Biology subjects

Zhang, H.

Publications and source records attributed to Zhang, H..

At least 631 records · Page 35Linked to original sources

bioRxiv2024

Defective interferon signaling in the circulating monocytes of type 2 diabetic mice

Type 2 diabetes mellitus (T2DM) is associated with poor outcome after stroke. Peripheral monocytes play a critical role in the secondary injury and recovery of damaged brain tissue after stroke, but the underlying mechanisms are largely unclear. To investigate transcriptome changes and molecular networks across monocyte subsets in response to T2DM and stroke, we performed single-cell RNA-sequencing (scRNAseq) from peripheral blood mononuclear cells and bulk RNA-sequencing from blood monocytes from four groups of adult mice, consisting of T2DM model db/db and normoglycemic control db/+ mice with or without ischemic stroke. Via scRNAseq we found that T2DM expands the monocyte population at the expense of lymphocytes, which was validated by flow cytometry. Among the monocytes, T2DM also disproportionally increased the inflammatory subsets with Ly6C+ and negative MHC class II expression (MO.6C+II-). Conversely, monocytes from control mice without stroke are enriched with steady-state classical monocyte subset of MO.6C+II+ but with the least percentage of MO.6C+II- subtype. Apart from enhancing inflammation and coagulation, enrichment analysis from both scRNAseq and bulk RNAseq revealed that T2DM specifically suppressed type-1 and type-2 interferon signaling pathways crucial for antigen presentation and the induction of ischemia tolerance. Preconditioning by lipopolysaccharide conferred neuroprotection against ischemic brain injury in db/+ but not in db/db mice and coincided with a lesser induction of brain Interferon-regulatory-factor-3 in the brains of the latter mice. Our results suggest that the increased diversity and altered transcriptome in the monocytes of T2DM mice underlie the worse stroke outcome by exacerbating secondary injury and potentiating stroke-induced immunosuppression. Significance StatementThe mechanisms involved in the detrimental diabetic effect on stroke are largely unclear. We show here, for the first time, that peripheral monocytes have disproportionally altered the subsets and changed transcriptome under diabetes and/or stroke conditions. Moreover, genes in the IFN-related signaling pathways are suppressed in the diabetic monocytes, which underscores the immunosuppression and impaired ischemic tolerance under the T2DM condition. Our data raise a possibility that malfunctioned monocytes may systemically and focally affect the host, leading to the poor outcome of diabetes in the setting of stroke. The results yield important clues to molecular mechanisms involved in the detrimental diabetic effect on stroke outcome.

neuroscience↗

bioRxiv2024

Dysfunctional S1P/S1PR1 signaling in the dentate gyrus drives vulnerability of chronic pain-related memory impairment

Memory impairment in chronic pain patients is substantial and common, and few therapeutic strategies are available. Chronic pain-related memory impairment has susceptible and unsusceptible features. Therefore, exploring the underlying mechanisms of its vulnerability is essential for developing effective treatments. Here, combining two spatial memory tests (Y-maze test and Morris water maze), we segregated chronic pain mice into memory impairment-susceptible and -unsusceptible subpopulations in a chronic neuropathic pain model induced by chronic constrictive injury of the sciatic nerve. RNA-seq analysis and gain/loss-of-function study revealed that S1P/S1PR1 signaling is a determinant for vulnerability to chronic pain-related memory impairment. Knockdown of the S1PR1 in the DG promoted a susceptible phenotype and led to structural plasticity changes of reduced excitatory synapse formation and abnormal spine morphology as observed in susceptible mice, while overexpression of the S1PR1 and pharmacological administration of S1PR1 agonist in the DG promoted an unsusceptible phenotype and prevented the occurrence of memory impairment, and rescued the morphological abnormality. Finally, GO enrichment analysis and biochemical evidence indicated that down-regulation of S1PR1 in susceptible mice may impair DG structural plasticity via interaction with actin cytoskeleton rearrangement-related signaling pathways including Itga2 and its downstream Rac1/Cdc42 signaling and Arp2/3 cascade. These results reveal a novel mechanism and provide a promising preventive and therapeutic molecular target for vulnerability to chronic pain-related memory impairment.

neuroscience↗

bioRxiv2024

Dynamic Modeling of Antibody Repertoire Reshaping in Response to Viral Infections

For many years, researchers have emphasized the production of high-affinity specific antibodies by hosts during viral infections. However, this has made it challenging for immunologists to systematically evaluate the initiation mechanisms of humoral immunity in specific immune responses. Employing mathematical modeling, we have systematically investigated the dynamic changes of the entire antibody atlas in response to exogenous antigenic stimuli, including viral infections. Our study reveals that the hosts antibody atlas is reshaped during viral infection, not through the proliferation of individual antibody types, but rather through the proliferation of antibody pools with strong binding activity. Moreover, we observe a contraction in pools of antibodies with low binding activity. We have identified the crucial role of self-antigens in maintaining antibody persistence, which can effectively explain the organisms lifelong protection against pathogens that are less prone to mutation. Using this model, we further explore the mechanisms underlying original antigenic sin and elucidate the specific practical applications of this model. This research transcends the limitations of mere mathematical parameter fitting, as we endeavor to elucidate the complex humoral immune processes using physical mechanisms as a foundation. Our work contributes to a renewed understanding of the antibody elicitation process in specific immune responses.

immunology↗

bioRxiv2024

Optimized Time-segmented Acquisition Expands Peptide and Protein Identification in TIMS-TOF Pro Mass Spectrometry

We introduce here a novel approach, termed time-segmented acquisition (Seg), to enhance the identification of peptides and proteins in trapped ion mobility spectrometry (TIMS)-Time of flight (TOF) mass spectrometry. Our method exploits the positive correlation between ion mobility values and liquid chromatography (LC) retention time to improve ion separation and resolution. By dividing the LC retention time into multiple segments and applying a segment-specific narrower ion mobility range within the TIMS tunnel, we achieved better separation and higher resolution of ion mobility. This resulted in a substantial increase in peptide identification. In comparison to conventional TIMS methods, which typically scan a static ion mobility range (either from 0.6 to 1.6 or from 0.85 to 1.3), the Seg method significantly enhances the identification of peptides, proteins and average sequence coverage per protein. These findings highlight the potential of the Seg method in expanding the capabilities of TIMS-TOF mass spectrometry, especially for peptide-focused analysis such as post-translational modifications and peptidomics.

biochemistry↗

bioRxiv2024

An anti-SARS-CoV-2 formula consisting volatile oil from TCM through inhibiting multiple targets in cultured cells

At present, coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variant virus are prevalent all over the world, taking a major toll on human lives worldwide. Oral mucosa and saliva are the high-risk routes of transmission. Inactivation of the virus in the mouth is one of the important strategies to reduce the source infectivity of the virus. However, the current preparations for inactivating oral virus are mainly aimed at ACE2 protein, and its effect needs to be improved. In this study, through literature mining, multi-target screening and other methods, we screened and optimized the volatile oil formula (Artemisiae argyi folium, Chrysanthemum morifolium, Trollii chinensis flos, Lonicerae japonicae flos) from the volatile oil of traditional Chinese medicine to inhibit the invasion and replication of SARS-CoV-2. A test using pseudotype virus with S glycoprotein confirmed that this formula could effectively bind to the S glycoprotein to prevent SARS-CoV-2 host cell entry. Molecular docking experiments showed that the m ultiple molecules in the formula might weakly bind to these targets including ACE2, cathepsin L, furin, mpro/3cl. In all, the volatile oil formula designed in this paper offers a general affordable strategy to protect patients from SARS-CoV-2 infections through debulking or minimizing transmission to others.

pharmacology and toxicology↗

bioRxiv2024

Cyclic di-GMP as an Antitoxin Regulates Bacterial Genome Stability and Antibiotic Persistence in Biofilms

Biofilms are complex bacterial communities characterized by a high persister prevalence, which contributes to chronic and relapsing infections. Historically, persister formation in biofilms has been linked to constraints imposed by their dense structures. However, we observed an elevated persister frequency accompanying the stage of cell adhesion, marking the onset of biofilm development. Subsequent mechanistic studies uncovered a comparable type of toxin-antitoxin (TA) module (TA-like system) triggered by cell adhesion, which is responsible for this elevation. In this module, the toxin HipH acts as a genotoxic deoxyribonuclease, inducing DNA double strand breaks and genome instability. While the second messenger c-di-GMP functions as the antitoxin, exerting control over HipH expression and activity. The dynamic interplay between c-di-GMP and HipH levels emerges as a crucial determinant governing genome stability and persister generation within biofilms. These findings unveil a unique TA system, where small molecules act as the antitoxin, outlining a biofilm-specific molecular mechanism influencing genome stability and antibiotic persistence, with potential implications for treating biofilm infections.

microbiology↗

bioRxiv2024

De novo pyrimidine biosynthesis inhibition synergizes with BCL-XL targeting in pancreatic cancer

Oncogenic KRAS, the genetic driver of 90% of pancreatic adenocarcinoma (PDAC), induces a metabolic rewiring characterized, in part, by dependency on de novo pyrimidine biosynthesis. Pharmacologic inhibition of dihydroorotate dehydrogenase (DHODH), an enzyme in the de novo pyrimidine synthesis pathway, delays pancreatic tumor growth in vivo; however, limited monotherapy efficacy suggests compensatory pathways and that combinatorial strategies are required for enhanced efficacy. Here, we use an integrated metabolomic, quantitative temporal proteomic and in vitro and in vivo DHODH inhibitor anchored CRISPR/Cas9 genetic screening approach to identify compensatory pathways to DHODH inhibition (DHODHi) and targets for combination strategies. We demonstrate that DHODHi alters the apoptotic regulatory proteome thereby enhancing sensitivity to inhibitors of the anti-apoptotic BCL2L1 (BCL-XL) protein. Combinatorial regimens with DHODH and BCL-XL inhibition synergistically induce apoptosis in PDAC cell lines and patient-derived PDAC organoids. In vivo DHODH inhibition with Brequinar and BCL-XL degradation with DT2216, a proteolysis targeting chimera (PROTAC), significantly inhibits the growth of PDAC tumors. Our data defines mechanisms of adaptation to DHODH inhibition and identifies a combination therapy strategy in PDAC.

cancer biology↗

bioRxiv2024

mosGraphGen: a novel tool to generate multi-omic signaling graphs to facilitate integrative and interpretable graph AI model development

Multi-omics data, i.e., genomics, epigenomics, transcriptomics, proteomics, characterize cellular complex signaling systems from multi-level and multi-view and provide a holistic view of complex cellular signaling pathways. However, it remains challenging to integrate and interpret multi-omics data for mining key disease targets and signaling pathways. Graph AI models have been widely used to analyze graph-structure datasets, and are ideal for integrative multi-omics data analysis because they can naturally integrate and represent multi-omics data as a biologically meaningful multi-level signaling graph and interpret multi-omics data via graph node and edge ranking analysis. However, it is non-trivial for graph-AI model developers to pre-analyze multi-omics data and convert the data into biologically meaningful graphs, which can be directly fed into graph-AI models. To resolve this challenge, we developed mosGraphGen (multi-omics signaling graph generator), generating Multi-omics Signaling graphs (mos-graph) of individual samples by mapping multi-omics data onto a biologically meaningful multi-level background signaling network with data normalization by aggregating measurements and aligning to the reference genome. With mosGraphGen, AI model developers can directly apply and evaluate their models using these mos-graphs. In the results, mosGraphGen was used and illustrated using two widely used multi-omics datasets of TCGA and Alzheimers disease (AD) samples. The code of mosGraphGen is open-source and publicly available via GitHub: https://github.com/FuhaiLiAiLab/mosGraphGen

systems biology↗

bioRxiv2024

Clonal expansion dictates the efficacy of mitochondrial lineage tracing in single cells

Although mitochondrial DNA (mtDNA) variants hold promise as endogenous barcodes for tracking human cell lineages, their efficacy as reliable lineage markers is hindered by the complex dynamics of mtDNA in somatic tissues. Here, we utilized computational modeling and single-cell genomics to thoroughly interrogate the origin and clonal dynamics of mtDNA lineage markers across various biological settings. Our findings revealed the majority of purported "clone informative variants (CIVs)" were pre-existing heteroplamies in the first cell instead of de novo somatic mutations during divisions. Moreover, CIVs demonstrated limited discriminatory power among different lineages during normal development; however, certain CIVs with consistently high allele frequencies proved capable of faithfully labeling cell lineages in scenarios of stringent clonal expansion. Inspired by our simulations, we introduced a lineage informative (LI) score, facilitating the identification of reliable mitochondrial lineage markers across different modalities of single-cell genomic data.

bioinformatics↗

bioRxiv2024

Intermittent theta burst stimulation (iTBS)-induced changes of resting-state brain entropy (BEN)

Intermittent theta burst stimulation (iTBS) is a novel protocol of repetitive transcranial magnetic stimulation (rTMS). While iTBS has shown better therapeutic effects for depression than conventional high-frequency rTMS (HF-rTMS), its underlying neuronal mechanism remains elusive. Brain entropy (BEN), a measure of irregularity of brain activity, has recently emerged as a novel marker of regional brain activity. Our previous studies have shown the sensitivity of BEN to depression and HF-rTMS, suggesting BEN as a sensitive tool for understanding the brain mechanism of iTBS. To assess this possibility, we calculated BEN using resting state fMRI data provided by an open dataset in OpenNeuro. Sixteen healthy participants underwent 600 pulses of iTBS applied over the left dorsolateral prefrontal cortex (L-DLPFC) at two intensities (90% and 120% of individual resting motor threshold (rMT)) on separate days. We assessed the pre-post stimulation BEN difference and its associations with neurotransmitter receptor and transporter binding maps. Our results showed that subthreshold iTBS (90% rMT) decreased striatal BEN, while suprathreshold iTBS (120% rMT) increased striatal BEN. We also found significant differences in the spatial correlation between BEN changes induced by different stimulation intensities and various neurotransmitters. These results suggest that differences in BEN caused by iTBS stimulation intensity may be related to the release of other neurotransmitters. The study underscores the significance of iTBS stimulation intensity and provides a basis for future clinical investigations to identify stimulation intensities with good therapeutic benefits.

neuroscience↗

bioRxiv2024

Quantifying uncertainty in RNA velocity

The concept of RNA velocity has made it possible to extract dynamic information from single-cell RNA sequencing data snapshots, attracting considerable attention and inspiring various extensions. Nonetheless, existing approaches lack uncertainty quantification and many adopt unrealistic assumptions or employ complex black-box models that are difficult to interpret. In this paper, we present a Bayesian hierarchical model to estimate RNA velocity, which leverages a time-dependent transcription rate and non-trivial initial conditions, allowing for well-calibrated uncertainty quantification. The proposed method is validated in a comprehensive simulation study that covers various scenarios, and benchmarked against a widely embraced and commonly recognized approach for RNA velocity on single-cell RNA sequencing data from mouse embryonic stem cells. We demonstrate that our model surpasses this widely used, state-of-the-art method, offering enhanced interpretation of cell velocity and cell orders. Additionally, it supports the estimation of a unified gene-shared latent time, providing a valuable resource for downstream analysis.

bioinformatics↗

bioRxiv2024

Interplay of condensate material properties and chromatin heterogeneity governs nuclear condensate ripening

Nuclear condensates play many important roles in chromatin functions, but how cells regulate their nucleation and growth within the complex nuclear environment is not well understood. Here, we report how condensate properties and chromatin mechanics dictate condensate growth dynamics in the nucleus. We induced condensates with distinct properties using different proteins in human cell nuclei and monitored their growth. We revealed two key physical mechanisms that underlie droplet growth: diffusion-driven or ripening-dominated growth. To explain the experimental observations, we developed a quantitative theory that uncovers the mechanical role of chromatin and condensate material properties in regulating condensate growth in a heterogeneous environment. By fitting our theory to experimental data, we find that condensate surface tension is critical in determining whether condensates undergo elastic or Ostwald ripening. Our model also predicts that chromatin heterogeneity can influence condensate nucleation and growth, which we validated by experimentally perturbing the chromatin organization and controlling condensate nucleation. By combining quantitative experimentation with theoretical modeling, our work elucidates how condensate surface tension and chromatin heterogeneity govern nuclear condensate ripening, implying that cells can control both condensate properties and the chromatin organization to regulate condensate growth in the nucleus.

biophysics↗

bioRxiv2024

Coxsackievirus group B3 regulates ASS1-mediated metabolic reprogramming and promotes macrophage inflammatory polarization in viral myocarditis

Coxsackievirus group B3 (CVB3) belongs to the genus Enteroviruses of the family Picornaviridae and is the main pathogen underlying viral myocarditis (VMC). No specific therapeutic is available for this condition. Argininosuccinate synthase 1 (ASS1) is a key enzyme in the urea cycle that converts citrulline and aspartic acid to argininosuccinate. Here, we found that CVB3 and its capsid protein VP2 inhibit the autophagic degradation of ASS1 and that CVB3 consumes citrulline to upregulate ASS1, triggers urea cycle metabolic reprogramming, then activates macrophages to develop pro-inflammatory polarization, thereby promoting the occurrence and development of VMC. Conversely, citrulline supplementation to prevent depletion can downregulate ASS1, rescue macrophage polarization, and alleviate the pathogenicity of VMC. These findings provide a new perspective on the occurrence and development of VMC, revealing ASS1 as a potential new target for the treatment of this disease. IMPORTANCEViral myocarditis (VMC) is a common and potentially life-threatening myocardial inflammatory disease, most commonly caused by CVB3 infection. So far, the pathogenesis of VMC caused by CVB3 is mainly focused on two aspects: one is the direct myocardial injury caused by a large number of viral replication in the early stage of infection, and the other is the local immune cell infiltration and inflammatory damage of the myocardium in the adaptive immune response stage. There are few studies on the early innate immunity of CVB3 infection in myocardial tissue, but the appearance of macrophages in the early stage of CVB3 infection suggests that they can play a regulatory role as early innate immune response cells in myocardial tissue. Here, we discovered a possible new mechanism of VMC caused by CVB3, revealed new drug targets for anti-CVB3 and discovered the therapeutic potential of citrulline for VMC.

microbiology↗

bioRxiv2024

Development of the overlapping network modules in the human brain

Developmental connectomic studies have shown that the modular organization of functional networks in the human brain undergoes substantial reorganization with age to support cognitive growth. However, these studies implicitly assume that each brain region belongs to one and only one specific network module, ignoring the potential spatial overlap between functional modules. How the overlapping functional modular architecture develops and whether this development is related to structural signatures remain unknown. Using longitudinal multimodal structural, functional, and diffusion MRI data from 305 children (aged 6-14 years), we investigated the development of the overlapping modular architecture of functional networks, and further explored their structural associations. Specifically, an edge-centric network model was used to identify the overlapping functional modules, and the nodal overlap in module affiliations was quantified using the entropy measure. We showed a remarkable regional inhomogeneity in module overlap in children, with higher entropy in the ventral attention, somatomotor, and subcortical networks and lower entropy in the visual and default-mode networks. Furthermore, the overlapping modules developed in a linear, spatially dissociable manner from childhood to adolescence, with significantly reduced entropy in the prefrontal cortex and putamen and increased entropy in the parietal lobules. Personalized overlapping modular patterns capture individual brain maturity as characterized by brain age. Finally, the overlapping functional modules can be significantly predicted by integrating gray matter morphology and white matter network properties. Our findings highlight the maturation of overlapping network modules and their structural substrates, thereby advancing our understanding of the principles of connectome development.

neuroscience↗

bioRxiv2024

CRISPR screens reveal convergent targeting strategies against evolutionarily distinct chemoresistance in cancer

Resistance to chemotherapy has been a major hurdle that limits therapeutic benefits for many types of cancer. Here we systematically identify genetic drivers underlying chemoresistance by performing 30 genome-scale CRISPR knockout screens for seven chemotherapeutic agents in multiple cancer cells. Chemoresistance genes vary between conditions primarily due to distinct genetic background and mechanism of action of drugs, manifesting heterogeneous and multiplexed routes towards chemoresistance. By focusing on oxaliplatin and irinotecan resistance in colorectal cancer, we unravel that evolutionarily distinct chemoresistance can share consensus vulnerabilities identified by 26 second-round CRISPR screens with druggable gene library. We further pinpoint PLK4 as a therapeutic target to overcome oxaliplatin resistance in various models via genetic ablation or pharmacological inhibition, highlighting a single-agent strategy to antagonize evolutionarily distinct chemoresistance. Our study not only provides resources and insights into the molecular basis of chemoresistance, but also proposes potential biomarkers and therapeutic strategies against such resistance.

cancer biology↗

bioRxiv2024

Plant Accessible Tissue Clearing Solvent System (PATCSOS) for 3-D Imaging of Whole Plants

Tissue clearing is a technique to make the inner structure of opaque tissue visible to achieve 3-dimensional (3-D) tissue imaging by unifying the refractive indexes of most of the cell components. Tissue clearing is widely used in animal tissue imaging, where whole body 3-D imaging has been realized. However, it has not been widely used in plant research. Most plant tissue clearing protocols have their disadvantages, including low efficiency, not being fluorescence-friendly and poor transparency on tissues with a high degree of lignification. In this work, we developed a new plant tissue clearing method for whole plant imaging, named Plant Accessible Tissue Clearing Solvent System (PATCSOS), which was based on the Polyethylene Glycol-associated Solvent System (PEGASOS). The PATCSOS method realized extensive transparency of plant tissues, including the flower, leaf, stem, root, and seed of Arabidopsis thaliana, with high efficiency. The PATCSOS method consists of four main steps: fixation, decolorization/delipidation, dehydration, and clearing. Subsequently a rapid and efficient clearing of mature plant tissue can be achieved. With PATCSOS, we can image Arabidopsis seedling in their entirety in 3-D using endogenous cellulose autofluorescence. Whats more, the PATCSOS method is compatible with fluorescence protein imaging and GUS staining, which greatly expands the applicability of this method. We also imaged intact Nicotiana benthamiana leaf and Zea mays embryos. Our results showed that the PATCSOS clearing method is an excellent tool to study plant development and cell biology.

plant biology↗

bioRxiv2024

GPnotebook: A pan-cancer glycoproteomic database and toolkit for analysis of protein glycosylation changes associated with cancer phenotypes

Protein glycosylation plays a pivotal role in various biological processes, and the analysis of intact glycopeptides (IGPs) has emerged as a powerful approach for characterizing alterations in protein glycosylation associated with diseases. Despite the critical insights gained from IGP analysis, there is an evident scarcity of intact glycopeptide database and specialized tools for a comprehensive glycoproteomic examination. In response to this deficiency, we have developed a Python package, "GPnotebook," which consolidates the intact glycopeptides identified from different cancer types by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and includes analytical tools for an in-depth characterization of glycopeptides. GPnotebook facilitates an array of functions including statistical profiling, differential expression analysis, glycosylation subtype categorization, investigation of glycosylation-phosphorylation interplay, survival analysis, and glycosylation enzyme assessment. We have deployed GPnotebook in a study of Pancreatic Ductal Adenocarcinoma (PDAC), thereby validating its application and demonstrating its capabilities. Our findings suggest that IGPs hold significant promise as cancer-specific changes and subtype differentiation. Consequently, GPnotebook stands out as a valuable resource for cancer researchers delving into the nuances of protein glycosylation and its correlation with cancer phenotypes. HILIGHTSO_LISimplified and unified access to pan-cancer glycoproteomic database including 90,795 intact glycopeptides. C_LIO_LIDeveloped a glycoproteomic analysis toolkit for systematic glycoproteomic data analysis C_LIO_LIApplied the toolkit for identification of glycosylation changes associated with cancer phenotypes in pancreatic cancer. C_LI

bioinformatics↗

bioRxiv2024

Intestinal commensal bacteria promote Bactrocera dorsalis larval development through vitamin B6 synthesis pathway

BackgroundThe gut microbiota can facilitate host growth under nutrient-constrained conditions. However, whether this effect is limited to certain bacterial species remains largely unclear, and the relevant mechanisms remain to be thoroughly investigated. ResultsHere, we found that the microbiota was required for Bactrocera dorsalis larval growth under poor diet conditions. Mono-association experiments revealed that Enterobacteriaceae and some Lactobacilli promoted larval growth. Of 27 tested bacterial strains, 15 strains significantly promoted larval development, and the Enterobacteriaceae cloacae N29 isolate exhibited the most obvious promoting effect. Bacterial genome-wide association study (GWAS) revealed that the vitamin B6 synthesis pathway was critical for E. cloacae growth promotion. The deletion of pdxA responsible for the vitamin B6 biosynthesis deprived the mutant strains of larval growth promotion function, indicating that pdxA gene was crucial for promoting larval growth in the N29 strain. Importantly, supplementation of vitamin B6 to poor diet successfully rescued the axenic larval growth phenotype of B. dorsalis. ConclusionOur results suggest that gut microbes promote insect larval growth by providing vitamin B6 under nutrient scarcity in B. dorsalis.

microbiology↗