EcCas6e-based antisense crRNA for gene repression and RNA editing in microorganisms.

Precise gene regulation and programmable RNA editing are vital RNA-level regulatory mechanisms. Gene repression tools grounded in small non-coding RNAs, microRNAs, and CRISPR-dCas proteins, along with RNA editing tools anchored in Adenosine Deaminases acting on RNA (ADARs), have found extensive application in molecular biology and cellular engineering. Here, we introduced a novel approach wherein we developed an EcCas6e mediated crRNA-mRNA annealing system for gene repression in Escherichia coli and RNA editing in Saccharomyces cerevisiae. We found that EcCas6e possesses inherent RNA annealing ability attributed to a secondary positively charged cleft, enhancing crRNA-mRNA hybridization and stability. Based on this, we demonstrated that EcCas6e, along with its cognate crRNA repeat containing a complementary region to the ribosome binding site of a target mRNA, effectively represses gene expression up to 25-fold. Furthermore, we demonstrated that multiple crRNAs can be easily assembled and can simultaneously target up to 13 genes. Lastly, the EcCas6e-crRNA system was developed as an RNA editing tool by fusing it with the ADAR2 deaminase domain. The EcCas6e-crRNA mediated gene repression and RNA editing tools hold broad applications for research and biotechnology.

miR-275/305 cluster is essential for maintaining energy metabolic homeostasis by the insulin signaling pathway in Bactrocera dorsalis.

Increasing evidence indicates that miRNAs play crucial regulatory roles in various physiological processes of insects, including systemic metabolism. However, the molecular mechanisms of how specific miRNAs regulate energy metabolic homeostasis remain largely unknown. In the present study, we found that an evolutionarily conserved miR-275/305 cluster was essential for maintaining energy metabolic homeostasis in response to dietary yeast stimulation in Bactrocera dorsalis. Depletion of miR-275 and miR-305 by the CRISPR/Cas9 system significantly reduced triglyceride and glycogen contents, elevated total sugar levels, and impaired flight capacity. Combined in vivo and in vitro experiments, we demonstrated that miR-275 and miR-305 can bind to the 3'UTR regions of SLC2A1 and GLIS2 to repress their expression, respectively. RNAi-mediated knockdown of these two genes partially rescued metabolic phenotypes caused by inhibiting miR-275 and miR-305. Furthermore, we further illustrated that the miR-275/305 cluster acting as a regulator of the metabolic axis was controlled by the insulin signaling pathway. In conclusion, our work combined genetic and physiological approaches to clarify the molecular mechanism of metabolic homeostasis in response to different dietary stimulations and provided a reference for deciphering the potential targets of physiologically important miRNAs in a non-model organism.

Isaridin E Protects against Sepsis by Inhibiting Von Willebrand Factor-Induced Endothelial Hyperpermeability and Platelet-Endothelium Interaction.

Endothelial hyperpermeability is pivotal in sepsis-associated multi-organ dysfunction. Increased von Willebrand factor (vWF) plasma levels, stemming from activated platelets and endothelium injury during sepsis, can bind to integrin αvß3, exacerbating endothelial permeability. Hence, targeting this pathway presents a potential therapeutic avenue for sepsis. Recently, we identified isaridin E (ISE), a marine-derived fungal cyclohexadepsipeptide, as a promising antiplatelet and antithrombotic agent with a low bleeding risk. ISE's influence on septic mortality and sepsis-induced lung injury in a mouse model of sepsis, induced by caecal ligation and puncture, is investigated in this study. ISE dose-dependently improved survival rates, mitigating lung injury, thrombocytopenia, pulmonary endothelial permeability, and vascular inflammation in the mouse model. ISE markedly curtailed vWF release from activated platelets in septic mice by suppressing vesicle-associated membrane protein 8 and soluble N-ethylmaleide-sensitive factor attachment protein 23 overexpression. Moreover, ISE inhibited healthy human platelet adhesion to cultured lipopolysaccharide (LPS)-stimulated human umbilical vein endothelial cells (HUVECs), thereby significantly decreasing vWF secretion and endothelial hyperpermeability. Using cilengitide, a selective integrin αvß3 inhibitor, it was found that ISE can improve endothelial hyperpermeability by inhibiting vWF binding to αvß3. Activation of the integrin αvß3-FAK/Src pathway likely underlies vWF-induced endothelial dysfunction in sepsis. In conclusion, ISE protects against sepsis by inhibiting endothelial hyperpermeability and platelet-endothelium interactions.

An adaptive multi-modal hybrid model for classifying thyroid nodules by combining ultrasound and infrared thermal images.

BACKGROUND: Two types of non-invasive, radiation-free, and inexpensive imaging technologies that are widely employed in medical applications are ultrasound (US) and infrared thermography (IRT). The ultrasound image obtained by ultrasound imaging primarily expresses the size, shape, contour boundary, echo, and other morphological information of the lesion, while the infrared thermal image obtained by infrared thermography imaging primarily describes its thermodynamic function information. Although distinguishing between benign and malignant thyroid nodules requires both morphological and functional information, present deep learning models are only based on US images, making it possible that some malignant nodules with insignificant morphological changes but significant functional changes will go undetected. RESULTS: Given the US and IRT images present thyroid nodules through distinct modalities, we proposed an Adaptive multi-modal Hybrid (AmmH) classification model that can leverage the amalgamation of these two image types to achieve superior classification performance. The AmmH approach involves the construction of a hybrid single-modal encoder module for each modal data, which facilitates the extraction of both local and global features by integrating a CNN module and a Transformer module. The extracted features from the two modalities are then weighted adaptively using an adaptive modality-weight generation network and fused using an adaptive cross-modal encoder module. The fused features are subsequently utilized for the classification of thyroid nodules through the use of MLP. On the collected dataset, our AmmH model respectively achieved 97.17% and 97.38% of F1 and F2 scores, which significantly outperformed the single-modal models. The results of four ablation experiments further show the superiority of our proposed method. CONCLUSIONS: The proposed multi-modal model extracts features from various modal images, thereby enhancing the comprehensiveness of thyroid nodules descriptions. The adaptive modality-weight generation network enables adaptive attention to different modalities, facilitating the fusion of features using adaptive weights through the adaptive cross-modal encoder. Consequently, the model has demonstrated promising classification performance, indicating its potential as a non-invasive, radiation-free, and cost-effective screening tool for distinguishing between benign and malignant thyroid nodules. The source code is available at https://github.com/wuliZN2020/AmmH .

Gut microbiota promotes host resistance to low-temperature stress by stimulating its arginine and proline metabolism pathway in adult Bactrocera dorsalis.

Gut symbiotic bacteria have a substantial impact on host physiology and ecology. However, the contribution of gut microbes to host fitness during long-term low-temperature stress is still unclear. This study examined the role of gut microbiota in host low-temperature stress resistance at molecular and biochemical levels in the oriental fruit fly Bactrocera dorsalis. The results showed that after the gut bacteria of flies were removed via antibiotic treatment, the median survival time was significantly decreased to approximately 68% of that in conventional flies following exposure to a temperature stress of 10°C. Furthermore, we found that Klebsiella michiganensis BD177 is a key symbiotic bacterium, whose recolonization in antibiotic treated (ABX) flies significantly extended the median survival time to 160% of that in the ABX control, and restored their lifespan to the level of conventional flies. Notably, the relative levels of proline and arginine metabolites were significantly downregulated by 34- and 10-fold, respectively, in ABX flies compared with those in the hemolymph of conventional flies after exposure to a temperature stress of 10°C whereas recolonization of ABX flies by K. michiganensis BD177 significantly upregulated the levels of proline and arginine by 13- and 10- fold, respectively, compared with those found in the hemolymph of ABX flies. qPCR analysis also confirmed that K. michiganensis-recolonized flies significantly stimulated the expression of transcripts from the arginine and proline metabolism pathway compared with the ABX controls, and RNAi mediated silencing of two key genes Pro-C and ASS significantly reduced the survival time of conventional flies, postexposure low-temperature stress. We show that microinjection of L-arginine and L-proline into ABX flies significantly increased their survival time following exposure to temperature stress of 10°C. Transmission electron microscopy (TEM) analysis further revealed that low-temperature stress caused severe destruction in cristae structures and thus resulted in abnormal circular shapes of mitochondria in ABX flies gut, while the recolonization of live K. michiganensis helped the ABX flies to maintain mitochondrial functionality to a normal status, which is important for the arginine and proline induction. Our results suggest that gut microbiota plays a vital role in promoting the host resistance to low-temperature stress in B. dorsalis by stimulating its arginine and proline metabolism pathway.

Comparative genomics of Klebsiella michiganensis BD177 and related members of Klebsiella sp. reveal the symbiotic relationship with Bactrocera dorsalis.

BACKGROUND: Bactrocera dorsalis is a destructive polyphagous and highly invasive insect pest of tropical and subtropical species of fruit and vegetable crops. The sterile insect technique (SIT) has been used for decades to control insect pests of agricultural, veterinary, and human health importance. Irradiation of pupae in SIT can reduce the ecological fitness of the sterile insects. Our previous study has shown that a gut bacterial strain BD177 that could restore ecological fitness by promoting host food intake and metabolic activities. RESULTS: Using long-read sequence technologies, we assembled the complete genome of K. michiganensis BD177 strain. The complete genome of K. michiganensis BD177 comprises one circular chromosome and four plasmids with a GC content of 55.03%. The pan-genome analysis was performed on 119 genomes (strain BD177 genome and 118 out of 128 published Klebsiella sp. genomes since ten were discarded). The pan-genome includes a total of 49305 gene clusters, a small number of 858 core genes, and a high number of accessory (10566) genes. Pan-genome and average nucleotide identity (ANI) analysis showed that BD177 is more similar to the type strain K. michiganensis DSM2544, while away from the type strain K. oxytoca ATCC13182. Comparative genome analysis with 21 K. oxytoca and 12 K. michiganensis strains, identified 213 unique genes, several of them related to amino acid metabolism, metabolism of cofactors and vitamins, and xenobiotics biodegradation and metabolism in BD177 genome. CONCLUSIONS: Phylogenomics analysis reclassified strain BD177 as a member of the species K. michiganensis. Comparative genome analysis suggested that K. michiganensis BD177 has the strain-specific ability to provide three essential amino acids (phenylalanine, tryptophan and methionine) and two vitamins B (folate and riboflavin) to B. dorsalis. The clear classification status of BD177 strain and identification of unique genetic characteristics may contribute to expanding our understanding of the symbiotic relationship of gut microbiota and B. dorsalis.

Tephritidae fruit fly gut microbiome diversity, function and potential for applications.

The family Tephritidae (order: Diptera), commonly known as fruit flies, comprises a widely distributed group of agricultural pests. The tephritid pests infest multiple species of fruits and vegetables, resulting in huge crop losses. Here, we summarize the composition and diversity of tephritid gut-associated bacteria communities and host intrinsic and environmental factors that influence the microbiome structures. Diverse members of Enterobacteriaceae, most commonly Klebsiella and Enterobacter bacteria, are prevalent in fruit flies guts. Roles played by gut bacteria in host nutrition, development, physiology and resistance to insecticides and pathogens are also addressed. This review provides an overview of fruit fly microbiome structure and points to diverse roles that it can play in fly physiology and survival. It also considers potential use of this knowledge for the control of economically important fruit flies, including the sterile insect technique and cue-lure baiting.

Temporal phenotyping by mining healthcare data to derive lines of therapy for cancer.

Lines of therapy (LOT) derived from real-world healthcare data not only depict real-world cancer treatment sequences, but also help define patient phenotypes along the course of disease progression and therapeutic interventions. The sequence of prescribed anticancer therapies can be defined as temporal phenotyping resulting from changes in morphological (tumor staging), biochemical (biomarker testing), physiological (disease progression), and behavioral (physician prescribing and patient adherence) parameters. We introduce a novel methodology that is a two-part approach: 1) create an algorithm to derive patient-level LOT and 2) aggregate LOT information via clustering to derive temporal phenotypes, in conjunction with visualization techniques, within a large insurance claims dataset. We demonstrated the methodology using two examples: metastatic non-small cell lung cancer and metastatic melanoma. First, we generated a longitudinal patient cohort for each cancer type and applied a set of rules to derive patient-level LOT. Then the LOT algorithm outputs for each cancer type were visualized using Sankey plots and K-means clusters based on durations of LOT and of gaps in therapy between LOT. We found differential distribution of temporal phenotypes across clusters. Our approach to identify temporal patient phenotypes can increase the quality and utility of analyses conducted using claims datasets, with the potential for application to multiple oncology disease areas across diverse healthcare data sources. The understanding of LOT as defining patients' temporal phenotypes can contribute to continuous health learning of disease progression and its interaction with different treatment pathways; in addition, this understanding can provide new insights that can be applied by tailoring treatment sequences for the patient phenotypes who will benefit.

Node Location Privacy Protection Based on Differentially Private Grids in Industrial Wireless Sensor Networks.

Wireless sensor networks (WSNs) are widely applied in industrial application with the rapid development of Industry 4.0. Combining with centralized cloud platform, the enormous computational power is provided for data analysis, such as strategy control and policy making. However, the data analysis and mining will bring the issue of privacy leakage since sensors will collect varieties of data including sensitive location information of monitored objects. Differential privacy is a novel technique that can prevent compromising single record benefits. Geospatial data can be indexed by a tree structure; however, existing differentially private release methods pay no attention to the concrete analysis about the partition granularity of data domains. Based on the overall analysis of noise error and non-uniformity error, this paper proposes a data domain partitioning model, which is more accurate to choose the grid size. A uniform grid release method is put forward based on this model. In order to further reduce the errors, similar cells are merged, and then noise is added into the merged cells. Results show that our method significantly improves the query accuracy compared with other existing methods.

An integrated chemical biology approach reveals the mechanism of action of HIV replication inhibitors.

Continuous flow (microfluidic) chemistry was employed to prepare a small focused library of dihydropyrimidinone (DHPM) derivatives. Compounds in this class have been reported to exhibit activity against the human immunodeficiency virus (HIV), but their molecular target had not been identified. We tested the initial set of DHPMs in phenotypic assays providing a hit (1i) that inhibited the replication of the human immunodeficiency virus HIV in cells. Flow chemistry-driven optimization of 1i led to the identification of HIV replication inhibitors such as 1l with cellular potency comparable with the clinical drug nevirapine (NVP). Mechanism of action (MOA) studies using cellular and biochemical assays coupled with 3D fingerprinting and in silico modeling demonstrated that these drug-like probe compounds exert their effects by inhibiting the viral reverse transcriptase polymerase (RT). This led to the design and synthesis of the novel DHPM 1at that inhibits the replication of drug resistant strains of HIV. Our work demonstrates that combining flow chemistry-driven analogue refinement with phenotypic assays, in silico modeling and MOA studies is a highly effective strategy for hit-to-lead optimization applicable to the discovery of future therapeutic agents.

Validation of a Pseudovirus Neutralization Assay for Severe Acute Respiratory Syndrome Coronavirus 2: A High-Throughput Method for the Evaluation of Vaccine Immunogenicity.

The evaluation of coronavirus disease 2019 (COVID-19) vaccine immunogenicity remains essential as the severe acute respiratory syncytial virus 2 (SARS-CoV-2) pandemic continues to evolve and as additional variants emerge. Neutralizing antibodies are a known correlate of protection for SARS-CoV-2 vaccines. A pseudovirus neutralization (PNT) assay was developed and validated at Novavax Clinical Immunology Laboratories to allow for the detection of neutralizing antibodies in vaccine clinical trial sera. The PNT assay was precise, accurate, linear, and specific in measuring SARS-CoV-2 neutralization titers in human serum for ancestral strain and the Omicron subvariants BA.5 and XBB.1.5, with an overall geometric coefficient of variation of ≤43.4%, a percent relative bias within the expected range of -60% to 150%, and a linearity value of R2 > 0.98 for all three strains. This pseudovirus assay will be useful for the analysis of vaccine clinical trial samples to assess vaccine immunogenicity. Future work will focus on modifying the assay for emerging variants, including XBB.1.16, EG.5.1, BA.2.86, and any other variants that emerge in the ongoing pandemic.

A Pseudovirus-Based Neutralization Assay for SARS-CoV-2 Variants: A Rapid, Cost-Effective, BSL-2-Based High-Throughput Assay Useful for Vaccine Immunogenicity Evaluation.

Neutralizing antibody responses from COVID-19 vaccines are pivotal in conferring protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Effective COVID-19 vaccines and assays measuring neutralizing antibodies against emerging variants (i.e., XBB.1.5, XBB.1.16, and XBB.2.3) are needed. The use of biosafety level (BSL)-3 laboratories for live virus assays results in higher costs and a longer turnaround time; therefore, a BSL-2-based pseudovirus neutralization assay (PNT) was developed. The pseudoviruses were produced by cotransfecting cells with plasmids encoding a lentiviral backbone-expressing luciferase reporter; non-surface proteins for lentiviral production; and ancestral or Omicron (BA.1 and BA.5) SARS-CoV-2 spike (S) proteins. The PNT was developed and optimized in dose and kinetics experiments. The representative serum samples (COVID-19-convalescent or NVX-CoV2373-vaccinated participants enrolled in the 2019nCoV-101 trial) demonstrated a wide dynamic range. The neutralization data showed robust correlation with validated anti-recombinant spike IgG levels and angiotensin-converting enzyme 2 inhibition titers (ancestral). This assay is suitable for measurement of the neutralization ability in clinical samples from individuals infected with SARS-CoV-2 or immunized with a COVID-19 vaccine. The results suggest that this PNT provides a lower cost, high-throughput, rapid turnaround alternative to BSL-3-based microneutralization assays and enables the discovery and development of effective vaccines against emerging variants.

Integrated analysis of miRNA and mRNA expression profiles in response to gut microbiota depletion in the abdomens of female Bactrocera dorsalis.

Insect gut microbiota has been reported to participate in regulating host multiple biological processes including metabolism and reproduction. However, the corresponding molecular mechanisms remain largely unknown. Recent studies suggest that microRNAs (miRNAs) are involved in complex interactions between the gut microbiota and the host. Here, we used next-generation sequencing technology to characterize miRNA and mRNA expression profiles and construct the miRNA-gene regulatory network in response to gut microbiota depletion in the abdomens of female Bactrocera dorsalis. A total of 3016 differentially expressed genes (DEGs) and 18 differentially expressed miRNAs (DEMs) were identified. Based on the integrated analysis of miRNA and mRNA sequencing data, 229 negatively correlated miRNA-gene pairs were identified from the miRNA-mRNA network. Gene ontology enrichment analysis indicated that DEMs could target several genes involved in the metabolic process, oxidation-reduction process, oogenesis, and insulin signaling pathway. Finally, real-time quantitative polymerase chain reaction further verified the accuracy of RNA sequencing results. In conclusion, our study provides the profiles of miRNA and mRNA expressions under antibiotics treatment and provides an insight into the roles of miRNAs and their target genes in the interaction between the gut microbiota and its host.

Time-aware neural ordinary differential equations for incomplete time series modeling.

Internet of Things realizes the ubiquitous connection of all things, generating countless time-tagged data called time series. However, real-world time series are often plagued with missing values on account of noise or malfunctioning sensors. Existing methods for modeling such incomplete time series typically involve preprocessing steps, such as deletion or missing data imputation using statistical learning or machine learning methods. Unfortunately, these methods unavoidable destroy time information and bring error accumulation to the subsequent model. To this end, this paper introduces a novel continuous neural network architecture, named Time-aware Neural-Ordinary Differential Equations (TN-ODE), for incomplete time data modeling. The proposed method not only supports imputation missing values at arbitrary time points, but also enables multi-step prediction at desired time points. Specifically, TN-ODE employs a time-aware Long Short-Term Memory as an encoder, which effectively learns the posterior distribution from partial observed data. Additionally, the derivative of latent states is parameterized with a fully connected network, thereby enabling continuous-time latent dynamics generation. The proposed TN-ODE model is evaluated on both real-world and synthetic incomplete time-series datasets by conducting data interpolation and extrapolation tasks as well as classification task. Extensive experiments show the TN-ODE model outperforms baseline methods in terms of Mean Square Error for imputation and prediction tasks, as well as accuracy in downstream classification task.

Composed Image Retrieval via Cross Relation Network With Hierarchical Aggregation Transformer.

Composing Text and Image to Image Retrieval (CTI-IR) aims at finding the target image, which matches the query image visually along with the query text semantically. However, existing works ignore the fact that the reference text usually serves multiple functions, e.g., modification and auxiliary. To address this issue, we put forth a unified solution, namely Hierarchical Aggregation Transformer incorporated with Cross Relation Network (CRN). CRN unifies modification and relevance manner in a single framework. This configuration shows broader applicability, enabling us to model both modification and auxiliary text or their combination in triplet relationships simultaneously. Specifically, CRN includes: 1) Cross Relation Network comprehensively captures the relationships of various composed retrieval scenarios caused by two different query text types, allowing a unified retrieval model to designate adaptive combination strategies for flexible applicability; 2) Hierarchical Aggregation Transformer aggregates top-down features with Multi-layer Perceptron (MLP) to overcome the limitations of edge information loss in a window-based multi-stage Transformer. Extensive experiments demonstrate the superiority of the proposed CRN over all three fashion-domain datasets. Code is available at github.com/yan9qu/crn.

XBB.1.5 spike protein COVID-19 vaccine induces broadly neutralizing and cellular immune responses against EG.5.1 and emerging XBB variants.

Monovalent SARS-CoV-2 Prototype (Wuhan-Hu-1) and bivalent (Prototype + BA.4/5) COVID-19 vaccines have demonstrated a waning of vaccine-mediated immunity highlighted by lower neutralizing antibody responses against SARS-CoV-2 Omicron XBB sub-variants. The reduction of humoral immunity due to the rapid evolution of SARS-CoV-2 has signaled the need for an update to vaccine composition. A strain change for all authorized/approved vaccines to a monovalent composition with Omicron subvariant XBB.1.5 has been supported by the WHO, EMA, and FDA. Here, we demonstrate that immunization with a monovalent recombinant spike protein COVID-19 vaccine (Novavax, Inc.) based on the subvariant XBB.1.5 induces neutralizing antibodies against XBB.1.5, XBB.1.16, XBB.2.3, EG.5.1, and XBB.1.16.6 subvariants, promotes higher pseudovirus neutralizing antibody titers than bivalent (Prototype + XBB.1.5) vaccine, induces SARS-CoV-2 spike-specific Th1-biased CD4 + T-cell responses against XBB subvariants, and robustly boosts antibody responses in mice and nonhuman primates primed with a variety of monovalent and bivalent vaccines. Together, these data support updating the Novavax vaccine to a monovalent XBB.1.5 formulation for the 2023-2024 COVID-19 vaccination campaign.

Gut fungal community and its probiotic effect on Bactrocera dorsalis.

The oriental fruit fly, Bactrocera dorsalis (Diptera: Tephritidae) is a destructive horticultural pest which causes considerable economic losses every year. A collection of microorganisms live within the B. dorsalis gut, and they are involved in its development, physiology, and behavior. However, knowledge regarding the composition and function of the gut mycobiota in B. dorsalis are still limited. Here, we comprehensively characterized the gut mycobiota in B. dorsalis across different developmental stages. High-throughput sequencing results showed a significant difference in fungal species abundance and diversity among different developmental stages of B. dorsalis. Quantitative polymerase chain reaction and culture-dependent methods showed that yeast species was the dominant group in the larval stage. We isolated 13 strains of yeast from the larval gut, and found that GF (germ-free) larvae mono-associated with strain Hanseniaspora uvarum developed faster than those mono-associated with other tested fungal strains. Supplementing the larval diet with H. uvarum fully rescued B. dorsalis development, shortened the larval developmental time, and increased adult wing lengths, as well as the body sizes and weights of both pupae and adults. Thus, our study highlights the close interactions between gut fungi, especially H. uvarum, and B. dorsalis. These findings can be applied to the sterile insect technique program to promote host development during mass insect rearing.

Compartmentalized PGRP expression along the dipteran Bactrocera dorsalis gut forms a zone of protection for symbiotic bacteria.

All metazoan guts are subject to opposing pressures wherein the immune system must eliminate pathogens while tolerating the presence of symbiotic microbiota. The Imd pathway is an essential defense against invading pathogens in insect guts, but tolerance mechanisms are less understood. Here, we find PGRP-LB and PGRP-SB express mainly in the anterior and middle midgut in a similar pattern to symbiotic Enterobacteriaceae bacteria along the Bactrocera dorsalis gut. Knockdown of PGRP-LB and PGRP-SB enhances the expression of antimicrobial peptide genes and reduces Enterobacteriaceae numbers while increasing abundance of opportunistic pathogens. Microbiota numbers recover to normal levels after the RNAi effect subsided. In contrast, high expression of PGRP-LC in the foregut allows increased antibacterial peptide production to efficiently filter the entry of pathogens, protecting the symbiotic bacteria. Our study describes a mechanism by which regional expression of PGRPs construct a protective zone for symbiotic microbiota while maintaining the ability to fight pathogens.

Novel Compound Inhibitors of HIV-1NL4-3 Vpu.

HIV-1 Vpu targets the host cell proteins CD4 and BST-2/Tetherin for degradation, ultimately resulting in enhanced virus spread and host immune evasion. The discovery and characterization of small molecules that antagonize Vpu would further elucidate the contribution of Vpu to pathogenesis and lay the foundation for the study of a new class of novel HIV-1 therapeutics. To identify novel compounds that block Vpu activity, we have developed a cell-based 'gain of function' assay that produces a positive signal in response to Vpu inhibition. To develop this assay, we took advantage of the viral glycoprotein, GaLV Env. In the presence of Vpu, GaLV Env is not incorporated into viral particles, resulting in non-infectious virions. Vpu inhibition restores infectious particle production. Using this assay, a high throughput screen of >650,000 compounds was performed to identify inhibitors that block the biological activity of Vpu. From this screen, we identified several positive hits but focused on two compounds from one structural family, SRI-41897 and SRI-42371. We developed independent counter-screens for off target interactions of the compounds and found no off target interactions. Additionally, these compounds block Vpu-mediated modulation of CD4, BST-2/Tetherin and antibody dependent cell-mediated toxicity (ADCC). Unfortunately, both SRI-41897 and SRI-42371 were shown to be specific to the N-terminal region of NL4-3 Vpu and did not function against other, more clinically relevant, strains of Vpu; however, this assay may be slightly modified to include more significant Vpu strains in the future.

Regulatory mechanisms of microbial homeostasis in insect gut.

Insects live in incredibly complex environments. The intestinal epithelium of insects is in constant contact with microorganisms, some of which are beneficial and some harmful to the host. Insect gut health and function are maintained through multidimensional mechanisms that can proficiently remove foreign pathogenic microorganisms while effectively maintaining local symbiotic microbial homeostasis. The basic immune mechanisms of the insect gut, such as the dual oxidase-reactive oxygen species (Duox-ROS) system and the immune deficiency (Imd)-signaling pathway, are involved in the maintenance of microbial homeostasis. This paper reviews the role of physical defenses, the Duox-ROS and Imd signaling pathways, the Janus kinase/signal transducers and activators of transcription signaling pathway, and intestinal symbiotic flora in the homeostatic maintenance of the insect gut microbiome.