Characterizing the Major Structural Variant Alleles of the Human Genome.

In order to provide a comprehensive resource for human structural variants (SVs), we generated long-read sequence data and analyzed SVs for fifteen human genomes. We sequence resolved 99,604 insertions, deletions, and inversions including 2,238 (1.6 Mbp) that are shared among all discovery genomes with an additional 13,053 (6.9 Mbp) present in the majority, indicating minor alleles or errors in the reference. Genotyping in 440 additional genomes confirms the most common SVs in unique euchromatin are now sequence resolved. We report a ninefold SV bias toward the last 5 Mbp of human chromosomes with nearly 55% of all VNTRs (variable number of tandem repeats) mapping to this portion of the genome. We identify SVs affecting coding and noncoding regulatory loci improving annotation and interpretation of functional variation. These data provide the framework to construct a canonical human reference and a resource for developing advanced representations capable of capturing allelic diversity.

Beyond the Human Genome Project: The Age of Complete Human Genome Sequences and Pangenome References.

The Human Genome Project was an enormous accomplishment, providing a foundation for countless explorations into the genetics and genomics of the human species. Yet for many years, the human genome reference sequence remained incomplete and lacked representation of human genetic diversity. Recently, two major advances have emerged to address these shortcomings: complete gap-free human genome sequences, such as the one developed by the Telomere-to-Telomere Consortium, and high-quality pangenomes, such as the one developed by the Human Pangenome Reference Consortium. Facilitated by advances in long-read DNA sequencing and genome assembly algorithms, complete human genome sequences resolve regions that have been historically difficult to sequence, including centromeres, telomeres, and segmental duplications. In parallel, pangenomes capture the extensive genetic diversity across populations worldwide. Together, these advances usher in a new era of genomics research, enhancing the accuracy of genomic analysis, paving the path for precision medicine, and contributing to deeper insights into human biology.

From tradition to innovation: conventional and deep learning frameworks in genome annotation.

Following the milestone success of the Human Genome Project, the 'Encyclopedia of DNA Elements (ENCODE)' initiative was launched in 2003 to unearth information about the numerous functional elements within the genome. This endeavor coincided with the emergence of numerous novel technologies, accompanied by the provision of vast amounts of whole-genome sequences, high-throughput data such as ChIP-Seq and RNA-Seq. Extracting biologically meaningful information from this massive dataset has become a critical aspect of many recent studies, particularly in annotating and predicting the functions of unknown genes. The core idea behind genome annotation is to identify genes and various functional elements within the genome sequence and infer their biological functions. Traditional wet-lab experimental methods still rely on extensive efforts for functional verification. However, early bioinformatics algorithms and software primarily employed shallow learning techniques; thus, the ability to characterize data and features learning was limited. With the widespread adoption of RNA-Seq technology, scientists from the biological community began to harness the potential of machine learning and deep learning approaches for gene structure prediction and functional annotation. In this context, we reviewed both conventional methods and contemporary deep learning frameworks, and highlighted novel perspectives on the challenges arising during annotation underscoring the dynamic nature of this evolving scientific landscape.

PB-LKS: a python package for predicting phage-bacteria interaction through local K-mer strategy.

Bacteriophages can help the treatment of bacterial infections yet require in-silico models to deal with the great genetic diversity between phages and bacteria. Despite the tolerable prediction performance, the application scope of current approaches is limited to the prediction at the species level, which cannot accurately predict the relationship of phages across strain mutants. This has hindered the development of phage therapeutics based on the prediction of phage-bacteria relationships. In this paper, we present, PB-LKS, to predict the phage-bacteria interaction based on local K-mer strategy with higher performance and wider applicability. The utility of PB-LKS is rigorously validated through (i) large-scale historical screening, (ii) case study at the class level and (iii) in vitro simulation of bacterial antiphage resistance at the strain mutant level. The PB-LKS approach could outperform the current state-of-the-art methods and illustrate potential clinical utility in pre-optimized phage therapy design.

A fully sequenced collection of homozygous EMS mutants for forward and reverse genetic screens in Arabidopsis thaliana.

Genetic screens are powerful tools for biological research and are one of the reasons for the success of the thale cress Arabidopsis thaliana as a research model. Here, we describe the whole-genome sequencing of 871 Arabidopsis lines from the Homozygous EMS Mutant (HEM) collection as a novel resource for forward and reverse genetics. With an average 576 high-confidence mutations per HEM line, over three independent mutations altering protein sequences are found on average per gene in the collection. Pilot reverse genetics experiments on reproductive, developmental, immune and physiological traits confirmed the efficacy of the tool for identifying both null, knockdown and gain-of-function alleles. The possibility of conducting subtle repeated phenotyping and the immediate availability of the mutations will empower forward genetic approaches. The sequence resource is searchable with the ATHEM web interface (https://lipm-browsers.toulouse.inra.fr/pub/ATHEM/), and the biological material is distributed by the Versailles Arabidopsis Stock Center.

Zero-shot-capable identification of phage-host relationships with whole-genome sequence representation by contrastive learning.

Accurately identifying phage-host relationships from their genome sequences is still challenging, especially for those phages and hosts with less homologous sequences. In this work, focusing on identifying the phage-host relationships at the species and genus level, we propose a contrastive learning based approach to learn whole-genome sequence embeddings that can take account of phage-host interactions (PHIs). Contrastive learning is used to make phages infecting the same hosts close to each other in the new representation space. Specifically, we rephrase whole-genome sequences with frequency chaos game representation (FCGR) and learn latent embeddings that 'encapsulate' phages and host relationships through contrastive learning. The contrastive learning method works well on the imbalanced dataset. Based on the learned embeddings, a proposed pipeline named CL4PHI can predict known hosts and unseen hosts in training. We compare our method with two recently proposed state-of-the-art learning-based methods on their benchmark datasets. The experiment results demonstrate that the proposed method using contrastive learning improves the prediction accuracy on known hosts and demonstrates a zero-shot prediction capability on unseen hosts. In terms of potential applications, the rapid pace of genome sequencing across different species has resulted in a vast amount of whole-genome sequencing data that require efficient computational methods for identifying phage-host interactions. The proposed approach is expected to address this need by efficiently processing whole-genome sequences of phages and prokaryotic hosts and capturing features related to phage-host relationships for genome sequence representation. This approach can be used to accelerate the discovery of phage-host interactions and aid in the development of phage-based therapies for infectious diseases.

An increased prevalence of carbapenem-resistant hypervirulent Klebsiella pneumoniae associated with the COVID-19 pandemic.

BACKGROUND: Klebsiella pneumoniae (Kp) is a common community-acquired and nosocomial pathogen. Carbapenem-resistant and hypervirulent (CR-hvKp) variants can emerge rapidly within healthcare facilities and impacted by other infectious agents such as COVID-19 virus. METHODS: To understand the impact of COVID-19 virus on the prevalence of CR-hvKp, we accessed Kp genomes with corresponding metadata from GenBank. Sequence types (STs), antimicrobial resistance genes, and virulence genes, and those scores and CR-hvKp were identified. We analyzed population diversity and phylogenetic characteristics of five most common STs, measured the prevalence of CR-hvKp, identified CR-hvKp subtypes, and determined associations between carbapenem resistance gene subtypes with STs and plasmid types. These variables were compared pre- and during the COVID-19 pandemic. FINDINGS: The proportion of CR-hvKp isolates increased within multiple STs in different continents during the COVID-19 pandemic and persistent CR-hvKp subtypes were found in common STs. blaKPC was dominant in CG258, blaKPC-2 was detected in 97 % of the ST11 CR-hvKp, blaNDM subtypes were prominent in ST147 (87.4 %) and ST307 (70.8 %); blaOXA-48 and its subtypes were prevalent in ST15 (80.5 %). The possession of carbapenemase genes was different among subclades from different origins in different periods of time within each ST. IncFIB/IncHI1B hybrid plasmids contained virulence genes and carbapenemase genes and were predominant in ST147 (67.37 %) and ST307 (56.25 %). INTERPRETATION: The prevalence of CR-hvKp increased during the COVID-19 pandemic, which was evident by an increase in local endemic clones. This process was facilitated by the convergence of plasmids containing carbapenemase genes and virulence genes. These findings have implications for the appropriate use of antimicrobials and infection prevention and control during outbreaks of respiratory viruses and pandemic management.

Spatial scale of tuberculosis transmission in Lima, Peru.

Spatially targeted interventions may be effective alternatives to individual or population-based prevention strategies against tuberculosis (TB). However, their efficacy may depend on the mechanisms that lead to geographically constrained hotspots. Local TB incidence may reflect high levels of local transmission; conversely, they may point to frequent travel of community members to high-risk areas. We used whole-genome sequencing to explore patterns of TB incidence and transmission in Lima, Peru. Between 2009 and 2012, we recruited incident pulmonary TB patients and their household contacts, whom we followed for the occurrence of TB disease. We used whole-genome sequences of 2,712 Mycobacterial tuberculosis isolates from 2,440 patients to estimate pariwise genomic distances and compared these to the spatial distance between patients' residences. Genomic distances increased rapidly as spatial distances increased and remained high beyond 2 km of separation. Next, we divided the study catchment area into 1 × 1 km grid-cell surface units and used household spatial coordinates to locate each TB patient to a specific cell. We estimated cell-specific transmission by calculating the proportion of patients in each cell with a pairwise genomic distance of 10 or fewer single-nucleotide polymorphisms. We found that cell-specific TB incidence and local transmission varied widely but that cell-specific TB incidence did not correlate closely with our estimates of local transmission (Cohen's k = 0.27). These findings indicate that an understanding of the spatial heterogeneity in the relative proportion of TB due to local transmission may help guide the implementation of spatially targeted interventions.

Genome characteristics and the ODV proteome of a second distinct alphabaculovirus from Spodoptera litura.

BACKGROUND: Spodoptera litura is a harmful pest that feeds on more than 80 species of plants, and can be infected and killed by Spodoptera litura nucleopolyhedrovirus (SpltNPV). SpltNPV-C3 is a type C SpltNPV clone, that was observed and collected in Japan. Compared with type A or type B SpltNPVs, SpltNPV-C3 can cause the rapid mortality of S. litura larvae. METHODS: In this study, occlusion bodies (OBs) and occlusion-derived viruses (ODVs) of SpltNPV-C3 were purified, and OBs were observed by scanning electron microscopy (SEM). ODVs were observed under a transmission electron microscope (TEM). RESULTS: Both OBs and ODVs exhibit morphological characteristics typical of nucleopolyhedroviruses (NPVs).The genome of SpltNPV-C3 was sequenced and analyzed; the total length was 148,634 bp (GenBank accession 780,426,which was submitted as SpltNPV-II), with a G + C content of 45%. A total of 149 predicted ORFs were found. A phylogenetic tree of 90 baculoviruses was constructed based on core baculovirus genes. LC‒MS/MS was used to analyze the proteins of SpltNPV-C3; 34 proteins were found in the purified ODVs, 15 of which were core proteins. The structure of the complexes formed by per os infectivity factors 1, 2, 3 and 4 (PIF-1, PIF-2, PIF-3 and PIF-4) was predicted with the help of the AlphaFold multimer tool and predicted conserved sequences in PIF-3. SpltNPV-C3 is a valuable species because of its virulence, and the analysis of its genome and proteins in this research will be beneficial for pest control efforts.

Genomic analysis uncovers novel candidate genes related to adaptation to tropical climates and milk production traits in native goats.

BACKGROUND: Since domestication, both evolutionary forces and human selection have played crucial roles in producing adaptive and economic traits, resulting in animal breeds that have been selected for specific climates and different breeding goals. Pakistani goat breeds have acquired genomic adaptations to their native climate conditions, such as tropical and hot climates. In this study, using next-generation sequencing data, we aimed to assess the signatures of positive selection in three native Pakistani goats, known as milk production breeds, that have been well adapted to their local climate. RESULTS: To explore the genomic relationship between studied goat populations and their population structure, whole genome sequence data from native goat populations in Pakistan (n = 26) was merged with available worldwide goat genomic data (n = 184), resulting in a total dataset of 210 individuals. The results showed a high genetic correlation between Pakistani goats and samples from North-East Asia. Across all populations analyzed, a higher linkage disequilibrium (LD) level (- 0.59) was found in the Pakistani goat group at a genomic distance of 1 Kb. Our findings from admixture analysis (K = 5 and K = 6) showed no evidence of shared genomic ancestry between Pakistani goats and other goat populations from Asia. The results from genomic selection analysis revealed several candidate genes related to adaptation to tropical/hot climates (such as; KITLG, HSPB9, HSP70, HSPA12B, and HSPA12B) and milk production related-traits (such as IGFBP3, LPL, LEPR, TSHR, and ACACA) in Pakistani native goat breeds. CONCLUSIONS: The results from this study shed light on the structural variation in the DNA of the three native Pakistani goat breeds. Several candidate genes were discovered for adaptation to tropical/hot climates, immune responses, and milk production traits. The identified genes could be exploited in goat breeding programs to select efficient breeds for tropical/hot climate regions.

Unveiling biosynthetic potential of an Arctic marine-derived strain Aspergillus sydowii MNP-2.

BACKGROUND: A growing number of studies have demonstrated that the polar regions have the potential to be a significant repository of microbial resources and a potential source of active ingredients. Genome mining strategy plays a key role in the discovery of bioactive secondary metabolites (SMs) from microorganisms. This work highlighted deciphering the biosynthetic potential of an Arctic marine-derived strain Aspergillus sydowii MNP-2 by a combination of whole genome analysis and antiSMASH as well as feature-based molecular networking (MN) in the Global Natural Products Social Molecular Networking (GNPS). RESULTS: In this study, a high-quality whole genome sequence of an Arctic marine strain MNP-2, with a size of 34.9 Mb was successfully obtained. Its total number of genes predicted by BRAKER software was 13,218, and that of non-coding RNAs (rRNA, sRNA, snRNA, and tRNA) predicted by using INFERNAL software was 204. AntiSMASH results indicated that strain MNP-2 harbors 56 biosynthetic gene clusters (BGCs), including 18 NRPS/NRPS-like gene clusters, 10 PKS/PKS-like gene clusters, 8 terpene synthse gene clusters, 5 indole synthase gene clusters, 10 hybrid gene clusters, and 5 fungal-RiPP gene clusters. Metabolic analyses of strain MNP-2 grown on various media using GNPS networking revealed its great potential for the biosynthesis of bioactive SMs containing a variety of heterocyclic and bridge-ring structures. For example, compound G-8 exhibited a potent anti-HIV effect with an IC50 value of 7.2 nM and an EC50 value of 0.9 nM. Compound G-6 had excellent in vitro cytotoxicities against the K562, MCF-7, Hela, DU145, U1975, SGC-7901, A549, MOLT-4, and HL60 cell lines, with IC50 values ranging from 0.10 to 3.3 µM, and showed significant anti-viral (H1N1 and H3N2) activities with IC50 values of 15.9 and 30.0 µM, respectively. CONCLUSIONS: These findings definitely improve our knowledge about the molecular biology of genus A. sydowii and would effectively unveil the biosynthetic potential of strain MNP-2 using genomics and metabolomics techniques.

Genome analysis of Shewanella putrefaciens 4H revealing the potential mechanisms for the chromium remediation.

Microbial remediation of heavy metal polluted environment is ecofriendly and cost effective. Therefore, in the present study, Shewanella putrefaciens stain 4H was previously isolated by our group from the activated sludge of secondary sedimentation tank in a dyeing wastewater treatment plant. The bacterium was able to reduce chromate effectively. The strains showed significant ability to reduce Cr(VI) in the pH range of 8.0 to 10.0 (optimum pH 9.0) and 25-42 ℃ (optimum 30 ℃) and were able to reduce 300 mg/L of Cr(VI) in 72 h under parthenogenetic anaerobic conditions. In this paper, the complete genome sequence was obtained by Nanopore sequencing technology and analyzed chromium metabolism-related genes by comparative genomics The genomic sequence of S. putrefaciens 4H has a length of 4,631,110 bp with a G + C content of 44.66% and contains 4015 protein-coding genes and 3223,  2414, 2343 genes were correspondingly annotated into the COG, KEGG, and GO databases. The qRT-PCR analysis showed that the expression of chrA, mtrC, and undA genes was up-regulated under Cr(VI) stress. This study explores the Chromium Metabolism-Related Genes of S. putrefaciens 4H and will help to deepen our understanding of the mechanisms of Cr(VI) tolerance and reduction in this strain, thus contributing to the better application of S. putrefaciens 4H in the field of remediation of chromium-contaminated environments.

Analysis of the complete genome sequence of Paenibacillus sp. lzh-N1 reveals its antagonistic ability.

BACKGROUND: Plant diseases caused by pathogenic fungi are devastating. However, commonly used fungicides are harmful to the environment, and some are becoming ineffective due to fungal resistance. Therefore, eco-friendly biological methods to control pathogenic fungi are urgently needed. RESULTS: In this study, a strain, Paenibacillus sp. lzh-N1, that could inhibit the growth of the pathogenic fungus Mycosphaerella sentina (Fr) Schrorter was isolated from the rhizosphere soil of pear trees, and the complete genome sequence of the strain was obtained, annotated, and analyzed to reveal the genetic foundation of its antagonistic ability. The entire genome of this strain contained a circular chromosome of 5,641,488 bp with a GC content of 45.50%. The results of species identification show that the strain belongs to the same species as P. polymyxa Sb3-1 and P. polymyxa CJX518. Sixteen secondary metabolic biosynthetic gene clusters were predicted by antiSMASH, including those of the antifungal peptides fusaricidin B and paenilarvins. In addition, biofilm formation-related genes containing two potential gene clusters for cyclic lactone autoinducer, a gene encoding S-ribosylhomocysteine lyase (LuxS), and three genes encoding exopolysaccharide biosynthesis protein were identified. CONCLUSIONS: Antifungal peptides and glucanase biosynthesized by Paenibacillus sp. lzh-N1 may be responsible for its antagonistic effect. Moreover, quorum sensing systems may influence the biocontrol activity of this strain directly or indirectly.

Genomic and transcriptomic landscape to decipher the genetic basis of hyperpigmentation in Lanping black-boned sheep (Ovis aries).

BACKGROUND: Lanping black-boned sheep (LPB) represent a distinctive mammalian species characterized by hyperpigmentation, resulting in black bone and muscle features, in contrast to their conventional counterparts exhibiting red muscle and white bone. The genetic basis underlying LPB hyperpigmentation has remained enigmatic. METHODS: In this study, we conducted whole-genome sequencing of 100 LPB and 50 Lanping normal sheep (LPN), and integrated this data with 421 sequenced datasets from wild and domestic sheep, shedding light on the genetic backdrop and genomic variations associated with LPB. Furthermore, we performed comparative RNA-Seq analysis using liver sample to pinpoint genes implicated in the pigmentation process. We generated a comprehensive dataset comprising 97,944,357 SNPs from 571 sheep, facilitating an in-depth exploration of genetic factors. RESULTS: Population genetic structure analysis revealed that the LPB breed traces its origin back to LPN, having evolved into a distinct breed. The integration of positively selected genes with differentially expressed genes identified two candidates, ERBB4 and ROR1, potentially linked to LPB hyperpigmentation. Comparative analysis of ERBB4 and ROR1 mRNA relative expression levels in liver, spleen, and kidney tissues of LPB, in comparison to Diqing sheep, revealed significant upregulation, except for ERBB4 in the liver. Gene expression heatmaps further underscored marked allelic frequency disparities in different populations. CONCLUSION: Our findings establish the evolutionary lineage of the LPB breed from LPN and underscore the involvement of ERBB4 and ROR1 genes in melanin synthesis. These results enhance our comprehension of the molecular basis of hyperpigmentation and contribute to a more comprehensive depiction of sheep diversity.

Complete genome sequence analysis of Pestalotiopsis microspora, a fungal pathogen causing kiwifruit postharvest rots.

BACKGROUND: The postharvest rot of kiwifruit is one of the most devastating diseases affecting kiwifruit quality worldwide. However, the genomic basis and pathogenicity mechanisms of kiwifruit rot pathogens are lacking. Here we report the first whole genome sequence of Pestalotiopsis microspora, one of the main pathogens causing postharvest kiwifruit rot in China. The genome of strain KFRD-2 was sequenced, de novo assembled, and analyzed. RESULTS: The genome of KFRD-2 was estimated to be approximately 50.31 Mb in size, with an overall GC content of 50.25%. Among 14,711 predicted genes, 14,423 (98.04%) exhibited significant matches to genes in the NCBI nr database. A phylogenetic analysis of 26 known pathogenic fungi, including P. microspora KFRD-2, based on conserved orthologous genes, revealed that KFRD-2's closest evolutionary relationships were to Neopestalotiopsis spp. Among KFRD-2's coding genes, 870 putative CAZy genes spanned six classes of CAZys, which play roles in degrading plant cell walls. Out of the 25 other plant pathogenic fungi, P. microspora possessed a greater number of CAZy genes than 22 and was especially enriched in GH and AA genes. A total of 845 transcription factors and 86 secondary metabolism gene clusters were predicted, representing various types. Furthermore, 28 effectors and 109 virulence-enhanced factors were identified using the PHI (pathogen host-interacting) database. CONCLUSION: This complete genome sequence analysis of the kiwifruit postharvest rot pathogen P. microspora enriches our understanding its disease pathogenesis and virulence. This study establishes a theoretical foundation for future investigations into the pathogenic mechanisms of P. microspora and the development of enhanced strategies for the efficient management of kiwifruit postharvest rots.

Genomic dissection of the correlation between milk yield and various health traits using functional and evolutionary information about imputed sequence variants of 34,497 German Holstein cows.

BACKGROUND: Over the last decades, it was subject of many studies to investigate the genomic connection of milk production and health traits in dairy cattle. Thereby, incorporating functional information in genomic analyses has been shown to improve the understanding of biological and molecular mechanisms shaping complex traits and the accuracies of genomic prediction, especially in small populations and across-breed settings. Still, little is known about the contribution of different functional and evolutionary genome partitioning subsets to milk production and dairy health. Thus, we performed a uni- and a bivariate analysis of milk yield (MY) and eight health traits using a set of ~34,497 German Holstein cows with 50K chip genotypes and ~17 million imputed sequence variants divided into 27 subsets depending on their functional and evolutionary annotation. In the bivariate analysis, eight trait-combinations were observed that contrasted MY with each health trait. Two genomic relationship matrices (GRM) were included, one consisting of the 50K chip variants and one consisting of each set of subset variants, to obtain subset heritabilities and genetic correlations. In addition, 50K chip heritabilities and genetic correlations were estimated applying merely the 50K GRM. RESULTS: In general, 50K chip heritabilities were larger than the subset heritabilities. The largest heritabilities were found for MY, which was 0.4358 for the 50K and 0.2757 for the subset heritabilities. Whereas all 50K genetic correlations were negative, subset genetic correlations were both, positive and negative (ranging from -0.9324 between MY and mastitis to 0.6662 between MY and digital dermatitis). The subsets containing variants which were annotated as noncoding related, splice sites, untranslated regions, metabolic quantitative trait loci, and young variants ranked highest in terms of their contribution to the traits` genetic variance. We were able to show that linkage disequilibrium between subset variants and adjacent variants did not cause these subsets` high effect. CONCLUSION: Our results confirm the connection of milk production and health traits in dairy cattle via the animals` metabolic state. In addition, they highlight the potential of including functional information in genomic analyses, which helps to dissect the extent and direction of the observed traits` connection in more detail.

Variability of macrolide-resistant profile in Mycobacterium avium complex pulmonary disease.

This single-center retrospective study aimed to analyze the variability of macrolide resistance (MR) in 68 patients with Mycobacterium avium complex pulmonary disease. Among 25 patients treated without macrolides, 13 (52%) reverted to macrolide-susceptible (MS) profiles. Only one (2%) of 43 patients who continued macrolide treatment showed this change. We compared 30 MR isolates with recent specimens. Among them, seven shifted to MS (five attributed to clonally related strains; two resulting from reinfection or polyclonal infection).

Stimulating T cell responses against patient-derived breast cancer cells with neoantigen peptide-loaded peripheral blood mononuclear cells.

Breast cancer stands as a formidable global health challenge for women. While neoantigens exhibit efficacy in activating T cells specific to cancer and instigating anti-tumor immune responses, the accuracy of neoantigen prediction remains suboptimal. In this study, we identified neoantigens from the patient-derived breast cancer cells, PC-B-142CA and PC-B-148CA cells, utilizing whole-genome and RNA sequencing. The pVAC-Seq pipeline was employed, with minor modification incorporating criteria (1) binding affinity of mutant (MT) peptide with HLA (IC50 MT) ≤ 500 nm in 3 of 5 algorithms and (2) IC50 wild type (WT)/MT > 1. Sequencing results unveiled 2513 and 3490 somatic mutations, and 646 and 652 non-synonymous mutations in PC-B-142CA and PC-B-148CA, respectively. We selected the top 3 neoantigens to perform molecular dynamic simulation and synthesized 9-12 amino acid neoantigen peptides, which were then pulsed onto healthy donor peripheral blood mononuclear cells (PBMCs). Results demonstrated that T cells activated by ADGRL1E274K, PARP1E619K, and SEC14L2R43Q peptides identified from PC-B-142CA exhibited significantly increased production of interferon-gamma (IFN-γ), while PARP1E619K and SEC14L2R43Q peptides induced the expression of CD107a on T cells. The % tumor cell lysis was notably enhanced by T cells activated with MT peptides across all three healthy donors. Moreover, ALKBH6V83M and GAAI823T peptides from PC-B-148CA remarkably stimulated IFN-γ- and CD107a-positive T cells, displaying high cell-killing activity against target cancer cells. In summary, our findings underscore the successful identification of neoantigens with anti-tumor T cell functions and highlight the potential of personalized neoantigens as a promising avenue for breast cancer treatment.

PE/PPE mutations in the transmission of Mycobacterium tuberculosis in China revealed by whole genome sequencing.

OBJECTIVE: This study aims to examine the impact of PE/PPE gene mutations on the transmission of Mycobacterium tuberculosis (M. tuberculosis) in China. METHODS: We collected the whole genome sequencing (WGS) data of 3202 M. tuberculosis isolates in China from 2007 to 2018 and investigated the clustering of strains from different lineages. To evaluate the potential role of PE/PPE gene mutations in the dissemination of the pathogen, we employed homoplastic analysis to detect homoplastic single nucleotide polymorphisms (SNPs) within these gene regions. Subsequently, logistic regression analysis was conducted to analyze the statistical association. RESULTS: Based on nationwide M. tuberculosis WGS data, it has been observed that the majority of the M. tuberculosis burden in China is caused by lineage 2 strains, followed by lineage 4. Lineage 2 exhibited a higher number of transmission clusters, totaling 446 clusters, of which 77 were cross-regional clusters. Conversely, there were only 52 transmission clusters in lineage 4, of which 9 were cross-regional clusters. In the analysis of lineage 2 isolates, regression results showed that 4 specific gene mutations, PE4 (position 190,394; c.46G > A), PE_PGRS10 (839,194; c.744 A > G), PE16 (1,607,005; c.620T > G) and PE_PGRS44 (2,921,883; c.333 C > A), were significantly associated with the transmission of M. tuberculosis. Mutations of PE_PGRS10 (839,334; c.884 A > G), PE_PGRS11 (847,613; c.1455G > C), PE_PGRS47 (3,054,724; c.811 A > G) and PPE66 (4,189,930; c.303G > C) exhibited significant associations with the cross-regional clusters. A total of 13 mutation positions showed a positive correlation with clustering size, indicating a positive association. For lineage 4 strains, no mutations were found to enhance transmission, but 2 mutation sites were identified as risk factors for cross-regional clusters. These included PE_PGRS4 (338,100; c.974 A > G) and PPE13 (976,897; c.1307 A > C). CONCLUSION: Our results indicate that some PE/PPE gene mutations can increase the risk of M. tuberculosis transmission, which might provide a basis for controlling the spread of tuberculosis.

Whole-genome sequencing and analysis of Chryseobacterium arthrosphaerae from Rana nigromaculata.

Chryseobacterium arthrosphaerae strain FS91703 was isolated from Rana nigromaculata in our previous study. To investigate the genomic characteristics, pathogenicity-related genes, antimicrobial resistance, and phylogenetic relationship of this strain, PacBio RS II and Illumina HiSeq 2000 platforms were used for the whole genome sequencing. The genome size of strain FS91703 was 5,435,691 bp and GC content was 37.78%. A total of 4,951 coding genes were predicted; 99 potential virulence factors homologs were identified. Analysis of antibiotic resistance genes revealed that strain FS91703 harbored 10 antibiotic resistance genes in 6 categories and 2 multidrug-resistant efflux pump genes, including adeG and farA. Strain FS91703 was sensitive to ß-lactam combination drugs, cephem, monobactam and carbapenems, intermediately resistant to phenicol, and resistant to penicillin, aminoglycosides, tetracycline, fluoroquinolones, and folate pathway inhibitors. Phylogenetic analysis revealed that strain FS91703 and C. arthrosphaerae CC-VM-7T were on the same branch of the phylogenetic tree based on 16 S rRNA; the ANI value between them was 96.99%; and the DDH values were 80.2, 72.2 and 81.6% by three default calculation formulae. These results suggested that strain FS91703 was a species of C. arthrosphaerae. Pan-genome analysis showed FS91703 had 566 unique genes compared with 13 other C. arthrosphaerae strains, and had a distant phylogenetic relationship with the other C. arthrosphaerae strains of the same branch in phylogenetic tree based on orthologous genes. The results of this study suggest that strain FS91703 is a multidrug-resistant and highly virulent bacterium, that differs from other C. arthrosphaerae strains at the genomic level. The knowledge about the genomic characteristics and antimicrobial resistance of strain FS91703 provides valuable insights into this rare species, as well as guidance for the treatment of the disease caused by FS91703 in Rana nigromaculata.