Genomic signatures underlying the oogenesis of the ectoparasitic mite Varroa destructor on its new host Apis mellifera.

INTRODUCTION: Host shift of parasites may have devastating effects on the novel hosts. One remarkable example is that of the ectoparasitic mite Varroa destructor, which has shifted its host from Eastern honey bees (Apis cerana) to Western honey bees (Apis mellifera) and posed a global threat to apiculture. OBJECTIVES: To identify the genetic factors underlying the reproduction of host-shifted V. destructor on the new host. METHODS: Genome sequencing was conducted to construct the phylogeny of the host-shifted and non-shifted mites and to screen for genomic signatures that differentiated them. Artificial infestation experiment was conducted to compare the reproductive difference between the mites, and transcriptome sequencing was conducted to find differentially expressed genes (DEGs) during the reproduction process. RESULTS: The host-shifted and non-shifted V. destructor mites constituted two genetically distinct lineages, with 15,362 high-FST SNPs identified between them. Oogenesis was upregulated in host-shifted mites on the new host A. mellifera relative to non-shifted mites. The transcriptomes of the host-shifted and non-shifted mites differed significantly as early as 1h post-infestation. The DEGs were associated with nine genes carrying nonsynonymous high-FST SNPs, including mGluR2-like, Lamb2-like and Vitellogenin 6-like, which were also differentially expressed, and eIF4G, CG5800, Dap160 and Sas10, which were located in the center of the networks regulating the DEGs based on protein-protein interaction analysis. CONCLUSIONS: The annotated functions of these genes were all associated with oogenesis. These genes appear to be the key genetic determinants of the oogenesis of host-shifted mites on the new host. Further study of these candidate genes will help elucidate the key mechanism underlying the success of host shifts of V. destructor.

Toward accurate diagnosis and surveillance of bacterial infections using enhanced strain-level metagenomic next-generation sequencing of infected body fluids.

Metagenomic next-generation sequencing (mNGS) enables comprehensive pathogen detection and has become increasingly popular in clinical diagnosis. The distinct pathogenic traits between strains require mNGS to achieve a strain-level resolution, but an equivocal concept of 'strain' as well as the low pathogen loads in most clinical specimens hinders such strain awareness. Here we introduce a metagenomic intra-species typing (MIST) tool (https://github.com/pandafengye/MIST), which hierarchically organizes reference genomes based on average nucleotide identity (ANI) and performs maximum likelihood estimation to infer the strain-level compositional abundance. In silico analysis using synthetic datasets showed that MIST accurately predicted the strain composition at a 99.9% average nucleotide identity (ANI) resolution with a merely 0.001× sequencing depth. When applying MIST on 359 culture-positive and 359 culture-negative real-world specimens of infected body fluids, we found the presence of multiple-strain reached considerable frequencies (30.39%-93.22%), which were otherwise underestimated by current diagnostic techniques due to their limited resolution. Several high-risk clones were identified to be prevalent across samples, including Acinetobacter baumannii sequence type (ST)208/ST195, Staphylococcus aureus ST22/ST398 and Klebsiella pneumoniae ST11/ST15, indicating potential outbreak events occurring in the clinical settings. Interestingly, contaminations caused by the engineered Escherichia coli strain K-12 and BL21 throughout the mNGS datasets were also identified by MIST instead of the statistical decontamination approach. Our study systemically characterized the infected body fluids at the strain level for the first time. Extension of mNGS testing to the strain level can greatly benefit clinical diagnosis of bacterial infections, including the identification of multi-strain infection, decontamination and infection control surveillance.

Multi-Epitope Vaccine Design Using an Immunoinformatic Approach for SARS-CoV-2.

Through 4 June 2021, COVID-19 has caused over 172.84 million cases of infection and 3.71 million deaths worldwide. Due to its rapid dissemination and high mutation rate, it is essential to develop a vaccine harboring multiple epitopes and efficacious against multiple variants to prevent the immune escape of SARS-CoV-2. An in silico approach based on the viral genome was applied to identify 19 high-immunogenic B-cell epitopes and 499 human leukocyte antigen (HLA)-restricted T-cell epitopes. Thirty multi-epitope peptide vaccines were designed by iNeo-Suite and manufactured by solid-phase synthesis. Docking analysis confirmed stable hydrogen bonds of epitopes with their corresponding HLA alleles. When four peptide candidates derived from the spike protein of SARS-CoV-2 were selected to immunize mice, a significantly larger amount of total IgG in serum, as well as an increase of CD19+ cells in the inguinal lymph nodes, were observed in the peptide-immunized mice compared to the control. The ratios of IFN-γ-secreting lymphocytes in CD4+ or CD8+ T-cells in the peptide-immunized mice were higher than those in the control mice. There were also a larger number of IFN-γ-secreting T-cells in the spleens of peptide-immunized mice. The peptide vaccines in this study successfully elicited antigen-specific humoral and cellular immune responses in mice. To further validate the safety and efficacy of this vaccine, animal studies using a primate model, as well as clinical trials in humans, are required.

A Novel Risk Model Based on Lipid Metabolism-Associated Genes Predicts Prognosis and Indicates Immune Microenvironment in Breast Cancer.

BACKGROUND: Breast cancer (BRCA) is the most common tumor in women, and lipid metabolism involvement has been demonstrated in its tumorigenesis and development. However, the role of lipid metabolism-associated genes (LMAGs) in the immune microenvironment and prognosis of BRCA remains unclear. METHODS: A total of 1076 patients with BRCA were extracted from The Cancer Genome Atlas database and randomly assigned to the training cohort (n = 760) or validation cohort (n = 316). Kaplan-Meier analysis was used to assess differences in survival. Consensus clustering was performed to categorize the patients with BRCA into subtypes. Using multivariate Cox regression analysis, an LMAG-based prognostic risk model was constructed from the training cohort and validated using the validation cohort. The immune microenvironment was evaluated using the ESTIMATE and tumor immune estimation resource algorithms, CIBERSORT, and single sample gene set enrichment analyses. RESULTS: Consensus clustering classified the patients with BRCA into two subgroups with significantly different overall survival rates and immune microenvironments. Better prognosis was associated with high immune infiltration. The prognostic risk model, based on four LMAGs (MED10, PLA2G2D, CYP4F11, and GPS2), successfully stratified the patients into high- and low-risk groups in both the training and validation sets. High risk scores predicted poor prognosis and indicated low immune status. Subgroup analysis suggested that the risk model was an independent predictor of prognosis in BRCA. CONCLUSION: This study demonstrated, for the first time, that LMAG expression plays a crucial role in BRCA. The LMAG-based risk model successfully predicted the prognosis and indicated the immune microenvironment of patients with BRCA. Our study may provide inspiration for further research on BRCA pathomechanisms.

Phylogeny, recombination, and invasiveness of group B Streptococcus revealed by genomic comparisons of its global strains.

Capsular polysaccharide (CPS) genes and pilus islands encode important virulence factors for group B Streptococcus (GBS) genomes. This study aims to detect phylogenetic inconsistency in CPS genes and pilus islands in GBSs and to explore its relationship with invasiveness. A total of 1016 GBS genomes were downloaded from the NCBI public database. The multi-locus sequence typing (MLST) and Bayesian analysis of Population Structure (BAPS) analyses were both conducted for phylogeny construction. Serotyping and pilus typing were determined in silico using the genomic sequences. The CPS and pilus typing results were generally consistent with MLST and BAPS clustering. GBS isolates of serotype II and of the PI-1 + PI-2b and PI-2a types were more prone to phylogenetic inconsistency than the others. Isolates of serotype Ib and of PI-1 + PI-2a were more likely to appear as colonizing strains, whereas PI-2b was more likely to appear in invasive strains. For serotype V, phylogenetic inconsistency occurred more commonly in colonizing isolates, while for serotype III, the opposite occurred. The present study profiles for the first time the phylogenetic inconsistency of CPS genes and pilus islands in global GBS isolates, which is helpful for infection control and the development of new vaccines for the prevention of GBS occurrence.

BacWGSTdb 2.0: a one-stop repository for bacterial whole-genome sequence typing and source tracking.

An increasing prevalence of hospital acquired infections and foodborne illnesses caused by pathogenic and multidrug-resistant bacteria has stimulated a pressing need for benchtop computational techniques to rapidly and accurately classify bacteria from genomic sequence data, and based on that, to trace the source of infection. BacWGSTdb (http://bacdb.org/BacWGSTdb) is a free publicly accessible database we have developed for bacterial whole-genome sequence typing and source tracking. This database incorporates extensive resources for bacterial genome sequencing data and the corresponding metadata, combined with specialized bioinformatics tools that enable the systematic characterization of the bacterial isolates recovered from infections. Here, we present BacWGSTdb 2.0, which encompasses several major updates, including (i) the integration of the core genome multi-locus sequence typing (cgMLST) approach, which is highly scalable and appropriate for typing isolates belonging to different lineages; (ii) the addition of a multiple genome analysis module that can process dozens of user uploaded sequences in a batch mode; (iii) a new source tracking module for comparing user uploaded plasmid sequences to those deposited in the public databases; (iv) the number of species encompassed in BacWGSTdb 2.0 has increased from 9 to 20, which represents bacterial pathogens of medical importance; (v) a newly designed, user-friendly interface and a set of visualization tools for providing a convenient platform for users are also included. Overall, the updated BacWGSTdb 2.0 bears great utility in continuing to provide users, including epidemiologists, clinicians and bench scientists, with a one-stop solution to bacterial genome sequence analysis.

Complete genome sequence of Salmonella enterica serovar Sendai shows H antigen convergence with S. Miami and recent divergence from S. Paratyphi A.

BACKGROUND: Salmonella enterica consists of over 2500 serovars and displays dichotomy in disease manifestations and host range. Except for the enrichment of pseudogenes in genomes for human-restricted serovars, no hallmark has been identified to distinguish those with host-generalist serovars. The serovar Sendai is rare and human-restricted. Notably, it exhibits an O, H antigen formula as the host-generalist serovar Miami. RESULTS: We sequenced the complete genomes of the two serovars Sendai and Miami. Analysis at both nucleotide identity and gene content level demonstrates the same high degree of similarity between Sendai and Paratyphi A, but their distinct CRISPR spacers suggests a recent divergence history. A frameshift mutation occurred in rfbE for the entire lineage of Paratyphi A but not in Sendai, which may explain their distinct O antigens. The nucleotide sequence of Miami's fliC is nearly identical to Sendai's. The incongruent phylogeny of this gene with that of the adjacent genes suggests a recombination event responsible for Sendai and Miami possessing the same H antigen. Sendai's even greater number of pseudogenes than that of Paratyphi A and Typhi indicates its undergoing continued genomic degradation. The phylogenetically distinct human-restricted serovars/strains share pseudogenes with the same inactivation mutations, therefore suggesting that recombination may have occurred and have been facilitated by their overlap in niches. CONCLUSIONS: Analysis of Sendai's genome and comparison with others reflect the finer evolutionary signatures of Salmonella in the process of niches changing from facultative to obligate parasite.