Communication between the stem cell niche and an adjacent differentiation niche through miRNA and EGFR signaling orchestrates exit from the stem cell state in the Drosophila ovary.

The signaling environment, or niche, often governs the initial difference in behavior of an adult stem cell and a derivative that initiates a path towards differentiation. The transition between an instructive stem cell niche and differentiation niche must generally have single-cell resolution, suggesting that multiple mechanisms might be necessary to sharpen the transition. Here, we examined the Drosophila ovary and found that Cap cells, which are key constituents of the germline stem cell (GSC) niche, express a conserved microRNA (miR-124). Surprisingly, loss of miR-124 activity in Cap cells leads to a defect in differentiation of GSC derivatives. We present evidence that the direct functional target of miR-124 in Cap cells is the epidermal growth factor receptor (EGFR) and that failure to limit EGFR expression leads to the ectopic expression of a key anti-differentiation BMP signal in neighboring somatic escort cells (ECs), which constitute a differentiation niche. We further found that Notch signaling connects EFGR activity in Cap cells to BMP expression in ECs. We deduce that the stem cell niche communicates with the differentiation niche through a mechanism that begins with the selective expression of a specific microRNA and culminates in the suppression of the major anti-differentiation signal in neighboring cells, with the functionally important overall role of sharpening the spatial distinction between self-renewal and differentiation environments.

Negative performance feedback from algorithms or humans? effect of medical researchers' algorithm aversion on scientific misconduct.

Institutions are increasingly employing algorithms to provide performance feedback to individuals by tracking productivity, conducting performance appraisals, and developing improvement plans, compared to traditional human managers. However, this shift has provoked considerable debate over the effectiveness and fairness of algorithmic feedback. This study investigates the effects of negative performance feedback (NPF) on the attitudes, cognition and behavior of medical researchers, comparing NPF from algorithms versus humans. Two scenario-based experimental studies were conducted with a total sample of 660 medical researchers (algorithm group: N1 = 411; human group: N2 = 249). Study 1 analyzes the differences in scientific misconduct, moral disengagement, and algorithmic attitudes between the two sources of NPF. The findings reveal that NPF from algorithms shows higher levels of moral disengagement, scientific misconduct, and negative attitudes towards algorithms compared to NPF from humans. Study 2, grounded in trait activation theory, investigates how NPF from algorithms triggers individual's egoism and algorithm aversion, potentially leading to moral disengagement and scientific misconduct. Results indicate that algorithm aversion triggers individuals' egoism, and their interaction enhances moral disengagement, which in turn leads to increased scientific misconduct among researchers. This relationship is also moderated by algorithmic transparency. The study concludes that while algorithms can streamline performance evaluations, they pose significant risks to scientific misconduct of researchers if not properly designed. These findings extend our understanding of NPF by highlighting the emotional and cognitive challenges algorithms face in decision-making processes, while also underscoring the importance of balancing technological efficiency with moral considerations to promote a healthy research environment. Moreover, managerial implications include integrating human oversight in algorithmic NPF processes and enhancing transparency and fairness to mitigate negative impacts on medical researchers' attitudes and behaviors.

Hyccin/FAM126A deficiency reduces glial enrichment and axonal sheath, which are rescued by overexpression of a plasma membrane-targeting PI4KIIIα in Drosophila.

Hyccin/FAM126A mutations are linked to hypomyelination and congenital cataract disease (HCC), but whether and how Hyccin/FAM126A deficiency causes hypomyelination remains undetermined. This study shows Hyccin/FAM126A expression was necessary for the expression of other components of the PI4KIIIα complex in Drosophila. Knockdown of Hyccin/FAM126A in glia reduced the enrichment of glial cells, disrupted axonal sheaths and visual ability in the visual system, and these defects could be fully rescued by overexpressing either human FAM126A or FAM126B, and partially rescued by overexpressing a plasma membrane-targeting recombinant mouse PI4KIIIα. Additionally, PI4KIIIα knockdown in glia phenocopied Hyccin/FAM126A knockdown, and this was partially rescued by overexpressing the recombinant PI4KIIIα, but not human FAM126A or FAM126B. This study establishes an animal model of HCC and indicates that Hyccin/FAM126A plays an essential role in glial enrichment and axonal sheath in a cell-autonomous manner in the visual system via controlling the expression and stabilization of the PI4KIIIα complex at the plasma membrane.

Block Copolymer Vesicles with Tunable Membrane Thicknesses and Compositions Prepared by Aqueous Seeded Photoinitiated Polymerization-Induced Self-Assembly at Room Temperature.

Block copolymer vesicles with diverse functionalities and intrinsic hollow structures have received considerable attention due to their broad applications in biomedical fields, including drug delivery, bioimaging, theranostics, gene therapy, etc. However, efficient preparation of block copolymer vesicles with tunable membrane thicknesses and compositions under mild conditions is still a challenge. Herein, we report an aqueous seeded photoinitiated polymerization-induced self-assembly (photo-PISA) for the precise preparation of block copolymer vesicles at room temperature. By changing the total degree of polymerization (DP) of the hydrophobic block in seeded photo-PISA, one can easily tune the membrane thickness without compromising the morphology of vesicles. Moreover, by adding different comonomers such as hydrophobic monomers, hydrophilic monomers, and cross-linkers into seeded photo-PISA, vesicles with different compositions could be prepared without compromising the morphology and colloidal stability. Polymerization kinetics show that seeded photo-PISA can skip the step of in situ self-assembly with a short homogeneous polymerization stage being observed. To demonstrate potential biological applications, enzymatic nanoreactors were constructed by loading horseradish peroxidase (HRP) inside vesicles via seeded photo-PISA. The enzymatic properties of these nanoreactors could be easily regulated by changing the membrane thickness and hydrophobicity. It is expected that this method can provide a facile platform for the precise preparation of block copolymer vesicles that may find applications in different fields.

Exosomal LncRNA RP5-977B1 as a novel minimally invasive biomarker for diagnosis and prognosis in non-small cell lung cancer.

BACKGROUND: Lung cancer is the leading cause of cancer-related deaths in the world. Non-small cell lung cancer (NSCLC) accounts for 85% of all lung cancer cases. For lack of conveniently sensitive and specific biomarkers, the majority of patients are in the late stage at initial diagnosis. Long non-coding RNAs (LncRNAs), a novel type of non-coding RNA, have recently been recognized as critical factors in tumor initiation and progression, but the role of exosomal LncRNAs has not been thoroughly excavated in NSCLC yet. METHODS: We isolated exosomes from the serum of patients with NSCLC and healthy controls. Exosome RNA deep sequencing was subsequently performed to detect differentially expressed exosomal LncRNAs. qRT-PCR assay was then utilized to validate dysregulated LncRNAs in both testing and multicentric validation cohort. Receiver operating characteristic (ROC) curve was used to detect the diagnostic capability of exosomal biomarkers. Furthermore, Kaplan-Meier analysis was applied to evaluate the prognostic values of these molecules. RESULTS: On the basis of analysis, we found that novel exosomal LncRNA RP5-977B1 exhibited higher levels in NSCLC than that in the healthy controls. The area under the curve (AUC) value of exosomal RP5-977B1 was 0.8899 and superior to conventional biomarkers CEA and CYFRA21-1 both in testing and multicentric validation cohort. Interestingly, the diagnostic capability of exosomal RP5-977B1 was also validated in early-stage patients with NSCLC. Furthermore, high expression of exosomal RP5-977B1was closely related with worse prognosis in NSCLC (P = 0.036). CONCLUSIONS: Our results suggested that exosomal RP5-977B1 might serve as a novel "liquid biopsy" diagnostic and prognostic biomarker to monitor NSCLC and improve possible therapy.

Enantioselective Diels-Alder reaction of anthracene by chiral tritylium catalysis.

The combination of the trityl cation and a chiral weakly coordinating Fe(III)-based bisphosphate anion was used to develop a new type of a highly active carbocation Lewis acid catalyst. The stereocontrol potential of the chiral tritylium ion pair was demonstrated by its application in an enantioselective Diels-Alder reaction of anthracene.

Asymmetric Latent Carbocation Catalysis with Chiral Trityl Phosphate.

Stable carbocations such as tritylium ions have been widely explored as organic Lewis acid catalysts and reagents in organic synthesis. However, achieving asymmetric carbocation catalysis remains elusive ever since they were first identified over one century ago. The challenges mainly come from their limited compatibility, scarcity of chiral carbocations, as well as the extremely low barrier to racemization of chiral carbenium ions. We reported here a latent concept for asymmetric carbocation catalysis. In this strategy, chiral trityl phosphate is employed as the carbocation precursor, which undergoes facile ionic dissociation upon mild external stimulation (e.g., acid, H-bonding, polar substrates) to form a catalytically active chiral ion pair for substrate activation and chiral induction. The latent strategy provides a solution for the long sought-after asymmetric carbocation catalysis as illustrated in three different enantioselective transformations.

The quality of crowdsourcing virtual community and users' voice behavior: An analysis of stimulus-organism-response framework among Chinese users.

The quality of a crowdsourcing virtual community is an essential factor that stimulates users' perceptions of belonging and attachment to the community, thereby influencing their behavior. As a prerequisite for the development of "creative crowdsourcing," it is particularly important to study how users' voice behavior can be promoted in virtual communities. Drawing on the Stimulus-Organism-Response (SOR) framework and the Social Identification Theory, this study developed a conceptual model that investigates the impact of crowdsourcing virtual communities in system, information, interaction, and service quality on users' voice behavior. Furthermore, we introduce community identification and self-disclosure to further analyze the influencing mechanism between these two variables. Data were collected through 672 survey questionnaires from participants in well-known crowdsourcing virtual communities such as Xiaohongshu, Bilibili, Haier Hope, Test Baidu, and Test China. Using hierarchical regression and bootstrap analysis, we found a positive correlation between the quality of the crowdsourcing virtual community and users' voice behavior, with community identification acting as a mediator. Furthermore, self-disclosure showed a significant moderating effect on the relationship between community identification and voice behavior. These findings significantly contribute to the theoretical landscape by advancing the SOR framework within a virtual community. This not only deepens the understanding of the quality of the crowdsourcing virtual community, but also provides theoretical and practical implications for managers and users on how to promote voice behavior.

Research progress on microbial adsorption of radioactive nuclides in deep geological environments.

Due to the development and utilization of nuclear energy, the safe disposal of nuclear waste needs to be urgently addressed. In recent years, the utilization of microorganisms' adsorption capacity to dispose of radioactive waste has received increasing attention. When compared with conventional disposal methods, microbial adsorption exhibits the characteristics of high efficiency, low cost, and no secondary pollution. In the long term, microbial biomass shows significant promise as specific chemical-binding agents. Optimization of biosorption conditions, identification of rare earth element binding sites, and studies on the sorption capacities of immobilized cells provide compelling reasons to consider biosorption for industrial applications in heavy metal removal from solutions. However, the interaction mechanism between microorganisms and radioactive nuclides is very complex. This mini-review briefly provides an overview of the preparation methods, factors affecting the adsorption capacity, and the mechanisms of microbial adsorbents.

Coordinated molecular and ecological adaptations underlie a highly successful parasitoid.

The success of an organism depends on the molecular and ecological adaptations that promote its beneficial fitness. Parasitoids are valuable biocontrol agents for successfully managing agricultural pests, and they have evolved diversified strategies to adapt to both the physiological condition of hosts and the competition of other parasitoids. Here, we deconstructed the parasitic strategies in a highly successful parasitoid, Trichopria drosophilae, which parasitizes a broad range of Drosophila hosts, including the globally invasive species D. suzukii. We found that T. drosophilae had developed specialized venom proteins that arrest host development to obtain more nutrients via secreting tissue inhibitors of metalloproteinases (TIMPs), as well as a unique type of cell-teratocytes-that digest host tissues for feeding by releasing trypsin proteins. In addition to the molecular adaptations that optimize nutritional uptake, this pupal parasitoid has evolved ecologically adaptive strategies including the conditional tolerance of intraspecific competition to enhance parasitic success in older hosts and the obligate avoidance of interspecific competition with larval parasitoids. Our study not only demystifies how parasitoids weaponize themselves to colonize formidable hosts but also provided empirical evidence of the intricate coordination between the molecular and ecological adaptations that drive evolutionary success.

Conditional Goal-Oriented Trajectory Prediction for Interacting Vehicles.

Predicting future trajectories of pairwise traffic agents in highly interactive scenarios, such as cut-in, yielding, and merging, is challenging for autonomous driving. The existing works either treat such a problem as a marginal prediction task or perform single-axis factorized joint prediction, where the former strategy produces individual predictions without considering future interaction, while the latter strategy conducts conditional trajectory-oriented prediction via agentwise interaction or achieves conditional rollout-oriented prediction via timewise interaction. In this article, we propose a novel double-axis factorized joint prediction pipeline, namely, conditional goal-oriented trajectory prediction (CGTP) framework, which models future interaction both along the agent and time axes to achieve goal and trajectory interactive prediction. First, a goals-of-interest network (GoINet) is designed to extract fine-grained features of goal candidates via hierarchical vectorized representation. Furthermore, we propose a conditional goal prediction network (CGPNet) to produce multimodal goal pairs in an agentwise conditional manner, along with a newly designed goal interactive loss to better learn the joint distribution of the intermediate interpretable modes. Explicitly guided by the goal-pair predictions, we propose a goal-oriented trajectory rollout network (GTRNet) to predict scene-compliant trajectory pairs via timewise interactive rollouts. Extensive experimental results confirm that the proposed CGTP outperforms the state-of-the-art (SOTA) prediction models on the Waymo open motion dataset (WOMD), Argoverse motion forecasting dataset, and In-house cut-in dataset. Code is available at https://github.com/LiDinga/CGTP/.

A new research proposal to prevent hydrogen embrittlement for nuclear waste container by bacteria-a mini review.

A large amount of nuclear waste produced in the process of nuclear energy utilization has always been a key problem to be solved urgently for nuclear safety. At present, "deep geological disposal" is a feasible method and generally accepted by many countries. The oxygen content in the near field environment of the waste container will decrease to anaerobic conditions, and hydrogen will permeation into the internal materials of container for a long time. Hydrogen evolution corrosion may cause a risk of hydrogen embrittlement. The harm of hydrogen embrittlement in metal container is far more severe than predictable uniform corrosion. It is a research hotspot that the microorganisms impact on the corrosion behavior of container materials in the deep geological environment. Microbial corrosion in deep geological environments can be divided into two types: aerobic microbial corrosion and anaerobic microbial corrosion. There is a type of hydrogen consuming microorganism in the natural environment that uses the oxidation of hydrogen as the energy for its life activities. This provides a new approach for us to study reducing the hydrogen embrittlement sensitivity of nuclear waste container materials.

A serum LncRNA signature for predicting prognosis of triple-negative breast cancer.

BACKGROUND: Breast cancer is the leading causes of cancer-associated mortality among women, and triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer. Long non-coding RNAs (LncRNAs) have recently been studied to predict the prognosis of various cancers, but whether it is an effective marker in TNBC is inconclusive. METHODS: We used RNA-sequencing analysis to identify differentially expressed exosomal LncRNAs, and qRT-PCR assay was performed to verify dysregulated LncRNAs in multicenter validation cohorts. A signature, which was composed of LINC00989, CEA, and CA153, was then utilized to predict the progression and recurrence of TNBC. Kaplan-Meier analysis was applied to evaluate the prognostic values of the signature. RESULTS: On the basis of RNA-sequencing analysis, we found that serum exosomal LncRNA LINC00989 was significantly up-regulated in metastatic patients of TNBC. Then LINC00989, together with clinic marker CEA and CA125, were selected to construct a prognostic signature. In both training and validation cohort, higher levels of this signature were significantly related with shorter overall and progression-free survival time. Univariate and multivariate analysis shown that the signature was the independent prognosis factor of TNBC patients. CONCLUSIONS: Our results suggested that this prognostic signature might potentially predict prognosis and recurrence of TNBC, and was worth validation in future clinical trials.

The odorant receptor co-receptor gene contributes to mating and host-searching behaviors in parasitoid wasps.

BACKGROUND: Biological control of pest insects by parasitoid wasps is an effective and environmentally friendly strategy compared with the use of synthetic pesticides. Successful courtship and host-search behaviors of parasitoid wasps are important for biological control efficiency and are often mediated by chemical odorant cues. The odorant receptor co-receptor (Orco) gene has an essential role in the perception of odors in insects. However, the function of Orco in the mating and host-searching behaviors of parasitoid wasps remains underexplored. RESULTS: We identified the full-length Orco genes of four Drosophila parasitoid species in the genus Leptopilina, namely L. heterotoma, L. boulardi, L. syphax and L. drosophilae. Sequence alignment and membrane-topology analysis showed that Leptopilina Orcos had similar amino acid sequences and topology structures. Phylogenetic analysis revealed that Leptopilina Orcos were highly conserved. Furthermore, the results of quantitative real-time polymerase chain reactions showed that all four Orco genes had a typical antennae-biased tissue expression pattern. After knockdown of Orco in these different parasitoid species, we found that Orco-deficient male parasitoid wasps, but not females, lost their courtship ability. Moreover, Orco-deficient female parasitoid wasps presented impaired host-searching performance and decreased oviposition rates. CONCLUSION: Our study demonstrates that Orcos are essential in the mating and host-searching behaviors of parasitoid wasps. To our knowledge, this is the first time that the functions of Orco genes have been characterized in parasitoid wasps, which broadens our understanding of the chemoreception basis of parasitoid wasps and contributes to developing advanced pest management strategies. © 2022 Society of Chemical Industry.

[Sperm sorting based on the imitation of the physiological process on the microfluidic chip].

OBJECTIVE: To establish a new method for sperm sorting by imitating the physiological process of sperm-cervical mucus interaction on the microfluidic chip. METHODS: We designed a microfluidic chip to imitate the physiological process of natural sperm sorting in the microchannel based on the interaction between sperm and cervical mucus, and obtained motile sperm after the interaction. Meanwhile, we established an integrated real-time sperm detection reservoir on this chip to determine sperm parameters using the computer-assisted sperm analysis system. We analyzed 30 samples using both microfluidic and swim-up methods, and compared the results with those obtained before sorting. RESULTS: The rate of grade a + b sperm, the rate of morphologically normal sperm, straight-line velocity (VSL), average path velocity (VAP) and straightness (STR) were (29.78 +/- 11.24)%, (8.00 +/- 5.19)%, (18.89 +/- 4.90) microm/s, (26.84 +/- 5.13) microm/s and (70.15 +/- 7.61)%, respectively, before sorting, (71.65 +/- 11.18)%, (14.95 +/- 6.79)%, (24.14 +/- 5.95) microm/s, (32.61 +/- 6.36) microm/s and (73.87 +/- 9.34)%, respectively, after swim-up sorting, and (92.37 +/- 6.33)%, (23.33 +/- 7.67)%, (34.03 +/- 16.78) microm/s, (38.73 +/- 16.40) microm/s and (84.91 +/- 12.56)%, respectively, after sorting on the microfluidic chip. The sperm parameters obtained before sorting showed statistically significant differences from those obtained on the chip (P < 0.01) and by the swim-up method (P < 0.05). CONCLUSION: Imitation of the physiological interaction between sperm and cervical mucus on the microfluidic chip helped the realization of both the natural sorting and real-time analysis of sperm. The quality of the sperm sorted on the microfluidic chip is significantly better than that of the sperm before sorting and sorted by the swim-up method. This has prepared the ground for imitating the fertilization process under the physiological condition on the microfluidic chip.

Dynamic-Horizon Model-Based Value Estimation With Latent Imagination.

Existing model-based value expansion (MVE) methods typically leverage a world model for value estimation with a fixed rollout horizon to assist policy learning. However, a proper horizon setting is essential to world-model-based policy learning. Meanwhile, choosing an appropriate horizon value is time-consuming, especially for visual control tasks. In this article, we investigate the idea of adaptively using the model knowledge for value expansion. We propose a novel world-model-based method called dynamic-horizon MVE (DMVE) to adjust the use of the world model with adaptive rollout horizon selection. Based on the reconstruction-based technique, the raw and reconstructed images are both used to obtain multihorizon rollouts by utilizing latent imagination. Then, a horizon reliability degree detection approach is given to select appropriate horizons and obtain more accurate value estimation by the reconstructed value expansion errors. Experimental results on the mainstream benchmark visual control tasks show that DMVE outperforms all baselines in sample efficiency and final performance. In addition, experiments on the autonomous driving lane-changing task further demonstrate the scalability of our method. The codes of DMVE are available at https://github.com/JunjieWang95/dmve.

BiFNet: Bidirectional Fusion Network for Road Segmentation.

Multisensor fusion-based road segmentation plays an important role in the intelligent driving system since it provides a drivable area. The existing mainstream fusion method is mainly to feature fusion in the image space domain which causes the perspective compression of the road and damages the performance of the distant road. Considering the bird's eye views (BEVs) of the LiDAR remains the space structure in the horizontal plane, this article proposes a bidirectional fusion network (BiFNet) to fuse the image and BEV of the point cloud. The network consists of two modules: 1) the dense space transformation (DST) module, which solves the mutual conversion between the camera image space and BEV space and 2) the context-based feature fusion module, which fuses the different sensors information based on the scenes from corresponding features. This method has achieved competitive results on the KITTI dataset.

CircFOXP1: A novel serum diagnostic biomarker for non-small cell lung cancer.

BACKGROUND: Emerging evidence suggests that circular RNAs (circRNAs) were aberrantly expressed in the patients of non-small cell lung cancer (NSCLC). This study aims to evaluate the diagnostic value of potential serum biomarker in circRNAs. METHODS: Serum circRNAs were extracted and purified by RNA isolated kit and identified by quantitative real time-polymerase chain reaction (qRT-PCR) assay. We then performed a receiver operating characteristic (ROC) curve to estimate the diagnostic efficacy. The relationship between circRNA and clinic characteristics of patients was analyzed by SPSS 25.0. Univariate and multivariate analyses were also used to evaluate its diagnostic capability. The mechanism of circFOXP1 was further excavated by bioinformatics analysis. RESULTS: By performing qRT-PCR assay, we identified that circFOXP1 (hsa_circ_0008234) and conventional tumor markers (carcinoembryonic antigen (CEA) and cytokeratin fragment 21-1 (CYFRA21-1)) were all significantly overexpressed in the serum of patients with NSCLC when compared with healthy controls (P < 0.05). While the ROC curves analysis demonstrated that area under the curve of circFOXP1 was obviously superior to CEA and CYFRA21-1, which exerted more diagnostic advantage. Univariate and multivariate analyses revealed that serum circFOXP1 was an independent diagnostic molecule, and was significantly correlated with T stage and lymphatic metastasis in NSCLC (P < 0.05). Mechanistically, circFOXP1 might target hsa-miR-370-3p and hsa-miR-18a-5p, and be involved in vascular endothelial growth factor signaling pathways to regulate proliferative and metastasis processes. CONCLUSION: Our results highlight the preferable diagnostic potential of serum circFOXP1 in NSCLC.

Search performance and octopamine neuronal signaling mediate parasitoid induced changes in Drosophila oviposition behavior.

Making the appropriate responses to predation risk is essential for the survival of an organism; however, the underlying mechanisms are still largely unknown. Here, we find that Drosophila has evolved an adaptive strategy to manage the threat from its parasitoid wasp by manipulating the oviposition behavior. Through perception of the differences in host search performance of wasps, Drosophila is able to recognize younger wasps as a higher level of threat and consequently depress the oviposition. We further show that this antiparasitoid behavior is mediated by the regulation of the expression of Tdc2 and Tßh in the ventral nerve cord via LC4 visual projection neurons, which in turn leads to the dramatic reduction in octopamine and the resulting dysfunction of mature follicle trimming and rupture. Our study uncovers a detailed mechanism underlying the defensive behavior in insects that may advance our understanding of predator avoidance in animals.

Parasite reliance on its host gut microbiota for nutrition and survival.

Studying the microbial symbionts of eukaryotic hosts has revealed a range of interactions that benefit host biology. Most eukaryotes are also infected by parasites that adversely affect host biology for their own benefit. However, it is largely unclear whether the ability of parasites to develop in hosts also depends on host-associated symbionts, e.g., the gut microbiota. Here, we studied the parasitic wasp Leptopilina boulardi (Lb) and its host Drosophila melanogaster. Results showed that Lb successfully develops in conventional hosts (CN) with a gut microbiota but fails to develop in axenic hosts (AX) without a gut microbiota. We determined that developing Lb larvae consume fat body cells that store lipids. We also determined that much larger amounts of lipid accumulate in fat body cells of parasitized CN hosts than parasitized AX hosts. CN hosts parasitized by Lb exhibited large increases in the abundance of the bacterium Acetobacter pomorum in the gut, but did not affect the abundance of Lactobacillus fructivorans which is another common member of the host gut microbiota. However, AX hosts inoculated with A. pomorum and/or L. fructivorans did not rescue development of Lb. In contrast, AX larvae inoculated with A. pomorum plus other identified gut community members including a Bacillus sp. substantially rescued Lb development. Rescue was further associated with increased lipid accumulation in host fat body cells. Insulin-like peptides increased in brain neurosecretory cells of parasitized CN larvae. Lipid accumulation in the fat body of CN hosts was further associated with reduced Bmm lipase activity mediated by insulin/insulin-like growth factor signaling (IIS). Altogether, our results identify a previously unknown role for the gut microbiota in defining host permissiveness for a parasite. Our findings also identify a new paradigm for parasite manipulation of host metabolism that depends on insulin signaling and the gut microbiota.