recruit Parkin proteins. Our results prove the mechanosensitivity and mechanoresponsiveness of mitochondria and reveal the role of mechanical cues in directly regulating mitochondrial dynamics.

cell biology↗
bioRxiv2022

Proliferative Exhausted CD8 T Cells Exacerbate Long-lasting Anti-tumor Effects in Human Papillomavirus Positive Head and Neck Squamous Cell Carcinoma

The survival prognosis of human papillomavirus (HPV)-positive and HPV-negative head and neck squamous cell carcinoma (HNSCC) is largely different, and little is known about the anti-tumor mechanism of tumor-infiltrated CD8+ exhausted T cells (Tex) in HNSCC. We performed cell level multi-omics sequencing on human HNSCC samples to decipher the multi-dimensional characteristics of Tex cells. A proliferative exhausted CD8+ T cell cluster (P-Tex) which was beneficial to survival outcomes of patients with HPV-positive HNSCC was identified. Interestingly, P-Tex cells expressed CDK4 genes as high as cancer cells, which could be simultaneously inhibited by CDK4 inhibitors and might be a potential reason for the ineffectiveness of CDK4 inhibitors in treating HPV-positive HNSCC. P-Tex cells could aggregate in the antigen presenting cell niches and activate certain signaling pathways. Together, our findings suggest a promising role for P-Tex cells in the prognosis of patients with HPV-positive HNSCC by providing modest but persistent anti-tumor effects. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/513993v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1f8810forg.highwire.dtl.DTLVardef@1e11d84org.highwire.dtl.DTLVardef@58fb6aorg.highwire.dtl.DTLVardef@1e20a13_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗
bioRxiv2022

The Quartet Data Portal: integration of community-wide resources for multiomics quality control

The implementation of quality control for multiomic data requires the widespread use of well-characterized reference materials, reference datasets, and related resources. The Quartet Data Portal was built to facilitate community access to such rich resources established in the Quartet Project. A convenient platform is provided for users to request the DNA, RNA, protein, and metabolite reference materials, as well as multi-level datasets generated across omics, platforms, labs, protocols, and batches. Interactive visualization tools are offered to assist users to gain a quick understanding of the reference datasets. Crucially, the Quartet Data Portal continuously collects, evaluates, and integrates the community-generated data of the distributed Quartet multiomic reference materials. In addition, the portal provides analysis pipelines to assess the quality of user-submitted multiomic data. Furthermore, the reference datasets, performance metrics, and analysis pipelines will be improved through periodic review and integration of multiomic data submitted by the community. Effective integration of the evolving technologies via active interactions with the community will help ensure the reliability of multiomics-based biological discoveries. The Quartet Data Portal is accessible at https://chinese-quartet.org. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

systems biology↗
bioRxiv2022

Benchmarking strategies for cross-species integration of single-cell RNA sequencing data

The growing number of available single cell gene expression datasets from different species creates opportunities to explore evolutionary relationships between cell types across species. Cross-species integration of single-cell RNA-sequencing data has been particularly informative in this context. However, in order to do so robustly it is essential to have rigorous benchmarking and appropriate guidelines to ensure that integration results truly reflect biology. We benchmarked 28 combinations of gene homology mapping methods and data integration algorithms in a variety of biological settings. We examined the capability of each strategy to perform species-mixing of known homologous cell types and to preserve biological heterogeneity using 9 established metrics. We also developed a new biology conservation metric to address the maintenance of cell type distinguishability. Overall, scANVI, scVI and SeuratV4 methods achieved a balance between species-mixing and biology conservation. For evolutionarily distant species, including in-paralogs was beneficial. SAMap outperformed when integrating whole-body atlases between species with challenging gene homology annotation. We provided our freely available cross-species integration and assessment pipeline to help analyse new data and develop new algorithms.

bioinformatics↗
bioRxiv2022

Allosteric regulation and crystallographic fragment screening of SARS-CoV-2 NSP15 endoribonuclease

SARS-CoV-2 is the causative agent of COVID-19. The highly conserved viral NSP15 endoribonuclease, NendoU, is a key enzyme involved in viral immune evasion, and a promising target for the development of new classes of antivirals. Yet, the broad variety of recognition sequences, complex assembly and kinetics, and lack of structural complexes hampers the development of new competitive or allosteric inhibitors for this target. Here, we performed enzymatic characterization of NendoU in its monomeric and hexameric form, showing that hexamers are allosteric enzymes with a positive cooperative index of 2. By using cryo-EM at distinct pHs combined with X-ray crystallography and structural analysis, we demonstrate the potential for NendoU to shift between open and closed states, and assembly in larger supramolecular entities, which might serve as a mechanism of self-regulation. Further, we report results from a large fragment screening campaign against NendoU, revealing multiple new allosteric sites for the development of inhibitors.

biochemistry↗
bioRxiv2022

Moderate activity of RNA chaperone maximizes the yield of self-spliced pre-RNA in vivo

CYT-19 is a DEAD-box protein whose ATP-dependent helicase activity facilitates the folding of group I introns in precursor RNA (pre-RNA) of Neurospora crassa. In the process they consume a substantial amount of ATP. While much of the mechanistic insights into CYT-19 activity has been gained through the studies on the folding of Tetrahymena group I intron ribozyme, the more biologically relevant issue, namely the effect of CYT-19 on the self-splicing of pre-RNA, remains largely unexplored. Here, we employ a kinetic network model, based on the generalized iterative annealing mechanism, to investigate the relation between CYT-19 activity, rate of ribozyme folding, and the kinetics of the self-splicing reaction. The network rate parameters are extracted by analyzing the recent biochemical data for CYT-19-facilitated folding of T. ribozyme. We then build extended models to explore the metabolism of pre-RNA. We show that the timescales of chaperone-mediated folding of group I ribozyme and self-splicing reaction compete with each other. As a consequence, in order to maximize the self-splicing yield of group I introns in pre-RNA, the chaperone activity must be sufficiently large to unfold the misfolded structures, but not too large to unfold the native structures prior to the self-splicing event. We discover that despite the promiscuous action on structured RNAs, the helicase activity of CYT-19 on group I ribozyme gives rise to self-splicing yields that are close to the maximum. Significance StatementIn cells, RNA chaperones assist misfolding-prone ribozymes to fold correctly to carry out its biological function. CYT-19 is an ATP-consuming RNA chaperone that accelerates the production of native group I intron ribozyme by partially unfolding the kinetically trapped structures. Using the theoretical framework based on the iterative annealing mechanism, we establish that to maximize the processing of pre-RNA, an optimal balance should exist between the timescales of self-splicing activity and CYT-19-mediated production of the native ribozyme. Remarkably, the activity of CYT-19 has been optimized to unfold the misfolded structures but is not so high that it disrupts the native ribozyme, which ensures that the yield of the self-splicing reaction is maximized in a biologically relevant time scale.

biophysics↗
bioRxiv2022

3D electron diffraction reveals the chiral nature of the malaria pigment crystal hemozoin

Detoxification of heme in Plasmodium depends on its crystallization into hemozoin. This pathway is a major target of antimalarial drugs. X-ray powder diffraction has established that the unit cell contains a cyclic hematin dimer, yet the pro-chiral nature of heme supports formation of four distinct stereoisomers, two centrosymmetric and two chiral enantiomers. Here we apply emerging methods of in situ cryo-electron tomography and diffraction to obtain a definitive structure of biogenic hemozoin. Individual crystals take a striking polar morphology. Diffraction analysis, supported by density functional theory, indicates a compositional mixture of one centrosymmetric and one chiral dimer, whose absolute configuration has been determined on the basis of crystal morphology and interaction with the aqueous medium. Structural modeling of the heme detoxification protein suggests a mechanism for dimer selection. The refined structure of hemozoin should serve as a guide to new drug development.

microbiology↗
bioRxiv2022

Imbalanced classification for protein subcellularlocalisation with multilabel oversampling

MotivationSubcellular localisation of human proteins is essential to comprehend their functions and roles in physiological processes, which in turn helps in diagnostic and prognostic studies of pathological conditions and impacts clinical decision making. Since proteins reside at multiple locations at the same time and few subcellular locations host far more proteins than other locations, the computational task for their subcellular localisation is to train a multilabel classifier while handling data imbalance. In imbalanced data, minority classes are underrepresented, thus leading to a heavy bias towards the majority classes and the degradation of predictive capability for the minority classes. Furthermore, data imbalance in multilabel settings is an even more complex problem due to the coexistence of majority and minority classes. ResultsOur studies reveal that based on the extent of concurrence of majority and minority classes, oversampling of minority samples through appropriate data augmentation techniques holds promising scope for boosting the classification performance for the minority classes. We measured the magnitude of data imbalance per class and the concurrence of majority and minority classes in the dataset. Based on the obtained values, we identified minority and medium classes, and a new oversampling method is proposed that includes nonlinear mixup, geometric and colour transformations for data augmentation and a sampling approach to prepare minibatches. Performance evaluation on the Human Protein Atlas Kaggle challenge dataset shows that the proposed method is capable of achieving better predictions for minority classes than existing methods. AvailabilityData used in this study is available at https://www.kaggle.com/competitions/human-protein-atlas-image-classification/data. Contactyang.song1@unsw.edu.au Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗
bioRxiv2022

ggcoverage: an R package to visualize and annotate genome coverage for various NGS data

SummaryVisualizing genome coverage is of vital importance to inspect and interpret various next-generation sequencing (NGS) data. However, existing tools that perform such visualizations remain inflexible, complicated, lack necessary annotations and the figures generated are not publication-quality. Here, we introduce ggcoverage, an R package with the grammar of graphics implemented in ggplot2, providing a flexible, programmable and user-friendly way to visualize genome coverage, multiple available annotations to adapt to different NGS data, and generating publication-quality plots. Availability and Implementationggcoverage is an R package available via CRAN (https://cran.r-project.org/web/packages/ggcoverage/index.html) under MIT license. Support is available via GitHub (https://github.com/showteeth/ggcoverage/issues). Data used to generate figures are available on GitHub as example data. Contactsongyb18@mails.tsinghua.edu.cn, jianbinwang@tsinghua.edu.cn.

bioinformatics↗
bioRxiv2022

Data augmentation for imbalanced blood cell image classification

Due to progression in cell-cycle or duration of storage, classification of morphological changes in human blood cells is important for correct and effective clinical decisions. Automated classification systems help avoid subjective outcomes and are more efficient. Deep learning and more specifically Convolutional Neural Networks have achieved state-of-the-art performance on various biomedical image classification problems. However, real-world data often suffers from the data imbalance problem, owing to which the trained classifier is biased towards the majority classes and does not perform well on the minority classes. This study presents an imbalanced blood cells classification method that utilises Wasserstein divergence GAN, mixup and novel nonlinear mixup for data augmentation to achieve oversampling of the minority classes. We also present a minority class focussed sampling strategy, which allows effective representation of minority class samples produced by all three data augmentation techniques and contributes to the classification performance. The method was evaluated on two publicly available datasets of immortalised human T-lymphocyte cells and Red Blood Cells. Classification performance evaluated using F1-score shows that our proposed approach outperforms existing methods on the same datasets.

bioinformatics↗
bioRxiv2022

Tracking neural correlates of prioritizing working memory representations through retrospective attentional strengthening

Previous work has proposed two potentials benefits of retrospective attention on working memory (WM): target strengthening and non-target inhibition. It remains unknown which hypothesis contributes to the improved WM performance, yet the neural mechanisms responsible for this attentional benefit are unclear. Here, we recorded electroencephalography (EEG) signals while 33 participants performed a retrospective-cue WM task. Multivariate pattern classification analysis revealed that only representations of target features were enhanced by valid retrospective attention during the retention, supporting the target strengthening hypothesis. Further univariate analysis found that mid-frontal theta inter-trial phase coherence (ITPC) and ERP components were modulated by valid retrospective attention and correlated with individual differences and moment-to-moment fluctuations on behavioral outcomes, suggesting that both trait- and state-level variability in attentional preparatory processes influence goal-directed behavior. Furthermore, task-irrelevant target spatial location could be decoded from EEG signals, indicating that enhanced spatial binding of target representation promotes high WM precision. Importantly, frontoparietal theta-alpha phase-amplitude-coupling was increased by valid retrospective attention and predicted the reduced randomly guessing rates. This long-range connection supported top-down information flow in engagement of frontoparietal networks, which might organize attentional states to integrate target features. Altogether, these results provide neurophysiological bases that retrospective attention improves WM precision through enhancing representation of target and emphasize the critical role of frontoparietal attentional network in the control of WM representations.

neuroscience↗
bioRxiv2022

Single cell transcriptomic profiling of human brain organoids reveals developmental timing- and cell-type-specific vulnerabilities induced by NRXN1 CNVs in schizophrenia

De novo mutations and copy number deletions in NRXN1 (2p16.3) pose a significant risk for schizophrenia (SCZ). It is unclear how NRXN1 deletions impact cortical development in a cell type-specific manner and disease background modulates these phenotypes. Here, we leveraged human pluripotent stem cell-derived forebrain organoid models carrying NRXN1 heterozygous deletions in isogenic and SCZ patient genetic backgrounds and conducted single-cell transcriptomic analysis over the course of brain organoid development from 3 weeks to 3.5 months. Intriguingly, while both deletions similarly impacted molecular pathways associated with ubiquitin-proteasome system, alternative splicing, and synaptic signaling in maturing glutamatergic and GABAergic neurons, SCZ-NRXN1 deletions specifically perturbed developmental trajectories of early neural progenitors and accumulated disease-specific transcriptomic signatures. Using calcium imaging, we found that both deletions led to long-lasting changes in spontaneous and synchronous neuronal networks, implicating synaptic dysfunction. Our study reveals developmental-timing- and cell-type-dependent actions of NRXN1 deletions in unique genetic contexts.

neuroscience↗
bioRxiv2022

A highly polymorphic effector protein promotes fungal virulence through suppression of plant-associated Actinobacteria

Plant pathogens secrete effector proteins to support host colonization through a wide range of molecular mechanisms, while plant immune systems evolved receptors to recognize effectors or their activities to mount immune responses to halt pathogens. Importantly, plants do not act as single organisms, but rather as holobionts that actively shape their microbiota as a determinant of health, and may thus be targeted by pathogen effectors as such. The soil-borne fungal pathogen Verticillium dahliae was recently demonstrated to exploit the VdAve1 effector to manipulate the host microbiota to promote vascular wilt disease in absence of the corresponding immune receptor Ve1. We now identified a multiallelic V. dahliae gene displaying ~65% sequence similarity to VdAve1, named VdAve1-like (VdAve1L). Interestingly, VdAve1L shows extreme sequence variation, including alleles that encode dysfunctional proteins, indicative of selection pressure to overcome host recognition. We show that the orphan cell surface receptor Ve2, encoded at the Ve1 locus, does not recognize VdAve1L. Furthermore, we show that the full-length variant VdAve1L2 possesses antimicrobial activity, like VdAve1, yet with a divergent activity spectrum. Altogether, VdAve1L2 is exploited by V. dahliae to mediate tomato colonization through the direct suppression of antagonistic Actinobacteria in the host microbiota. Our findings open up strategies for more targeted biocontrol against microbial plant pathogens.

plant biology↗
bioRxiv2022

IL-12/18/21 pre-activation enhances the anti-tumor efficacy of expanded γδT cells and overcomes resistance to anti-PD-L1 treatment

{gamma}{delta}T cells are promising candidates for cellular immunotherapy due to their immune regulation through cytokine production and MHC-independent direct cytotoxicity against a broad spectrum of tumors. However, current {gamma}{delta}T cell-based cancer immunotherapy has limited efficacies and novel strategies are needed to improve its clinical outcomes. Here, we report that cytokine pre-treatment with IL-12/18, IL-12/15/18, IL-12/18/21 and IL-12/15/18/21 could effectively enhance the activation and cytotoxicity of in vitro expanded murine and human {gamma}{delta}T cells. However, only adoptive transfer of IL-12/18/21 pre-activated {gamma}{delta}T cells significantly inhibited tumor growth in a murine melanoma model and a hepatocellular carcinoma model. Both IL-12/18/21 pre-activated antibody-expanded and zoledronate-expanded human {gamma}{delta}T cells effectively controlled tumor growth in a humanized mouse model. IL-12/18/21 pre-activation promoted {gamma}{delta}T cell proliferation and cytokine production in vivo and enhanced IFN-{gamma} and TNF- production, as well as granzyme B expression by endogenous CD8+ T cells in a cell-cell contact dependent manner. Furthermore, the adoptive transfer of IL-12/18/21 pre-activated {gamma}{delta}T cells could overcome the resistance to anti-PD-L1 therapy, and the combination therapy had a synergistic effect on the therapeutic outcomes. Moreover, the enhanced anti-tumor function of adoptively transferred IL-12/18/21 pre-activated {gamma}{delta}T cells was largely diminished in the absent of endogenous CD8+T cells when administered alone or in combination with anti-PD-L1, suggesting a CD8+T cell-dependent mechanism. Taken together, IL-12/18/21 pre-activation could promote {gamma}{delta}T cell anti-tumor function and overcome the resistance to checkpoint blockade therapy, indicating an effective combinational cancer immunotherapeutic strategy. SynopsisO_LIIL-12/18/21 pre-activation enhances the anti-tumor efficacy of adoptively transferred {gamma}{delta}T cells by promoting its proliferation, activation, and cytotoxicity, as well as activating endogenous CD8+ T cells. C_LIO_LIAdoptive transfer of IL-12/18/21 pre-activated {gamma}{delta}T cells could overcome the resistance to anti-PD-L1 therapy, indicating an effective combinational cancer immunotherapeutic strategy. C_LI

immunology↗
bioRxiv2022

The role of GmXTH1, a new xyloglucan endotransglycosylase/hydrolase from soybean, in regulating soybean root growth at seedling stage

Soybean is an important crop for both food and oil, providing high quality protein and oil for humans and animals. Drought stress has an significant effect on the yield and quality of soybean. In the early vegetative stage of soybean, the developed root system can effectively improve the tolerance of soybean plant to drought. Xyloglucan endoglycosylase/hydrolase (XTH) is a cell wall remodeling enzyme involved in cell wall expansion and degradation. However, there are few studies on XTHs regulation of root growth and response to drought stress in soybean seedlings.The objectives of this study were to clone GmXTH1 gene and determine the effects of over and interference-expression of GmXTH1 on soybean root development at seedling stage. A 1,015 bp full-length of the GmXTH1 gene was cloned from soybean (Glycine max L. Merril) cv. RM18 with a 840 bp open reading frame (ORF) of a putative protein. The over and interference expression vectors of GmXTH1 were transformed into soybean using Agrobacterium method. Transformed strains OEA1, OEA3, IEA4, IEA5 were identified by molecular detection methods. The roots of transformed strains OEA1and OEA3 with GmXTH1 gene overexpression are clearly developed and the root phenotypic attributes, including main root length, primary root number, lateral root length, root surface area, root volume, root dry weight, root fresh weight are higher than the control. In contrast, root attributes of IEA4 and IEA5 with GmXTH1 gene interference expression were significantly lower than those of the control, suggesting that the expression of GmXTH1 gene has an important effect on the soybean root growth and development at seedling stage. Under drought stress conditions, the activities of Superoxide dismutase (SOD), Peroxidase(POD)and Catalase(CAT)in the transgenic strains with an overexpression of the GmXTH1 gene were significantly increased, and the root activity, leaf relative water content and total chlorophyll content were ranked in order of OEAs, CK, and IEAs. In conclusion, GmXHT1 plays an important role in the growth of soybean root at seedling stage. Overexpression of GmXTH1 gene can promote root development of soybean seedling. The results of activities of protective enzymes (SOD, POD, CAT), root activity, leaf relative water content and total chlorophyll content under drought stress indicated that transgenic strains OEA1 and OEA3 with overexpressing GmXTH1 gene were resistant to drought stress, suggesting that GmXTH1 may play a positive role in responding to drought stress at soybean seedling stage.

genetics↗
bioRxiv2022

Cohort-mean measured macromolecules lead to more robust linear-combination modeling than subject-specific or parameterized ones

Expert consensus recommends linear-combination modeling (LCM) of 1H MR spectra with sequence-specific simulated metabolite basis function and experimentally derived macromolecular (MM) basis functions. Measured MM basis functions have been derived from metabolite-nulled spectra averaged across a small cohort. The use of subject-specific instead of cohort-averaged measured MM basis functions has not been studied. Furthermore, measured MM basis functions are not widely available to non-expert users, who commonly rely on parameterized MM signals internally simulated by LCM software. To investigate the impact of the choice of MM modeling, this study, therefore, compares metabolite level estimates between different MM modeling strategies (cohort-mean measured; subject-specific measured; parameterized) in a lifespan cohort and characterizes its impact on metabolite-age associations. 100 conventional (TE = 30 ms) and metabolite-nulled (TI = 650 ms) PRESS datasets, acquired from the medial parietal lobe in a lifespan cohort (20-70 years of age), were analyzed in Osprey. Short-TE spectra were modeled in Osprey using six different strategies to consider the macromolecular baseline. Fully tissue- and relaxation-corrected metabolite levels were compared between MM strategies. Model performance was evaluated by model residuals, the Akaike information criterion (AIC), and the impact on metabolite-age associations. The choice of MM strategy had a significant impact on the mean metabolite level estimates and no major impact on variance. Correlation analysis revealed moderate-to-strong agreement between different MM strategies (r > 0.6). The lowest relative model residuals and AIC values were found for the cohort-mean measured MM. Metabolite-age associations were consistently found for two major singlet signals (tCr, tCho) for all MM strategies, however, findings for highly J-coupled metabolites it was depended on the MM strategy. A variance partition analysis indicated that up to 44% of the total variance was related to the choice of MM strategy. Additionally, the variance partition analysis reproduced the metabolite-age association for tCr and tCho found in the simpler correlation analysis. In summary, the inclusion of a single high-SNR MM basis function (cohort-mean) leads to more robust metabolite estimation (lower model residuals and AIC values) compared to MM strategies with more degrees of freedom (Gaussian parametrization) or subject-specific MM information. Integration of multiple LCM analyses into a single statistical model potentially improves the robustness in the detection of underlying effects (e.g. metabolite vs age), reduces algorithm-based bias, and estimates algorithm-related variance.

neuroscience↗
bioRxiv2022

Nitrate-dependent salt tolerance mediated by OsNLP4-OsMADS27 module

Salt stress is a major constraint of plant growth and yield. Nitrogen (N) fertilizers are known to alleviate salt stress. However, the underlying molecular mechanisms remain unclear. Here we show that OsNLP4-OsMADS27 module controls nitrate-dependent salt tolerance in rice. The expression of OsMADS27 is specifically induced by nitrate. The OsMADS27 knockout mutants are more sensitive to salt stress than the wild type, whereas the OsMADS27 overexpression lines are more tolerant. Transcriptomic analyses revealed that OsMADS27 controls the expression of a number of known stress-responsive genes as well as those involved in ion homeostasis and antioxidation. We demonstrated that OsMADS27 directly binds to the promoter of OsHKT1.1 and OsSPL7 to regulate their expression. Notably, OsMADS27-mediated salt tolerance is nitrate-dependent and positively correlated with nitrate concentration. We further showed that OsNLP4, a nitrate-responsive key regulator in N metabolism and N use efficiency, positively regulates the expression of OsMADS27 by directly binding to the nitrate-responsive cis-element in its promoter, thereby transmitting the nitrate signal to OsMADS27 and conferring its nitrate dependence. Our results reveal the role of nitrate-responsive OsNLP4-OsMADS27 module and its downstream target genes in salt tolerance, filling the gap in the molecular mechanism of nitrate-dependent salt tolerance of rice. Moreover, OsMADS27 overexpression increased grain yield under salt stress in presence of sufficient nitrate, indicating that OsMADS27 is a promising candidate for the improvement of salt tolerance in rice.

plant biology↗