Biology subjects

Li, S.

Publications and source records attributed to Li, S..

At least 1,027 records · Page 57Linked to original sources

bioRxiv2021

Rice NIN-LIKE PROTEIN 3 plays a significant role in nitrogen use efficiency and grain yield under nitrate-sufficient conditions

Nitrogen (N) is an essential macronutrient for crop growth and yield, but excessive application of N fertilizer has caused serious environmental pollution and greatly increased the cost of agricultural production. One of the effective and economical solutions to this dilemma is to improve the N use efficiency (NUE) of crops. Although some components involved in regulating NUE have been identified, the underlying molecular mechanism remains largely elusive in rice. Here we report that the OsNLP3 (NIN-like protein 3) is an important regulator in NUE and grain yield under nitrate-sufficient conditions. Both NUE and grain yield were significantly improved by enhanced OsNLP3 expression in the field, but reduced in osnlp3 mutants. The expression of OsNLP3 responds to both nitrate and ammonium, while OsNLP3 nuclear retention is only induced by nitrate, not by ammonium. OsNLP3 regulates the expression of a set of genes involved in N transport and assimilation by directly binding to the nitrate-responsive cis-element in the promoters of these genes. Our study demonstrates that OsNLP3 is significant for the regulation of NUE and grain yield, particularly in nitrate-rich conditions, thus providing a candidate for improving NUE and grain yield in rice.

plant biology↗

bioRxiv2021

Constructing An Adult Orofacial Premotor Atlas In Allen Mouse CCF

Premotor circuits in the brainstem control pools of orofacial motoneurons to execute essential functions such as drinking, eating, breathing, and in rodent, whisking. Previous transsynaptic tracing studies only mapped orofacial premotor circuits in neonatal mice but the adult circuits remain unknown due to technical difficulties. Here we developed a three-step monosynaptic transsynaptic tracing strategy to identify premotor neurons controlling whisker, tongue protrusion, and jaw-closing muscles in the adult. We registered these different groups of premotor neurons onto the Allen mouse brain common coordinate framework (CCF) and consequently generated a combined 3D orofacial premotor atlas, revealing unique spatial organizations of distinct premotor circuits. We also uncovered premotor neurons simultaneously innervating multiple motor nuclei and, thus, likely coordinating different muscles involved in the same orofacial behaviors. Our method for tracing adult premotor circuits and registering to Allen CCF is generally applicable and should facilitate the investigations of motor controls of diverse behaviors.

neuroscience↗

bioRxiv2021

Identifying gene regulatory networks of senescence in postharvest broccoli (Brassica oleracea)

The facts of postharvest food loss and waste and the resulting consequences affect us in many ways, ranging from important economic and social issues to lasting and detrimental environmental problems. We are using genomic tools to understand senescence in postharvest broccoli florets when stored at room temperature or 4 {degrees}C. The RNA-sequencing approaches provide key insights into the gradual changes in transcriptome profiling in broccoli during postharvest storage. Identification of those key factors could lead to a better understanding of gene regulation of postharvest senescence. Those genes could serve as freshness-indicators that have the potential to mediate senescence and to generate germplasm for breeding new varieties with longer shelf-life in Brassica vegetables. Such a tool would also allow a new level of postharvest logistics based on physiological age, supporting improved availability of high-quality, nutritious, fresh vegetables and fruits. One sentence summaryA gene regulatory network modulates senescence in postharvest broccoli florets

genomics↗

bioRxiv2021

Mesenchymal stem cells carry and transport clusters of cancer cells

Cell clusters that collectively migrate from primary tumors appear to be far more potent in forming distant metastases than single cancer cells. A better understanding of collective cell migration phenomenon and the involvement of different cell types during this process is needed. Here, we utilize a micropatterned surface composed of a thousand of low-adhesive microwells to screen motility of spheroids containing different cell types by analyzing their ability to move from the bottom to the top of the microwells. Mesenchymal stem cells (MSCs) spheroid migration was efficient in contrast to cancer cell only spheroids. In spheroids with both cell types mixed together, MSCs were able to carry the low-motile cancer cells during migration. As the percentage of MSCs increased in the spheroids, more migrating spheroids were detected. Extracellular vesicles secreted by MSCs also contributed to the pro-migratory effect exerted by MSCs. However, the transport of cancer cells was more efficient when MSCs were physically present in the cluster. Similar results were obtained when cell clusters were encapsulated within a micropatterned hydrogel, where collective migration was guided by micropatterned matrix stiffness. These results suggest that stromal cells facilitate the migration of cancer cell clusters, which is contrary to the general belief that malignant cells metastasize independently. SignificanceDuring metastasis, tumor cells may migrate as a cluster, which exhibit higher metastatic capacity compared to single cells. However, whether and how non-cancer cells contained in tumor cluster regulate its migration is not clear. Here, we utilize two unique approaches to study collective tumor cell migration in vitro: first, in low-adhesive microwells and second, in micropatterned hydrogels to analyze migration in 3D microenvironment. Our results indicate that MSCs in tumor cell clusters could play an important role in the dissemination of cancer cells by actively transporting low-motile cancer cells. In addition, MSC-released paracrine factors also increase the motility of tumor cells. These findings reveal a new mechanism of cancer cell migration and may lead to new approaches to suppress metastases.

bioengineering↗

bioRxiv2021

Methylation of KRAS at lysine 182 and 184 by SETD7 promotes KRAS degradation

Oncogenic KRAS mutations are considered to be a key driver for initiation and progression in non-small-cell lung cancer (NSCLC). However, how post-translational modifications (PTMs) of KRAS, especially methylation, modify KRAS activity and downstream signals remain largely unclear. Here, we showed that SET domain containing histone lysine methyltransferase 7 (SETD7) interacts with KRAS and methylates KRAS at lysine 182 and 184. SETD7-mediated methylation of KRAS led to degradation of KRAS and attenuation of the RAS/MEK/ERK signaling cascade, endowing SETD7 with a potent tumor-suppressive role in NSCLC, both in vitro and in vivo. Mechanistically, RABGEF1, a ubiquitin E3 ligase of KRAS, was recruited and promoted KRAS degradation in a K182/K184 methylation-dependent manner. Notably, low SETD7 or RABGEF1 expression was associated with poor prognosis in lung adenocarcinoma patients. Taken together, our results establish a novel connection between lysine methylation and KRAS protein stability, in addition to elucidating a tumor-suppressive function of SETD7 that operates via modulation of oncogenic RAS signaling.

cancer biology↗

bioRxiv2021

Strain dynamics of specific contaminant bacteria modulate the performance of ethanol biorefineries

Bioethanol is a viable alternative for fossil fuels, and its use has lowered CO2 emissions by over 500 million tonnes in Brazil alone by replacing more than 40% of the national gasoline consumption. However, contaminant bacteria reduce yields during fermentation. Our understanding of these contaminants is limited to targeted studies, and the interplay of the microbial community and its impact on fermentation efficiency remains poorly understood. Comprehensive surveying and longitudinal analysis using shotgun metagenomics of two major biorefineries over a production season revealed similar patterns in microbial community structure and dynamics throughout the entire fermentation system. Strain resolution metagenomics identified specific Lactobacillus fermentum strains as strongly associated with poor industrial performance and laboratory-scale fermentations revealed yield reductions of up to 4.63{+/-}1.35% depending on the specific contaminating strains. Selective removal of these strains could reduce emissions from the bioethanol industry by more than 2x106 tonnes per year. Using the large-scale Brazilian ethanol fermentations as a model system for studying microbiome-phenotype relationships this study further demonstrates how high-resolution metagenomics can identify culprits of large scale industrial biomanufacturing.

microbiology↗

bioRxiv2021

Mitochondriomics reveals the underlying neuoprotective mechanism of TrkB receptor agonist R13 in the 5xFAD mice

Decreased energy metabolism and mitochondrial biogenesis defects are implicated in the pathogenesis of Alzheimers disease (AD). In present study, mitochondriomics analysis revealed significant effects of R13, a prodrug of 7,8-dihydroxyflavone, on mitochondrial protein expression profile, including the proteins related to the biological processes: fatty acid beta-oxidation, fatty acid metabolic process, mitochondrial electron transport, and mitochondrial respiratory chain. Cluster analysis of mitochondriomics demonstrated that R13 promoted mitochondrial oxidative phosphorylation (OXPHOS). The functional analysis showed that R13 increased ATP levels and enhanced OXPHOS including complex I, complex II, complex III and complex IV. R13 treatment increased mitochondrial biogenesis by regulating the levels of p-AMPK, p-CREB, PGC-1, NRF1 and TFAM as a consequence of activation of TrkB receptor in the 5xFAD mice. Finally, R13 significantly reduced the levels of tau phosphorylation and A{beta} plaque. Our data suggest that R13 may be used for treating AD via enhancing mitochondrial biogenesis and metabolism.

pharmacology and toxicology↗

bioRxiv2021

Neptune: An environment for the delivery of genomic medicine

PurposeGenomic medicine holds great promise for improving healthcare, but integrating searchable and actionable genetic data into electronic health records remains a challenge. Here, we describe Neptune, a system for managing the interaction between a clinical laboratory and an electronic health record system. MethodsWe developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis and EHR integration. ResultsNeptune enabled the analysis of data for generation of and delivery to EHR systems of over 15,000 clinical genomic reports. These projects demanded customizable clinical reports that contained a variety of genetic data types including SNVs, CNVs, pharmacogenomics and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. ConclusionsMethods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open and available at https://gitlab.com/bcm-hgsc/neptune.

bioinformatics↗

bioRxiv2021

dSCOPE: a software to detect sequences critical for liquid-liquid phase separation

Membrane based cells are the fundamental structure and function units of organisms, while evidences were increasing that liquid-liquid phase separation (LLPS) is associated with the formation of membraneless organelles, such as P-bodies, nucleoli and stress granules. Many studies have been undertaken to explore the functions of protein phase separation, but these studies lacked an effective tool to identify the sequence segments that critical for LLPS (SCOPEs). In this study, we presented a novel software called dSCOPE (http://dscope.omicsbio.info) to predict the SCOPEs. To develop the predictor, we curated experimentally identified sequence segments that can drive LLPS from published literature. Then sliding sequence window based physiological, biochemical, structural and coding features were integrated by random forest algorithm to perform prediction. Through rigorous evaluation, dSCOPE was demonstrated to achieve satisfactory performance. Furthermore, large-scale analysis of human proteome based on dSCOPE showed that the predicted SCOPEs enriched various protein post-translational modifications and cancer mutations, and the proteins which contain predicted SCOPEs enriched critical cellular signaling pathways. Taken together, dSCOPE precisely predicted the protein sequence segments critical for LLPS, with various helpful information visualized in the webserver to facilitate LLPS related research.

bioinformatics↗

bioRxiv2021

Analysis of Spleen Histopathology, Splenocyte composition and Hematological Parameters in Mice Infected with Plasmodium berghei K173

Malaria is a fatal disease that presents clinically as a continuum of symptoms and severity, which are determined by complex host-parasite interactions. Clearance of infection is believed to be accomplished by the spleen and mononuclear phagocytic system (MPS), both in the presence and absence of artemisinin treatment. The spleen filters infected RBCs from circulation through immune-mediated recognition of the infected RBCs followed by phagocytosis. Using different strains of mice infected with P. berghei K173 (PbK173), the mechanisms leading to splenomegaly, histopathology, splenocyte activation and proliferation, and their relationship to control of parasitemia and host mortality were examined. Survival time of mice infected with PbK173 varied, although the infection was uniformly lethal. Mice of the C57BL/6 strain were the most resistant, while mice of the strain ICR were the most susceptible. BALB/c and KM mice were intermediate. In the course of PbK173 infection, both strains of mice experienced significant splenomegaly. Parasites were observed in the red pulp at 3 days post infection in all animals. All spleens retained late trophozoite stages as well as a fraction of earlier ring-stage parasites. The percentages of macrophages in infected C57BL/6 and KM mice were higher than uninfected mice on 8 dpi. Spleens of infected ICR and KM mice exhibited structural disorganization and remodeling. Furthermore, parasitemia was significantly higher in KM versus C57BL/6 mice at 8 dpi. The percentages of macrophages in ICR infected mice were lower than uninfected mice, and the parasitemia was higher than other strains. The results presented here demonstrate the rate of splenic mechanical filtration and the splenic macrophages likely contribute to an individuals total parasite burden. This in turn can influence the pathogenesis of malaria. Finally, different genetic backgrounds of mice have different splenic mechanisms for controlling malaria infection.

microbiology↗

bioRxiv2021

Dual expression of Atoh1 and Ikzf2 promotes transformation of adult cochlear supporting cells into outer hair cells

Mammalian cochlear outer hair cells (OHCs) are essential for hearing. OHC degeneration causes severe hearing impairment. Previous attempts of regenerating new OHCs from cochlear supporting cells (SCs) had yielded cells lacking Prestin, a key motor protein for OHC function. Thus, regeneration of Prestin+ OHCs remains a challenge for repairing OHC damage in vivo. Here, we reported that successful in vivo conversion of adult cochlear SCs into Prestin+ OHC-like cells could be achieved by simultaneous expression of Atoh1 and Ikzf2, two key transcriptional factors necessary for OHC development. New OHC-like cells exhibited upregulation of hundreds of OHC genes and downregulation of SC genes. Single cell transcriptomic analysis demonstrated that the differentiation status of these OHC-like cells was much more advanced than previously achieved. Thus, we have established an efficient approach to promote regeneration of Prestin+ OHCs and paved the way for repairing damaged cochlea in vivo via transdifferentiation of SCs.

developmental biology↗

bioRxiv2021

Generation and characterization of a laforin nanobody inhibitor

Mutations in the gene encoding the glycogen phosphatase laforin result in the fatal childhood epilepsy Lafora disease (LD). A cellular hallmark of LD is cytoplasmic, hyper-phosphorylated, glycogen-like aggregates called Lafora bodies (LBs) that form in nearly all tissues and drive disease progression. Additional tools are needed to define the cellular function of laforin, understand the pathological role of laforin in LD, and determine the role of glycogen phosphate in glycogen metabolism. We present the generation and characterization of laforin nanobodies. We identify multiple classes of specific laforin-binding nanobodies and determine their binding epitopes using hydrogen deuterium exchange (HDX) mass spectrometry. Further, one family of nanobodies is identified that serves as an inhibitor of laforin catalytic activity. The laforin nanobodies are an important set of tools that open new avenues to define unresolved questions.

biochemistry↗

bioRxiv2021

Function-structure Coupling：White matter fMRI hyper-activation associates with structural integrity reductions in schizophrenia

BackgroundWhite matter (WM) microstructure deficit may be an underlying factor in the brain dysconnectivity hypothesis of schizophrenia using diffusion tensor imaging (DTI). However, WM dysfunction is unclear in schizophrenia. This study aimed to investigate the association between structural deficits and functional disturbances in major WM tracts in schizophrenia. MethodsUsing functional magnetic resonance imaging (fMRI) and DTI, we developed the skeleton-based white matter functional analysis, which could achieve voxel-wise function-structure coupling by projecting the fMRI signals onto a skeleton in WM. We measured the fractional anisotropy (FA) and WM low-frequency oscillation activation and their couplings in ninety-three schizophrenia patients and 122 healthy controls (HCs). An independent open database (62 schizophrenia patients and 71 HCs) was used to test the reproducibility. Finally, associations between WM activations and five behaviour assessment categories (cognition, emotion, motor, personality and sensory) were examined. ResultsThis study revealed a reversed pattern of structure and function in frontotemporal tracts, as follows. (1) WM hyper-activation was associated with reduced FA in schizophrenia. (2) The function-structure association was positive in healthy controls but negative in schizophrenia patients. Furthermore, function-structure dissociation was exacerbated by long illness duration and severe negative symptoms. (3) WM activations were significantly related to cognition and emotion. ConclusionsThis study indicated function-structure dys-coupling, with higher functional activation and reduced structural integration in frontotemporal WM, which may reflect a potential mechanism in WM neuropathologic processing of schizophrenia.

neuroscience↗

bioRxiv2021

Computational and experimental approaches to controlling bacterial microcompartment assembly

Bacterial microcompartments compartmentalize the enzymes that aid chemical and energy production in many bacterial species. These protein organelles are found in various bacterial phyla and are postulated to help many of these organisms survive in hostile environments such as the gut of their hosts. Metabolic engineers are interested in repurposing these organelles for non-native functions. Here, we use computational, theoretical and experimental approaches to determine mechanisms that effectively control microcompartment self-assembly. As a model system, we find via multiscale modeling and mutagenesis studies, the interactions responsible for the binding of hexamer-forming proteins propanediol utilization bacterial microcompartments from Salmonella and establish conditions that form various morphologies. We determine how the changes in the microcompartment hexamer protein preferred angles and interaction strengths can modify the assembled morphologies including the naturally occurring polyhedral microcompartment shape, as well as other extended shapes or quasi-closed shapes. We demonstrate experimentally that such altered strengths and angles are achieved via amino acid mutations. A thermodynamic model that agrees with the coarse-grained simulations provides guidelines to design microcompartments. These findings yield insight in controlled protein assembly and provide principles for assembling microcompartments for biochemical or energy applications as nanoreactors.

biophysics↗

bioRxiv2021

Myoglobin primary structure reveals multiple convergent transitions to semi-aquatic life in the world smallest mammalian divers

Identifying the phylogenomic underpinnings of specialized phenotypes that fueled transitions into new adaptive zones is central to evolutionary biology but is often confounded by a fragmentary fossil record, morphological convergence, and unresolved phylogenetic relationships. The speciose mammalian order Eulipotyphla (e.g., moles, shrews, hedgehogs, solenodons) combines an unusual diversity of semi-aquatic, semi-fossorial, and fossorial forms that arose from terrestrial forbearers, yet the ecomorphological pathways leading to these lifestyles have been disputed for a century and more, calling for novel approaches. Here we resolve previously intractable eulipotyphlan intra-family relationships and establish the net surface charge of the oxygen-storing muscle protein myoglobin-readily determined from its primary structure-as a molecular signature to trace ancient lifestyle transitions based on protein sequence alone. Our analyses confidently resolve fossorial habits having evolved twice in talpid moles and reveal five independent origins of a semi-aquatic lifestyle in the order housing the worlds smallest endothermic divers.

evolutionary biology↗

bioRxiv2021

MoTSE: an interpretable task similarity estimator for small molecular property prediction tasks

Understanding the molecular properties (e.g., physical, chemical or physiological characteristics and biological activities) of small molecules plays essential roles in biomedical researches. The accumulating amount of datasets has enabled the development of data-driven computational methods, especially the machine learning based methods, to address the molecular property prediction tasks. Due to the high cost of obtaining experimental labels, the datasets of individual tasks generally contain limited amount of data, which inspired the application of transfer learning to boost the performance of the molecular property prediction tasks. Our analyses revealed that simultaneously considering similar tasks, rather than randomly chosen ones, can significantly improve the performance of transfer learning in this field. To provide accurate estimation of task similarity, we proposed an effective and interpretable computational tool, named Molecular Tasks Similarity Estimator (MoTSE). By extracting task-related local and global knowledge from pretrained graph neural networks (GNNs), MoTSE projects individual tasks into a latent space and measures the distance between the embedded vectors to derive the task similarity estimation and thus enhance the molecular prediction results. We have validated that the task similarity estimated by MoTSE can serve as a useful guidance to design a more accurate transfer learning strategy for molecular property prediction. Experimental results showed that such a strategy greatly outperformed baseline methods including training from scratch and multitask learning. Moreover, MoTSE can provide interpretability for the estimated task similarity, through visualizing the important loci in the molecules attributed by the attribution method employed in MoTSE. In summary, MoTSE can provide an accurate method for estimating the molecular property task similarity for effective transfer learning, with good interpretability for the learned chemical or biological insights underlying the intrinsic principles of the task similarity.

bioinformatics↗

bioRxiv2021

Multi-omics analysis of glucose-mediated signaling by a moonlighting Gβ protein Asc1/RACK1

G proteins were originally discovered through efforts to understand the effects of hormones, such as glucagon and epinephrine, on glucose metabolism. On the other hand, many cellular metabolites, including glucose, serve as ligands for G protein-coupled receptors. Here we investigate the consequences of glucose-mediated receptor signaling, and in particular the role of a G subunit Gpa2 and a non-canonical G{beta} subunit, known as Asc1 in yeast and RACK1 in animals. Asc1/RACK1 is of particular interest because it has multiple, seemingly unrelated, functions in the cell. The existence of such "moonlighting" operations has complicated the determination of phenotype from genotype. Through a comparative analysis of individual gene deletion mutants, and by integrating transcriptomics and metabolomics measurements, we have determined the relative contributions of the G and G{beta} protein subunits to glucose-initiated processes in yeast. We determined that Gpa2 is primarily involved in regulating sugar metabolism while Asc1 is primarily involved in amino acid metabolism. Both proteins are involved in regulating purine metabolism. Of the two subunits, Gpa2 regulates a greater number of gene transcripts and was particularly important in determining the amplitude of response to glucose addition. We conclude that the two G protein subunits regulate distinct but complementary processes downstream of the glucose-sensing receptor, as well as processes that lead ultimately to changes in cell growth and metabolism. AUTHOR SUMMARYDespite the societal importance of glucose fermentation in yeast, the mechanisms by which these cells detect and respond to glucose have remained obscure. Glucose detection requires a cell surface receptor coupled to a G protein that is comprised of two subunits, rather than the more typical heterotrimer: an subunit Gpa2 and the {beta} subunit Asc1 (or RACK1 in humans). Asc1/RACK1 also serves as a subunit of the ribosome, where it regulates the synthesis of proteins involved in glucose fermentation. This manuscript uses global metabolomics and transcriptomics to demonstrate the distinct roles of each G protein subunit in transmitting the glucose signal. Whereas Gpa2 is primarily involved in the metabolism of sugars, Asc1/RACK1 contributes to production of amino acids necessary for protein synthesis and cell division. These findings reveal the initial steps of glucose signaling and several unique and complementary functions of the G protein subunits. More broadly, the integrated approach used here is likely to guide efforts to determine the topology of complex G protein and metabolic signaling networks in humans.

genomics↗

bioRxiv2021

Correcting statistical bias in correlation-based kinship estimators

Accurate estimate of relatedness is important for genetic data analyses, such as association mapping and heritability estimation based on data collected from genome-wide association studies. Inaccurate relatedness estimates may lead to spurious associations and biased heritability estimations. Individual-level genotype data are often used to estimate kinship coefficient between individuals. The commonly used sample correlation-based genomic relationship matrix (scGRM) method estimates kinship coefficient by calculating the average sample correlation coefficient among all single nucleotide polymorphisms (SNPs), where the observed allele frequencies are used to calculate both the expectations and variances of genotypes. Although this method is widely used, a substantial proportion of estimated kinship coefficients are negative, which are difficult to interpret. In this paper, through mathematical derivation, we show that there indeed exists bias in the estimated kinship coefficient using the scGRM method when the observed allele frequencies are regarded as true frequencies. This leads to negative bias for the average estimate of kinship among all individuals, which explains the estimated negative kinship coefficients. Based on this observation, we propose an unbiased estimation method, UKin, which can reduce the bias. We justify our improved method with rigorous mathematical proof. We have conducted simulations as well as two real data analyses to demonstrate that both bias and root mean square error in kinship coefficient estimation can be reduced by using UKin. Further simulations indicate that the power in association mapping can also be improved by using our unbiased kinship estimates to adjust for cryptic relatedness. Author summaryInference of relatedness plays an important role in genetic data analysis. Many methods have been proposed to estimate kinship coefficients, including the commonly used genomic relationship matrix method. However, a substantial proportion of the kinship coefficients estimated by this method are negative, which is difficult to interpret. In this paper, through mathematical derivation, we show that there indeed exists a negative bias in this approach. To correct for this bias, we propose a new kinship coefficient estimation method, UKin, which is unbiased without requiring extra genetic information nor added computational complexity. The better performance of UKin in reducing bias and root mean squared error is demonstrated through theory, simulations and analysis of data from the young-onset breast cancer and familial intracranial aneurysm studies.

genetics↗