Biology subjects

Wang, Q.

Publications and source records attributed to Wang, Q..

At least 613 records · Page 34Linked to original sources

bioRxiv2021

Deep Learning-Based Brain Transcriptomic Signatures Associated with the Neuropathological and Clinical Severity of Alzheimer's Disease

Brain tissue gene expression from donors with and without Alzheimers disease (AD) have been used to help inform the molecular changes associated with the development and potential treatment of this disorder. Here, we use a deep learning method to analyze RNA-seq data from 1,114 brain donors from the AMP-AD consortium to characterize post-mortem brain transcriptome signatures associated with amyloid-{beta} plaque, tau neurofibrillary tangles, and clinical severity in multiple AD dementia populations. Starting from the cross-sectional data in the ROSMAP cohort (n = 634), a deep learning framework was built to obtain a trajectory that mirrors AD progression. A severity index (SI) was defined to quantitatively measure the progression based on the trajectory. Network analysis was then carried out to identify key gene (index gene) modules present in the model underlying the progression. Within this dataset, SIs were found to be very closely correlated with all AD neuropathology biomarkers (R [~] 0.5, p < 1e-11) and global cognitive function (R = -0.68, p < 2.2e-16). We then applied the model to additional transcriptomic datasets from different brain regions (MAYO, n = 266; MSBB, n = 214), and observed that the model remained significantly predictive (p < 1e-3) of neuropathology and clinical severity. The index genes that significantly contributed to the model were integrated with AD co-expression regulatory networks, resolving four discrete gene modules that are implicated in vascular and metabolic dysfunction in different cell types respectively. Our work demonstrates the generalizability of this signature to frontal and temporal cortex measurements and additional brain donors with AD, other age-related neurological disorders and controls; and revealed the transcriptomic network modules contribute to neuropathological and clinical disease severity. This study illustrates the promise of using deep learning methods to analyze heterogeneous omics data and discover potentially targetable molecular networks that can inform the development, treatment and prevention of neurodegenerative diseases like AD.

genomics↗

bioRxiv2021

Risk of Bias Assessment in Preclinical Literature using Natural Language Processing

ObjectiveWe sought to apply natural language processing to the task of automatic risk of bias assessment in preclinical literature, which could speed the process of systematic review, provide information to guide research improvement activity, and support translation from preclinical to clinical research. Materials and MethodsWe use 7,840 full-text publications describing animal experiments with yes/no annotations for five risk of bias items. We implement a series of models including baselines (support vector machine, logistic regression, random forest), neural models (convolutional neural network, recurrent neural network with attention, hierarchical neural network) and models using BERT with two strategies (document chunk pooling and sentence extraction). We tune hyperparameters to obtain the highest F1 scores for each risk of bias item on the validation set and compare evaluation results on the test set to our previous regular expression approach. ResultsThe F1 scores of best models on test set are 82.0% for random allocation, 81.6% for blinded assessment of outcome, 82.6% for conflict of interests, 91.4% for compliance with animal welfare regulations and 46.6% for reporting animals excluded from analysis. Our models significantly outperform regular expressions for four risk of bias items. ConclusionFor random allocation, blinded assessment of outcome, conflict of interests and animal exclusions, neural models achieve good performance, and for animal welfare regulations, BERT model with sentence extraction strategy works better.

bioinformatics↗

bioRxiv2021

Modelling Porcine NAFLD by Deletion of Leptin and defining the role of AMPK in hepatic fibrosis

Liver fibrosis occurs during chronic liver disease. Advanced liver fibrosis results in cirrhosis, liver failure and often requires liver transplantation. However, due to the lack of human models, mechanisms underlining the pathogenesis of liver fibrosis remain unclear. Recent studies implicated a central role of deranged lipid metabolism in its pathogenesis. In this study, we generated LEPTIN-deficient (LEPTIN-/-) pigs using zinc finger nuclease technology to investigate the mechanisms of liver fibrosis associated with obesity. The LEPTIN-/- pigs showed increased body fat and significant insulin resistance by 12 months of age. To resemble non-alcoholic fatty liver disease (NAFLD) patients, LEPTIN-/- pig developed the phenotypic features of fatty liver, non-alcoholic steatohepatitis (NASH) and hepatic fibrosis with age. Meanwhile, LEPTIN absence reduced phosphorylation of JAK2-STAT3 and AMPK. The alteration of JAK2-STAT3 enhanced fatty acid {beta}-oxidation, whereas inactivation of AMPK led to mitochondrial autophagy, and both contributed to increased oxidative stress in hepatocytes. Although Leptin deletion in the rat liver altered JAK2-STAT3 phosphorylation, it activated the AMPK pathway and prevented liver fibrogenesis in contrast with the LEPTIN-/- pig. To our knowledge, the LEPTIN-/- pig provides the first model recapitulating the full pathogenesis of NAFLD and its progression toward liver fibrosis. The activity of AMPK signaling pathway suggests a potential target for development of new strategies for the diagnosis and treatment of NAFLD.

developmental biology↗

bioRxiv2021

Molecular classification reveals the diverse genetic features and prognosis of gastric cancer: a multi-omics consensus ensemble clustering

BackgroundGastric cancer (GC) is the fifth most common tumor around the world, it is necessary to reveal novel molecular subtypes to guide the selection of patients who may benefit from specific target therapy. MethodsMulti-omics data, including RNA-sequence of transcriptomics (mRNA, LncRNA, miRNA), DNA methylation and gene mutation of TCGA-STAD cohort was used for the clustering. Ten classical clustering algorithms were applied to recognize patients with different molecular features via the R package "MOVICS". The activated signaling pathways were evaluated using the single-sample gene set enrichment analysis. The difference distribution of gene mutations, copy number alterations and tumor mutation burden was compared, and potential response to immunotherapy and chemotherapy was assessed as well. ResultsTwo molecular subtypes (CS1 and CS2) were recognized by ten clustering algorithms with further consensus ensembles. Patients in the CS1 group were found to contain a shorter average overall survival time (28.5 vs. 68.9 months, P = 0.016), and progression-free survival (19.0 vs. 63.9 months, P = 0.008) compared to the CS2 group. CS1 group contained more activation of extracellular associated biological process, while CS2 group displayed the activation of cell cycle associated pathways. The significantly higher total mutation numbers and neo antigens were observed in CS2 group, along with the specific mutation of TTN, MUC16 and ARID1A. Higher infiltration of immunocytes were also observed in CS2 group, reflected to the potential benefit from immunotherapy. Moreover, CS2 group also can response to 5-fluorouracil, cisplatin, and paclitaxel. The similar diverse of clinical outcome of CS1 and CS2 groups were successfully validation in external cohorts of GSE62254, GSE26253, GSE15459, and GSE84437. ConclusionNovel insight into the GC subtypes was obtained via integrative analysis of five omics data by ten clustering algorithms, which can provide the idea to the clinical target therapy based on the specific molecular features.

cancer biology↗

bioRxiv2021

Radiation-induced reprogramming drives glioma vascular transdifferentiation and tumor recurrence

Treatment-refractory glioma stem and tumor cells exhibit phenotypic plasticity driving recurrence, but the underlying molecular mechanisms remain to be elucidated. Here, we employed single-cell and whole transcriptomic analyses to discover that radiation induces a dynamic shift in functional states of glioma cells allowing for acquisition of vascular endothelial-like and pericyte-like cell phenotypes. These vascular-like cells provide a trophic niche to promote proliferation of irradiated glioma cells, and their selective depletion results in reduced tumor growth post-treatment in vivo. Mechanistically, the acquisition of vascular-like phenotype is driven by increased chromatin accessibility and H3K27 acetylation in specific vascular gene regions post-treatment. Blocking P300 histone acetyltransferase activity reverses the epigenetic changes induced by radiation, and inhibits the phenotypic transition and tumor growth. Our findings highlight an important role for P300 histone acetyltransferase in treatment-induced plasticity and opens a new therapeutic avenue for preventing glioma recurrence. SignificanceOur study demonstrates that radiation therapy promotes glioma resistance by inducing vascular-like phenotypes in GSC that, in turn, aid in proliferation of the remaining tumor cells. This phenotype switch is mediated by P300 HAT, and inhibition of this enzyme is a potential therapeutic target for preventing glioma recurrence following radiation.

cancer biology↗

bioRxiv2021

PHARP: A pig haplotype reference panel for genotype imputation

Pigs not only function as a major meat source worldwide but also are commonly used as an animal model for studying human complex traits. A large haplotype reference panel has been used to facilitate efficient phasing and imputation of relatively sparse genome-wide microarray chips and low-coverage sequencing data. Using the imputed genotypes in the downstream analysis, such as GWASs, TWASs, eQTL mapping and genomic prediction (GS), is beneficial for obtaining novel findings. However, currently, there is still a lack of publicly available and high-quality pig reference panels with large sample sizes and high diversity, which greatly limits the application of genotype imputation in pigs. In response, we built the pig Haplotype Reference Panel (PHARP) database. PHARP provides a reference panel of 2,012 pig haplotypes at 34 million SNPs constructed using whole-genome sequence data from more than 49 studies of 71 pig breeds. It also provides Web-based analytical tools that allow researchers to carry out phasing and imputation consistently and efficiently. PHARP is freely accessible at http://alphaindex.zju.edu.cn/PHARP/index.php. We demonstrate its applicability for pig commercial 50K SNP arrays, by accurately imputing 2.6 billion genotypes at a concordance rate value of 0.971 in 81 Large White pigs (~ 17x sequencing coverage). We also applied our reference panel to impute the low-density SNP chip into the high-density data for three GWASs and found novel significantly associated SNPs that might be casual variants.

genomics↗

bioRxiv2021

Molecular basis and evolutionary cost of a novel phenotype of macrolides/lincosamides resistance in Staphylococcus haemolyticus

Staphylococcus haemolyticus (S. haemolyticus) is a coagulase-negative Staphylococcus and has become one of the primary pathogens of nosocomial infections. After a long period using the antibiotics against the infections caused by S. haemolyticus, S. haemolyticus developed several resistance phenotypes of macrolides and lincosamides. Here, we acquired four S. haemolyticus clinical isolates, of which three isolates demonstrated antibiotic resistance as reported previously, while one was resistant to both erythromycin and clindamycin without erythromycin induction. Such novel phenotype, known as constitutive Macrolides-Lincosamides-Streptogramins (MLS) resistance, was reported in other bacteria, but it was found for the first time in S. haemolyticus. To further investigate such behavior, we confirmed that the deletion of the methyltransferase ErmC upstream leader peptide was critical to cause constitutive MLS resistance based on the analysis of potential antibiotic resistance genes via whole-genome sequencing and experimental verification. In addition, we discovered that the continuous expression of ErmC may inhibit the growth of S. haemolyticus, which turned out to be the cost with no MLS pressure. Taken together, this study firstly reported the constitutive MLS resistance in S. haemolyticus, and provided new ideas for using macrolides and lincosamides in clinical treatment.

microbiology↗

bioRxiv2021

Probing DNA-protein interactions using single-molecule diffusivity contrast

Single-molecule fluorescence investigations of protein-nucleic acid interactions require robust means to identify the binding state of individual substrate molecules in real time. Here we show that diffusivity contrast, widely used in fluorescence correlation spectroscopy at the ensemble level and in single-particle tracking on individual (but slowly diffusing) species, can be used as a general readout to determine the binding state of single DNA molecules with unlabeled proteins in solution. We first describe the technical basis of drift-free single-molecule diffusivity measurements in an Anti-Brownian ELetrokinetic (ABEL) trap. We then cross-validate our method with protein-induced fluorescence enhancement (PIFE), a popular technique to detect protein binding on nucleic acid substrates with single-molecule sensitivity. We extend an existing hydrodynamic modeling framework to link measured diffusivity to particular DNA-protein structures and obtain good agreement between the measured and predicted diffusivity values. Finally, we show that combining diffusivity contrast with PIFE allows simultaneous mapping of binding stoichiometry and location on individual DNA-protein complexes, potentially enhancing single-molecule views of relevant biophysical processes.

biophysics↗

bioRxiv2021

Rare copy number variants (CNVs) and breast cancer risk

BackgroundCopy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. ResultsGene burden tests detected the strongest association for deletions in BRCA1 (P= 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P= 0.0008), ATM (P= 0.002) and BRCA2 (P= 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. ConclusionsThis is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.

genetics↗

bioRxiv2021

Broad neutralization against SARS-CoV-2 variants induced by a modified B.1.351 protein-based COVID-19 vaccine candidate

Beginning in late 2020, the emergence and spread of multiple variant SARS-CoV-2 strains harboring mutations which may enable immune escape necessitates the rapid evaluation of second generation COVID-19 vaccines, with the goal of inducing optimized immune responses that are broadly protective. Here we demonstrate in a mouse immunogenicity study that two doses of a modified B.1.351 spike (S)-Trimer vaccine (B.1.351 S-Trimer) candidate can induce strong humoral immune responses that can broadly neutralize both the original SARS-CoV-2 strain (Wuhan-Hu-1) and Variants of Concern (VOCs), including the UK variant (B.1.1.7), South African variant (B.1.351) and Brazil variant (P.1). Furthermore, while immunization with two doses (prime-boost) of Prototype S-Trimer vaccine (based on the original SARS-CoV-2 strain) induced lower levels of cross-reactive neutralization against the B.1.351 variant, a third dose (booster) administered with either Prototype S-Trimer or B.1.351 S-Trimer was able to increase neutralizing antibody titers against B.1.351 to levels comparable to neutralizing antibody titers against the original strain elicited by two doses of Prototype S-Trimer.

immunology↗

bioRxiv2021

CD147 antibody specifically and effectively inhibits infection and cytokine storm of SARS-CoV-2 variants

SARS-CoV-2 and its variants are raging worldwide. Unfortunately, the global vaccination is not efficient enough to attain a vaccine-based herd-immunity and yet no special and effective drug is developed to contain the spread of the disease. Previously we have identified CD147 as a novel receptor for SARS-CoV-2 infection. Here, we demonstrated that CD147 antibody effectively inhibits infection and cytokine storm caused by SARS-CoV-2 variants. In CD147KO VeroE6 cells, infections of SARS-CoV-2, its variants (B.1.1.7, B.1.351) and pseudovirus mutants (B.1.1.7, B.1.351, B.1.525, B.1.526 (S477N), B.1.526 (E484K), P.1, P.2, B.1.617.1, B.1.617.2) were decreased. Meanwhile, CD147 antibody effectively blocked the entry of variants and pseudomutants in VeroE6 cells, and inhibited the expression of cytokines. A model of SARS-CoV-2-infected hCD147 transgenic mice was constructed, which recapitulated the features of exudative diffuse alveolar damage and dynamic immune responses of COVID-19. CD147 antibody could effectively clear the virus and alveolar exudation, resolving the pneumonia. We found the elevated level of cyclophilin A (CyPA) in plasma of severe/critical cases, and identified CyPA as the most important proinflammatory intermediate causing cytokine storm. Mechanistically, spike protein of SARS-CoV-2 bound to CD147 and initiated the JAK-STAT pathway, which induced expression of CyPA. CyPA reciprocally bound to CD147, triggered MAPK pathway and consequently mediated the expression of cytokine and chemokine. In conclusion, CD147 is a critical target for SARS-CoV-2 variants and CD147 antibody is a promising drug to control the new wave of COVID-19 epidemic.

immunology↗

bioRxiv2021

Dual functions of ZmGI1 in the photoperiodic flowering pathway and salt stress responses in maize

The circadian clock perceives photoperiodic changes and initiates processes leading to floral transition. GIGANTEA (GI) primarily functions as a principal clock component that integrates environmental cues into regulation of growth and development in Arabidopsis. However, it is unclear whether ZmGIs regulate photoperiodic flowering and abiotic stress response. Here, we demonstrated that the expression of ZmGI1 depicted a typical circadian pattern and was differentially expressed under LDs and SDs in photoperiodic sensitive and insensitive maize lines. The transcription level was significantly and positively correlated with days to silking and photoperiodic sensitivity in maize. Moreover, natural variation in ZmGI1 was associated with maize photoperiod response and the fine-tuning of plant development traits. Overexpression of ZmGI1Huangzao4 induced early flowering and enhanced salt tolerance in Arabidopsis relative to the wild-type and gi mutants. ZmGI1 formed a protein complex with ZmFKF1 and acted as a positive regulator of flowering time by regulating CONSTANS transcription in the photoperiod pathway. The ZmGI1/ZmThox complex regulates oxidative stress induced by salt stress via a redox balance pathway. Over all, we have provided compelling evidence to suggest that ZmGI1 is a pleotropic gene whose expression depicts a typical circadian rhythmic pattern and regulates flowering time and confers salt stress tolerance.

developmental biology↗

bioRxiv2021

OPUS-X: An Open-Source Toolkit for Protein Torsion Angles, Secondary Structure, Solvent Accessibility, Contact Map Predictions, and 3D Folding

In this paper, we report an open-source toolkit for protein 3D structure modeling, named OPUS-X. It contains three modules: OPUS-TASS2, which predicts protein torsion angles, secondary structure and solvent accessibility; OPUS-Contact, which measures the distance and orientations information between different residue pairs; and OPUS-Fold2, which uses the constraints derived from the first two modules to guide folding. OPUS-TASS2 is an upgraded version of our previous method OPUSS-TASS (Bioinformatics 2020, 36 (20), 5021-5026). OPUS-TASS2 integrates protein global structure information and significantly outperforms OPUS-TASS. OPUS-Contact combines multiple raw co-evolutionary features with protein 1D features predicted by OPUS-TASS2, and delivers better results than the open-source state-of-the-art method trRosetta. OPUS-Fold2 is a complementary version of our previous method OPUS-Fold (J. Chem. Theory Comput. 2020, 16 (6), 3970-3976). OPUS-Fold2 is a gradient-based protein folding framework based on the differentiable energy terms in opposed to OPUS-Fold that is a sampling-based method used to deal with the non-differentiable terms. OPUS-Fold2 exhibits comparable performance to the Rosetta folding protocol in trRosetta when using identical inputs. OPUS-Fold2 is written in Python and TensorFlow2.4, which is user-friendly to any source-code level modification. The code and pre-trained models of OPUS-X can be downloaded from https://github.com/OPUS-MaLab/opus_x.

bioinformatics↗

bioRxiv2021

Discovery of novel ID2 antagonists from pharmacophore-based virtual screening as potential therapeutics for glioma

Glioma, especially the most aggressive type glioblastoma multiforme, is one of the central nervous system malignant cancer with a poor prognosis. Traditional treatments are mainly surgery combined with radiotherapy and chemotherapy, which is still not satisfactory. Therefore, it is of great clinical significance to find new therapeutic agents. Served as an inhibitor of differentiation, protein ID2 (inhibitor of DNA binding 2) plays an important role in neurogenesis, neovascularization and malignant development of gliomas. It has been shown that ID2 affects the malignant progression of gliomas through different mechanisms. In this study, a pharmacophore-based virtual screening was carried out and 16 hit compounds were purchased for pharmacological evaluations on their ID2 inhibitory activities. Based on the cytotoxicity of these small-molecule compounds, two compounds were shown to effectively inhibit the viability of glioma cells in the low micromolar range. Among them, AK-778-XXMU was chosen for further study due to its better solubility in water. A SPR assay proved the high affinity between AK-778-XXMU and ID2 protein with the KD value as 129 nM. The plausible binding mode in the biding site of ID2 was studied by molecular docking. Subsequently, the cancer-suppressing potency of the compound was characterized both in vitro and in vivo. The data demonstrated that compound AK-778-XXMU is a potent ID2 antagonist which has the potential to be developed as a therapeutic agent against glioma. HighlightsO_LITwo pharmacophores were built from the first-in-class pan-ID antagonists AGX51 C_LIO_LIA pharmacophore-based virtual screening was carried out and 16 hit compounds were purchased for pharmacological evaluations in glioma inhibition C_LIO_LICompound AK-778-XXMU was identified to be a potent ID2 antagonist in the low submicromolar range (KD: 159 nM) C_LI

cancer biology↗

bioRxiv2021

Emu: Species-Level Microbial Community Profiling for Full-Length Nanopore 16S Reads

16S rRNA based analysis is the established standard for elucidating microbial community composition. While short read 16S analyses are largely confined to genus-level resolution at best since only a portion of the gene is sequenced, full-length 16S sequences have the potential to provide species-level accuracy. However, existing taxonomic identification algorithms are not optimized for the increased read length and error rate of long-read data. Here we present Emu, a novel approach that employs an expectation-maximization (EM) algorithm to generate taxonomic abundance profiles from full-length 16S rRNA reads. Results produced from one simulated data set and two mock communities prove Emu capable of accurate microbial community profiling while obtaining fewer false positives and false negatives than alternative methods. Additionally, we illustrate a real-world application of our new software by comparing clinical sample composition estimates generated by an established whole-genome shotgun sequencing workflow to those returned by full-length 16S sequences processed with Emu.

bioinformatics↗

bioRxiv2021

WRKY33-mediated indole glucosinolate metabolic pathway confers host resistance against Alternaria brassicicola

The tryptophan (Trp)-derived plant secondary metabolites, including camalexin, 4-hydroxy-indole-3-carbonylnitrile (4OH-ICN), and indole glucosinolate (IGS), show broad-spectrum antifungal activity. However, the upstream regulators of these metabolic pathways among different plant species in response to fungus infection are rarely studied. In this study, our results revealed a positive role of WRKY33 in host resistance to Alternaria brassicicola by directly regulating the transcription of genes involved in the biosynthesis and atypical hydrolysis of IGS both in Arabidopsis and Chinese kale. Indole-3-yl-methylglucosinolate (I3G) and 4-methoxyindole-3-yl-methylglucosinolate (4MI3G) are the main components of IGS. WRKY33 induces the expression of MYB51 and CYP83B1 which promotes the biosynthesis of I3G, the precursor of 4MI3G. Moreover, it also directly activates the expression of CYP81F2, IGMT1, and IGMT2 to drive side chain modification of I3G to produce 4MI3G, which is in turn hydrolyzed by PEN2. However, Chinese kale showed a more severe symptom than Arabidopsis when infected by Alternaria brassicicola. Comparative analyses of the origin and evolution of Trp-metabolism indicate that the loss of camalexin biosynthesis in Brassica crops during evolution might attenuate the resistance of crops to Alternaria brassicicola. As a result, IGS metabolic pathway mediated by WRKY33 becomes essential for Chinese kale to deter Alternaria brassicicola. Our results highlight the differential regulation of Trp-derived camalexin and IGS biosynthetic pathways in plant immunity between Arabidopsis and Brassica crops. One-sentence SummaryPathogen-responsive WRKY33 directly regulates indole glucosinolates biosynthesis and atypical hydrolysis, conferring to host resistance to Alternaria brassicicola in Arabidopsis and Brassica crops.

plant biology↗

bioRxiv2021

Class II LBD genes ZmLBD5 and ZmLBD33 regulate gibberellin and abscisic acid biosynthesis

Lateral organ boundaries domain (LBD) proteins are plant-specific transcription factors. Class I LBD members are widely reported to be pivotal for organ development, however, the role of class II members is unknown in cereal crops. Class II LBD proteins are distinguished from class I by the lack of a Gly-Ala-Ser (GAS) peptide and leucine-zipper-like coiled-coil domain, which is thought to be essential for protein dimerization. In this study, ZmLBD5 and ZmLBD33 form homo- and hetero-dimers, like class I members. At seedling stage, ZmLBD5 promoted biomass accumulation (shoot dry weight and root dry weight), root development (root length, root number, and root volume), and organ expansion (leaf area), while ZmLBD33 repressed these processes and display a dwarf phenotype. Both ZmLBD5 and ZmLBD33 displayed negative roles in drought tolerance mainly by increasing stomatal density and stomatal aperture. RNA sequencing, gene ontology enrichment analysis, and transient luciferase expression assays indicated that ZmLBD5 and ZmLBD33 are mainly involved in the regulation of the TPS-KS-GA2ox gene module, which comprises key enzymatic genes upstream of GA and ABA biosynthesis. GA1 content increased in ZmLBD5-overexpressing seedlings, while GA3 and abscisic acid content decreased in both transgenic seedlings. Consequently, exogenous GA1 or GA3 undoubtedly rescued the dwarf phenotype of ZmLBD33-overexpressing plants, with GA1 performing better. The study of ZmLBD5 and ZmLBD33 sheds light on the function of the class II LBD gene family in maize.

plant biology↗

bioRxiv2021

Unbalanced dietary patterns contribute to the pathogenesis of precocious puberty by affecting gut microbiota and host metabolites

Precocious puberty (PP) mostly stems from endocrine disorders. However, its triggering factors, especially for the early onset of partial PP, and the associated pathogenic mechanisms remain ambiguous. In this study, a systematic analysis in the form of a questionnaire of lifestyles, gut microbiome, and serum metabolome data was carried out to examine the pathogenesis of PP in a cohort comprised of 200 girls, with or without PP. The analysis revealed substantial alterations in gut microbiota, serum metabolites, as well as lifestyle patterns in the PP group, which were characterized by an elevated abundance of {beta}-glucuronidase-producing and butyrate-producing bacteria, and excessive lipid concentration with decreased levels of organic nitrogen compounds in the serum of the participants. These differential microbes and metabolites tend to be reliable non-invasive diagnostic biomarkers aiding the early diagnosis of PP and exhibit a strong discriminative power (AUC = 0.93 and AUC = 0.97, respectively). Furthermore, the microbial biomarkers were confirmed in an independent validation cohort (n = 83, AUC = 0.85). Moreover, structural equation modeling revealed that unhealthy dietary habits were the primary contributors for the alteration of gut microbiota and serum metabolites, triggering the imbalance in the host hormones that leads to premature physical development. Our study determines a causal relationship among the gut microbiota, host metabolites, diet, and clinical characteristics of preadolescent girls who experienced early onset of PP, and formulates non-invasive diagnostic tools demonstrating excellent performance for the early detection of PP.

microbiology↗