Early radical lung cancer outcome after prompt recovery from COVID-19 infection: A real-world study (preprint)

Background: There has been an increase in the number of patients with lung cancer who had previously contracted SARS-CoV-2 and currently require surgery. This study was to share the early postoperative outcomes in patients who underwent radical lung cancer surgery after early recovery of COVID-19 infection. Methods We retrospectively collected data for 99 patients who had undergone lung cancer surgery in our hospital during January 2022 and January 2023 (including the peak of the COVID-19 crisis）. The patients were divided into two groups according to the inclusion criteria and exclusion criteria. One of these included individuals with a history of SARS-CoV-2 infection. Perioperative and follow-up data at 30-day and 90-day were recorded. Results There were no statistical differences between groups (p > 0.05) in terms of their postoperative complications or 30-day and 90-day postoperative readmission rates. However, there were significant differences between groups (p < 0.05) in terms of their tumor sizes, pathological stages, total drainage volumes, drainage diversion times, and hospital stays. Conclusions The results of the present trial suggested that it is safe to implement radical curative lung cancer surgery in patients without pulmonary impairment and in the early stages (2–4 weeks) of recovery from SARS-CoV-2 infection.

Baricitinib treatment for hospitalized patients with severe COVID-19 on invasive mechanical ventilation：a propensity score-matched and retrospective analysis (preprint)

Introduction: Baricitinib is a selective inhibitor of Janus kinase (JAK)1 and JAK2, which is associated with clinical improvement in non-severe COVID-19 patients. But in severe COVID-19 patients, the efficacy of baricitinib is still controversial. Methods: A propensity score-matched and retrospective study was conducted to evaluate the efficacy of baricitinib in severe COVID-19 patients requiring invasive mechanical ventilation (IMV). Results: A total number of 46 patients treated with baricitinib were included, and 44 patients were assigned to control group by propensity score matching. The mean ages were high in both group (baricitinib group vs control group: 78.80±9.04 vs 82.57±9.27), and most were unvaccinated (65.2% vs 72.7%). Baricitinib group had a higher proportion of patients with hypertension (73.9% vs 45.5%). Control group had higher level of creatine kinase-myocardial band (247.50 vs 104.50). Patients in the baricitinib group were more likely to receive nirmatrelvir/ritonavir (41.3% vs 18.2%) and intravenous immunoglobin (15.2% vs 0). Both groups reported high all-cause 28-day mortality (73.9% vs 84.1%). The use of baricitinib didn’t reduce 28-days mortality. Conclusion: The present study revealed baricitinib didn’t reduce 28-days mortality in severe COVID-19 patients on IMV. The effectiveness of baricitinib in treating patients with severe COVID-19 on IMV needs to be further investigated through future studies.

A new tractable method for generating Human Alveolar Macrophage Like cells in vitro to study lung inflammatory processes and diseases (preprint)

Alveolar macrophages (AMs) are unique lung resident cells that contact airborne pathogens and environmental particulates. The contribution of human AMs (HAM) to pulmonary diseases remains poorly understood due to difficulty in accessing them from human donors and their rapid phenotypic change during in vitro culture. Thus, there remains an unmet need for cost-effective methods for generating and/or differentiating primary cells into a HAM phenotype, particularly important for translational and clinical studies. We developed cell culture conditions that mimic the lung alveolar environment in humans using lung lipids, i.e., Infasurf (calfactant, natural bovine surfactant) and lung-associated cytokines (GM-CSF, TGF-{beta}, and IL-10) that facilitate the conversion of blood-obtained monocytes to an AM-Like (AML) phenotype and function in tissue culture. Similar to HAM, AML cells are particularly susceptible to both Mycobacterium tuberculosis and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. This study reveals the importance of alveolar space components in the development and maintenance of HAM phenotype and function, and provides a readily accessible model to study HAM in infectious and inflammatory disease processes, as well as therapies and vaccines.

Household Transmission of SARS-CoV-2 along the Evolution of Pandemic (preprint)

Over the past three years, we have gained some understanding of the transmission mechanisms of COVID-19. One of the key findings that experts have agreed on is that household transmission is an important pathway for the pandemic. However, most studies on the transmission patterns of COVID-19 focus on the community transmission only, while the equally important study on household transmission has lagged behind. We developed a stochastic dynamic model motivated by the cluster growth algorithm in Erdös–Rényi Random Graph to differentiate the COVID-19 transmission within households from that in the community by noting only a small fraction of the total susceptible population, replenished dynamically by the community transmission events, are indeed vulnerable to household transmission. Thus the model allowed us to the role and characteristics of household transmission within the full framework of virus transmission, beyond the intrinsic characteristics of household transmission. It was then applied to a comprehensive individual-level pandemic dataset collected in Yichang, China. Our findings showed that household transmission accounted for 25.1% and 38.5% of total infections before and during the lockdown, respectively, and that 80.9% of infections were unavoidable. Our model suggests that household-level contact tracing could have reduced the number of infections by over 50% and advanced the clearance date of active infection by 72 days. This model can be used to fit COVID-19 data outside Yichang or other infectious diseases, though modifications might be needed.

Single-cell multi-omic topic embedding reveals cell-type-specific and COVID-19 severity-related immune signatures (preprint)

The advent of single-cell multi-omics sequencing technology makes it possible for researchers to leverage multiple modalities for individual cells and explore cell heterogeneity. However, the high dimensional, discrete, and sparse nature of the data make the downstream analysis particularly challenging. Most of the existing computational methods for single-cell data analysis are either limited to single modality or lack flexibility and interpretability. In this study, we propose an interpretable deep learning method called multi-omic embedded topic model (moETM) to effectively perform integrative analysis of high-dimensional single-cell multimodal data. moETM integrates multiple omics data via a product-of-experts in the encoder for efficient variational inference and then employs multiple linear decoders to learn the multi-omic signatures of the gene regulatory programs. Through comprehensive experiments on public single-cell transcriptome and chromatin accessibility data (i.e., scRNA+scATAC), as well as scRNA and proteomic data (i.e., CITE-seq), moETM demonstrates superior performance compared with six state-of-the-art single-cell data analysis methods on seven publicly available datasets. By applying moETM to the scRNA+scATAC data in human peripheral blood mononuclear cells (PBMCs), we identified sequence motifs corresponding to the transcription factors that regulate immune gene signatures. Applying moETM analysis to CITE-seq data from the COVID-19 patients revealed not only known immune cell-type-specific signatures but also composite multi-omic biomarkers of critical conditions due to COVID-19, thus providing insights from both biological and clinical perspectives.

Research on Design Strategy of Mask Recycling Service Based on Behavior Environment

The global novel coronavirus pandemic has caused a surge in the use of masks worldwide. A large number of used masks that have not been properly handled enter the environment, which caused and will cause serious ecological problems. The purpose of this study is to propose a solution to the problem of mask management from the perspective of science of design, and to build a good mask recycling service design strategy through the combination of design and psychology. Firstly, based on the theory of behavioral environment and field investigation, this study analyzes the correlation between the existing mask recycling device and its recycling efficiency, user behavior psychology and environment, and studies the behavioral scene of mask recycling, and then establishes the center of design strategy implementation. Secondly, a visual guidance system is designed, as is a special recycling device for masks by color psychology and product design. Thirdly, combined with the concept of social innovation service design, the design of a mask recycling strategy is conceived, and the optimization and formulation of mask recycling strategy is demonstrated through stakeholders, user journey maps and service flow charts. Finally, the design strategy is hierarchically established, and the feasibility analysis system model of a mask recycling strategy design is constructed. The data collection is carried out through expert interviews and questionnaires, and the weight is calculated by a fuzzy analytic hierarchy process. The final output comprehensive evaluation results show that the mask recycling strategy constructed in this study has public recognition.

Global dynamics of Porcine Epidemic Diarrhea Virus evolution and transmission (preprint)

With a possible origin from bats, the alphacoronavirus Porcine epidemic diarrhea virus (PEDV) causes significant hazards and widespread epidemics in the swine population. However, the ecology, evolution, and spread of PEDV are still unclear. Here, from 149,869 fecal and intestinal tissue samples of pigs collected in an 11-year survey, we identified PEDV as the most dominant virus in diarrheal animals. Global whole genomic and evolutionary analyses of 672 PEDV strains revealed the fast-evolving PEDV genotype 2 (G2) strains as the main epidemic viruses worldwide, which seems to correlate with the use of G2-targeting vaccines. The evolving pattern of the G2 viruses presents geographic bias as they evolve tachytely in South Korea but undergo the highest recombination in China. Therefore, we clustered six PEDV haplotypes in China, whereas South Korea held five haplotypes, including a unique haplotype G. In addition, an assessment of the spatiotemporal spread route of PEDV indicates Germany and Japan as the primary hubs for PEDV dissemination in Europe and Asia, respectively. Overall, our findings provide novel insights into the epidemiology, evolution, and transmission of PEDV, and thus may lay a foundation for the prevention and control of PEDV and other coronaviruses.

Bat and bat-borne hantaviruses

Hantaviruses are important pathogenes of natural focal diseases that causes hemorrhagic fever with renal syndrome and Hantavirus pulmonary syndrome. According to the latest classification of the International Committee on Taxonomy of Viruses, hantaviruses can be divided into 53 species, 7 genera, and 4 subfamilies. Hantaviruses are widely found in Rodentia, Chiroptera, and Insectivora, and later also found in reptile, Actinopterygii, and Agnatha. There are many species of bats, which are the second largest group of mammals in the world after rodents. At present, 1 446 species have been reported, accounting for about 22% of global mammals. In addition, bats have strong flight ability and are widely distributed in all continents except Antarctica. As the host animal of viruses, bats bear a variety of viruses, and many emerging infectious pathogens such as Marburg virus, Hendra virus, and Nipah virus have been confirmed to come from bats. Bats have also been associated to Ebola virus, severe acute respiratory syndrome coronavirus, Middle East respiratory syndrome coronavirus, and severe acute respiratory syndrome coronavirus 2. In recent decades, more and more bat-borne hantaviruses have been discovered. Bats and bat-borne hantaviruses have an important research value. Therefore, this paper reviews the latest classification of Hantavirus and bat-borne hantaviruses.

Safety and immunogenicity of a broad-spectrum mosaic vaccine as a booster dose against SARS-CoV-2 Omicron and other circulating variants (preprint)

BACKGROUNDThe rising breakthrough infections caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, especially Omicron and its sub-lineages, have raised an urgent need to develop broad-spectrum vaccines against coronavirus disease 2019 (COVID-19). We have developed a mosaic-type recombinant vaccine candidate, named NVSI-06-09, having immune potentials against a broad range of SARS-CoV-2 variants. METHODSAn ongoing randomized, double-blind, controlled phase 2 trial was conducted to evaluate the safety and immunogenicity of NVSI-06-09 as a booster dose in subjects aged 18 years and older from the United Arab Emirates (UAE), who had completed two or three doses of BBIBP-CorV vaccinations at least 6 months prior to the enrollment. The participants were randomly assigned with 1:1 to receive a booster dose of NVSI-06-09 or BBIBP-CorV. The primary outcomes were immunogenicity and safety against SARS-CoV-2 Omicron variant, and the exploratory outcome was cross-immunogenicity against other circulating strains. RESULTSA total of 516 participants received booster vaccination. Interim results showed a similar safety profile between NVSI-06-09 and BBIBP-CorV booster groups, with low incidence of adverse reactions of grade 1 or 2. For immunogenicity, by day 14 after the booster vaccination, the fold rises in neutralizing antibody geometric mean titers (GMTs) from baseline level elicited by NVSI-06-09 were remarkably higher than those by BBIBP-CorV against the prototype strain (19.67 vs 4.47-fold), Omicron BA.1.1 (42.35 vs 3.78-fold), BA.2 (25.09 vs 2.91-fold), BA.4 (22.42 vs 2.69-fold), and BA.5 variants (27.06 vs 4.73-fold). Similarly, the neutralizing GMTs boosted by NVSI-06-09 against Beta and Delta variants were also 6.60-fold and 7.17-fold higher than those boosted by BBIBP-CorV. CONCLUSIONSA booster dose of NVSI-06-09 was well-tolerated and elicited broad-spectrum neutralizing responses against SARS-CoV-2 prototype strain and immune-evasive variants, including Omicron and its sub-lineages. The immunogenicity of NVSI-06-09 as a booster vaccine was superior to that of BBIBP-CorV. (Funded by LIBP and BIBP of Sinopharm; ClinicalTrials.gov number, NCT05293548).

The SARS‐CoV‐2 main protease (Mpro): Structure, function, and emerging therapies for COVID‐19

The main proteases (Mpro), also termed 3‐chymotrypsin‐like proteases (3CLpro), are a class of highly conserved cysteine hydrolases in β‐coronaviruses. Increasing evidence has demonstrated that 3CLpros play an indispensable role in viral replication and have been recognized as key targets for preventing and treating coronavirus‐caused infectious diseases, including COVID‐19. This review is focused on the structural features and biological function of the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) main protease Mpro (also known as 3CLpro), as well as recent advances in discovering and developing SARS‐CoV‐2 3CLpro inhibitors. To better understand the characteristics of SARS‐CoV‐2 3CLpro inhibitors, the inhibition activities, inhibitory mechanisms, and key structural features of various 3CLpro inhibitors (including marketed drugs, peptidomimetic, and non‐peptidomimetic synthetic compounds, as well as natural compounds and their derivatives) are summarized comprehensively. Meanwhile, the challenges in this field are highlighted, while future directions for designing and developing efficacious 3CLpro inhibitors as novel anti‐coronavirus therapies are also proposed. Collectively, all information and knowledge presented here are very helpful for understanding the structural features and inhibitory mechanisms of SARS‐CoV‐2 3CLpro inhibitors, which offers new insights or inspiration to medicinal chemists for designing and developing more efficacious 3CLpro inhibitors as novel anti‐coronavirus agents. A comprehensive summary of recent advances in SARS‐CoV‐2 3CLpro inhibitors (including marketed drugs, peptidomimetic, and non‐peptidomimetic synthetic compounds, as well as natural compounds and their derivatives), including the inhibitory activities, inhibitory mechanisms, and key structural features, provides new insights for designing and developing more efficacious 3CLpro inhibitors as broad‐spectrum anti‐coronavirus agents.

NcPath: A novel tool for visualization and enrichment analysis of human non-coding RNA and KEGG signaling pathways (preprint)

Noncoding RNAs play important roles in transcriptional processes and participate in the regulation of various biological functions, in particular miRNAs and lncRNAs. Despite their importance for several biological functions, the existing signaling pathway databases do not include information on miRNA and lncRNA. Here, we redesigned a novel pathway database named NcPath by integrating and visualizing a total of 178,308 human experimentally-validated miRNA-target interactions (MTIs), 36,537 experimentally-verified lncRNA target interactions (LTIs), and 4,879 experimentally-validated human ceRNA networks across 222 KEGG pathways (including 27 sub-categories). To expand the application potential of the redesigned NcPath database, we identified 553,523 reliable lncRNA-PCG interaction pairs by integrating co-expression relations, ceRNA relations, co-TF-binding interactions, co-Histone-modification interactions, cis-regulation relations and lncPro Tool predictions between lncRNAs and protein-coding genes. In addition, to determine the pathways in which miRNA/lncRNA targets are involved, we performed a KEGG enrichment analysis using an hypergeometric test. The NcPath database also provides information on MTIs/LTIs/ceRNA networks, PubMed IDs, gene annotations and the experimental verification method used. In summary, the NcPath database will serve as an important and continually updated platform that provides annotation and visualization of the pathways on which noncoding RNAs (miRNA and lncRNA) are involved, and provide support to multimodal noncoding RNAs enrichment analysis. The NcPath database is freely accessible at http://ncpath.pianlab.cn/.

Anxiety and depression among epilepsy patients in low-risk areas for COVID-19 in the northern part of Guizhou Province, China, during the COVID-19 pandemic

Background This study was aimed to investigate whether patients with epilepsy (PWE) have higher depression and anxiety levels than the normal population in low-risk areas for coronavirus disease 2019 (COVID-19) in the northern part of Guizhou Province, China, during the COVID-19 epidemic, to evaluate their knowledge on COVID-19, and to analyze related factors for the psychological distress of PWE at this special time. Methods The survey was conducted online from February 28, 2020 to March 7, 2020 via a questionnaire. PWE from the outpatient clinic of epilepsy of the Affiliated Hospital of Zunyi Medical University, and healthy people matched for age and sex, participated in this study. Mental health was assessed via a generalized anxiety self-rating scale (GAD-7) and the self-rating depression scale (PHQ-9). The knowledge of COVID-19 in both groups was investigated. Results There were no significant differences in the general demographics between the PWE and healthy control groups. The scores of PHQ-9 (P < 0.01) and GAD-7 (P < 0.001) were higher in the PWE group than in the healthy group. There was a significant difference in the proportions of respondents with different severities of depression and anxiety, between the two groups, which revealed significantly higher degree of depression and anxiety in PWE than in healthy people (P = 0, P = 0). Overwhelming awareness and stressful concerns for the pandemic and female patients with epilepsy were key factors that affect the level of anxiety and depression in PWE. Further, the PWE had less accurate knowledge of COVID-19 than healthy people (P < 0.001). There was no statistically significant difference between the two groups in the knowledge of virus transmission route, incubation period, susceptible population, transmission speed, clinical characteristics, and isolation measures on COVID-19 (P > 0.05). PWE knew less about some of the prevention and control measures of COVID-19 than healthy people. Conclusions During the COVID-19 epidemic, excessive attention to the epidemic and the female sex are factors associated with anxiety and depression in PWE, even in low-risk areas.

Machine Learning for Identifying Data-Driven Subphenotypes of Incident Post-Acute SARS-CoV-2 Infection Conditions with Large Scale Electronic Health Records: Findings from the RECOVER Initiative (preprint)

The post-acute sequelae of SARS-CoV-2 infection (PASC) refers to a broad spectrum of symptoms and signs that are persistent, exacerbated, or newly incident in the post-acute SARS-CoV-2 infection period of COVID-19 patients. Most studies have examined these conditions individually without providing concluding evidence on co-occurring conditions. To answer this question, this study leveraged electronic health records (EHRs) from two large clinical research networks from the national Patient-Centered Clinical Research Network (PCORnet) and investigated patients’ newly incident diagnoses that appeared within 30 to 180 days after a documented SARS-CoV-2 infection. Through machine learning, we identified four reproducible subphenotypes of PASC dominated by blood and circulatory system, respiratory, musculoskeletal and nervous system, and digestive system problems, respectively. We also demonstrated that these subphenotypes were associated with distinct patterns of patient demographics, underlying conditions present prior to SARS-CoV-2 infection, acute infection phase severity, and use of new medications in the post-acute period. Our study provides novel insights into the heterogeneity of PASC and can inform stratified decision-making in the treatment of COVID-19 patients with PASC conditions.

Optimization of Multisource Dynamic Model in TBO

When extracting flight data from airport terminal area, there are matters such as large volume, unclear features, and similar trend in time series. In order to deal with the related issues and to optimize the description, by combining with the TBO (Trajectory-Based Operation), an application proposed by the ICAO (International Civil Aviation Organization) in ASBU (Aviation System Block Upgrade), using multisource dynamic model to establish 4DDW (4D dynamic warping) algorithm, the multisource modeling integrated with evaluation system is proposed to realize the flight path optimization with time series characteristics and accord with the interval concept. The calculation results show that 4DDW can obtain the optimal solution for multiprofile calculation of TBO by comparing the composite trajectory deviation values and time dimension planning using the buffer and threshold values recommended by ICAO in airspace planning and flight procedure design. The results meet the requirements of high accuracy and convergence features of spatial waypoints and can improve the airport operation standards and terminal area capacity.

Optimize Data-Driven Multi-Agent Simulation for COVID-19 Transmission (preprint)

Background: Multi-Agent Simulation is an essential technique for exploring complex systems. In researches of contagious diseases, it is widely exploited to analyze their spread mechanisms, especially for preventing COVID-19. Nowadays, transmission dynamics and interventions of COVID-19 have been elaborately established by this method, but its computation performance is seldomly concerned. As it usually suffers from inadequate CPU utilization and pour data locality, optimizing the performance is challenging. Results: This paper explores approaches to optimize multi-agent simulation for COVID-19 disease. The focus of this work is on the algorithm and data structure designs for improving performance, as well as its parallelisation strategies. We propose two successive methods to optimize the computation. We construct a case-focused iteration algorithm to improve data locality, and create a thread-safe data-mapping paradigm called hierachical hash table to accelerate hash operations. Conclusions: Our performance results demonstrate capabilities of these methods exhibiting significant improvements of system performance. The case-focused method degrades $\sim 90 \%$ cache references and achieves $\times 4.3$ speedup. Hierachical hash table can further boost computation speed by 47\%. And parallel implementation with 20 threads on CPU achieves $\times 81$ speedup consequently.

Lyophilized mRNA-lipid nanoparticles vaccine with long-term stability and high antigenicity against SARS-CoV-2 (preprint)

Advanced mRNA vaccines play vital roles against SARS-CoV-2. However, due to the poor stability, most current mRNA delivery platforms need to be stored at -20 {degrees}C or -70 {degrees}C. Here we present lyophilized thermostable mRNA loaded lipid nanoparticles, which could be stored at room temperature with long-term stability. We demonstrate the applicability of lyophilization techniques to different mRNA sequences and lipid components. Three lyophilized vaccines targeting wild-type, Delta and Omicron SARS-CoV-2 variant were prepared and demonstrated to be able induce high-level of IgG titer and neutralization response. In the Delta challenge in vivo experiment, the lyophilized mRNA vaccine successfully protected the mice from infection and clear the virus. This lyophilization platform could significantly improve the accessibility of mRNA vaccine or therapeutics, particularly in remote regions.

A Multivariate Multi-Step LSTM Forecasting Model For Tuberculosis Incidence With Model Explanation In Liaoning Province, China (preprint)

Background: In addition to COVID-19, tuberculosis (TB) is the respiratory infectious disease with the highest incidence in China. We aim to design a series of forecasting models and find the factors that affect the incidence of TB, thereby improving the accuracy of the incidence prediction. Results: : In this paper, we developed a new interpretable prediction system based on the multivariate multi-step Long Short-Term Memory (LSTM) model and SHapley Additive exPlanation (SHAP) method. Moreover, four accuracy measures are introduced into the system: Root Mean Square Error, Mean Absolute Error, Mean Absolute Percentage Error, and symmetric Mean Absolute Percentage Error. Meanwhile, the Autoregressive Integrated Moving Average (ARIMA) model and seasonal ARIMA model are established. The multi-step ARIMA-LSTM model is proposed for the first time to examine the performance of each model in the short, medium, and long term, respectively. Compared with the ARIMA model, each error of the multivariate 2-step LSTM model is reduced by 12.92%, 15.94%, 15.97%, and 14.81% in the short term. The 3-step ARIMA-LSTM model achieved excellent performance, with each error decreased to 15.19%, 33.14%, 36.79%, and 29.76% in the medium and long term. We provide the local and global explanation of the multivariate single-step LSTM model in the field of incidence prediction, pioneering. Conclusions: : The multivariate 2-step LSTM model is suitable for short-term forecasts, and the 3-step ARIMA-LSTM model is appropriate for medium and long-term forecasts. In addition, the prediction effect was better than similar TB incidence forecasting models. The SHAP results indicate that the five most crucial features are maximum temperature, average relative humidity, local financial budget, monthly sunshine percentage, and sunshine hours.

Diverse pathogens activate the host RIDD pathway to subvert BLOS1-directed immune defense (preprint)

The phagocytosis and destruction of pathogens in lysosomes constitute central elements of innate immune defense. Here, we show that Brucella , the causative agent of brucellosis, the most prevalent bacterial zoonosis globally, subverts this immune defense pathway by activating regulated IRE1α-dependent decay (RIDD) of mRNAs encoding BLOS1, a protein that promotes endosome-lysosome fusion. RIDD-deficient cells and mice harboring a RIDD-incompetent variant of IRE1α were resistant to infection. Non-functional Blos1 struggled to assemble the BLOC-1-related complex (BORC), resulting in differential recruitment of BORC-related lysosome trafficking components, perinuclear trafficking of Brucella -containing vacuoles (BCVs), and enhanced susceptibility to infection. The RIDD-resistant Blos1 variant maintains the integrity of BORC and a higher-level association of BORC-related components that promote centrifugal lysosome trafficking, resulting in enhanced BCV peripheral trafficking and lysosomal-destruction, and resistance to infection. These findings demonstrate that host RIDD activity on BLOS1 regulates Brucella intracellular parasitism by disrupting BORC-directed lysosomal trafficking. Notably, coronavirus MHV also subverted the RIDD-BLOS1 axis to promote intracellular replication. Our work therefore establishes BLOS1 as a novel immune defense factor whose activity is hijacked by diverse pathogens.