Plasma level of alpha-synuclein oligomers as a biomarker for isolated rapid eye movement sleep behavior disorder diagnosis and progression: a prospective cohort study.

Background: Alpha-synuclein oligomers (o-α-syn) are pivotal in the pathogenesis of α-synucleinopathy. Isolated rapid eye movement (REM) sleep behavior disorder (iRBD) serves as an early indicator of the disease, offering insights into disease mechanisms and early intervention. Nevertheless, the diagnostic and predictive potential of o-α-syn in iRBD remains largely unexplored. This study aimed to evaluate the plasma levels of o-α-syn in patients and investigate their utility as biomarkers for diagnosis of and predicting phenoconversion in iRBD. Methods: A total of 143 participants, including 77 polysomnography-confirmed iRBD patients and 66 normal controls (NC), were recruited for this longitudinal observational study. Baseline clinical assessments and plasma collection were conducted for all iRBD patients, with 72 of them undergoing regularly prospective follow-up assessments for parkinsonism or dementia. Plasma levels of o-α-syn were quantified using enzyme-linked immunosorbent assay, and were compared between groups using a general linear model adjusted for age and sex. The diagnostic performance of plasma o-α-syn in iRBD was evaluated by area under the receiver operating characteristic curve (AUC) with 95% CI. Cox regression analysis and Kaplan-Meier survival curves were employed to assess the predictive value of plasma o-α-syn for phenoconversion in iRBD. Results: Plasma o-α-syn levels did not exhibit statistically significant differences among iRBD converter patients, iRBD nonconverter patients, and NC. The AUC for distinguishing NC from iRBD was 0.52 (95% CI: 0.42-0.62, p = 0.682). Spearman correlation analysis revealed a significant positive correlation between plasma o-α-syn levels and MOCA scores in the iRBD group (p < 0.001). Subgroup analyses indicated that iRBD patients with cognitive decline (p = 0.058) and depressive symptoms (p = 0.017) had notably lower o-α-syn levels compared to those without such symptoms. Over a median follow-up period of 5.83 years, 26 iRBD patients developed neurodegenerative synucleinopathies. Cox regression and Kaplan-Meier survival curve analyses indicated that plasma level of o-α-syn lacked a predictive value for disease conversion in iRBD patients. Conclusion: Despite a potential role in the pathophysiology of iRBD, o-α-syn are not appropriate biomarkers for diagnosing or predicting disease progression. While this study offers insights into the pathogenesis of iRBD and neurodegenerative synucleinopathies, further large-scale longitudinal studies are warranted to validate these findings.

Global Marine Cold Seep Metagenomes Reveal Diversity of Taxonomy, Metabolic Function, and Natural Products.

Cold seeps in the deep sea are closely linked to energy exploration as well as global climate change. The alkane-dominated chemical energy-driven model makes cold seeps an oasis of deep-sea life, showcasing an unparalleled reservoir of microbial genetic diversity. Here, by analyzing 113 metagenomes collected from 14 global sites across 5 cold seep types, we present a comprehensive Cold Seep Microbiomic Database (CSMD) to archive the genomic and functional diversity of cold seep microbiomes. The CSMD includes over 49 million non-redundant genes and 3175 metagenome-assembled genomes, which represent 1895 species spanning 105 phyla. In addition, beta diversity analysis indicates that both the sampling site and cold seep type have a substantial impact on the prokaryotic microbiome community composition. Heterotrophic and anaerobic metabolisms are prevalent in microbial communities, accompanied by considerable mixotrophs and facultative anaerobes, highlighting the versatile metabolic potential in cold seeps. Furthermore, secondary metabolic gene cluster analysis indicates that at least 98.81% of the sequences potentially encode novel natural products, with ribosomally synthesized and post-translationally modified peptides being the predominant type widely distributed in archaea and bacteria. Overall, the CSMD represents a valuable resource that would enhance the understanding and utilization of global cold seep microbiomes.

Single-cell landscape revealed immune characteristics associated with disease phases in brucellosis patients.

A comprehensive immune landscape for Brucella infection is crucial for developing new treatments for brucellosis. Here, we utilized single-cell RNA sequencing (scRNA-seq) of 290,369 cells from 35 individuals, including 29 brucellosis patients from acute (n = 10), sub-acute (n = 9), and chronic (n = 10) phases as well as six healthy donors. Enzyme-linked immunosorbent assays were applied for validation within this cohort. Brucella infection caused a significant change in the composition of peripheral immune cells and inflammation was a key feature of brucellosis. Acute patients are characterized by potential cytokine storms resulting from systemic upregulation of S100A8/A9, primarily due to classical monocytes. Cytokine storm may be mediated by activating S100A8/A9-TLR4-MyD88 signaling pathway. Moreover, monocytic myeloid-derived suppressor cells were the probable contributors to immune paralysis in acute patients. Chronic patients are characterized by a dysregulated Th1 response, marked by reduced expression of IFN-γ and Th1 signatures as well as a high exhausted state. Additionally, Brucella infection can suppress apoptosis in myeloid cells (e.g., mDCs, classical monocytes), inhibit antigen presentation in professional antigen-presenting cells (APCs; e.g., mDC) and nonprofessional APCs (e.g., monocytes), and induce exhaustion in CD8+ T/NK cells, potentially resulting in the establishment of chronic infection. Overall, our study systemically deciphered the coordinated immune responses of Brucella at different phases of the infection, which facilitated a full understanding of the immunopathogenesis of brucellosis and may aid the development of new effective therapeutic strategies, especially for those with chronic infection.

Spike structures, receptor binding, and immune escape of recently circulating SARS-CoV-2 Omicron BA.2.86, JN.1, EG.5, EG.5.1, and HV.1 sub-variants.

The recently emerged BA.2.86, JN.1, EG.5, EG.5.1, and HV.1 variants have a growth advantage. In this study, we explore the structural bases of receptor binding and immune evasion for the Omicron BA.2.86, JN.1, EG.5, EG.5.1, and HV.1 sub-variants. Our findings reveal that BA.2.86 exhibits strong receptor binding, whereas its JN.1 sub-lineage displays a decreased binding affinity to human ACE2 (hACE2). Through complex structure analyses, we observed that the reversion of R493Q in BA.2.86 receptor binding domain (RBD) plays a facilitating role in receptor binding, while the L455S substitution in JN.1 RBD restores optimal affinity. Furthermore, the structure of monoclonal antibody (mAb) S309 complexed with BA.2.86 RBD highlights the importance of the K356T mutation, which brings a new N-glycosylation motif, altering the binding pattern of mAbs belonging to RBD-5 represented by S309. These findings emphasize the importance of closely monitoring BA.2.86 and its sub-lineages to prevent another wave of SARS-CoV-2 infections.

Co-expression of a pair of interdependent regulators coding genes ovmZ and ovmW awakens the production of angucyclinones antibiotics in Streptomyces neyagawaensis.

BACKGROUND: Microbial genome sequencing and analysis revealed the presence of abundant silent secondary metabolites biosynthetic gene clusters (BGCs) in streptomycetes. Activating these BGCs has great significance for discovering new compounds and novel biosynthetic pathways. RESULTS: In this study, we found that ovmZ and ovmW homologs, a pair of interdependent transcriptional regulators coding genes, are widespread in actinobacteria and closely associated with the biosynthesis of secondary metabolites. Through co-overexpression of native ovmZ and ovmW in Streptomyces neyagawaensis NRRL B-3092, a silent type II polyketide synthase (PKS) gene cluster was activated to produce gephyromycin A, tetrangomycin and fridamycin E with the yields of 22.3 ± 8.0 mg/L, 4.8 ± 0.5 mg/L and 20.3 ± 4.1 mg/L respectively in the recombinant strain of S.ne/pZnWn. However, expression of either ovmZ or ovmW failed to activate this gene cluster. Interestingly, overexpression of the heterologous ovmZ and ovmW pair from oviedomycin BGC of S. ansochromogenes 7100 also led to awakening of this silent angucyclinone BGC in S. neyagawaensis. CONCLUSION: A silent angucyclinone BGC was activated by overexpressing both ovmZ and ovmW in S. neyagawaensis. Due to the wide distribution of ovmZ and ovmW in the BGCs of actinobacteria, co-overexpression of ovmZ and ovmW could be a strategy for activating silent BGCs, thus stimulating the biosynthesis of secondary metabolites.

Exploring CYP2D6 polymorphisms and angiotensin receptor blocker response in the Bai hypertensive population.

OBJECTIVE: The CYP2D6 enzyme is crucial for the metabolism and disposition of a variety of drugs. This study was conducted to examine the relationship between CYP2D6 gene polymorphisms and the response to angiotensin receptor blocker (ARB)-based treatment in patients of Chinese Bai ethnicity with hypertension. METHODS: Seventy-two hypertensive adults from the Chinese Bai ethnic group, exhibiting systolic blood pressure (SBP) ≥ 140 mmHg or diastolic blood pressure (DBP) ≥ 90 mmHg, were recruited. Targeted regional sequencing was utilized to genotype single nucleotide polymorphisms in the CYP2D6 gene, aiming to assess their frequency and to evaluate their influence on the therapeutic efficacy of ARB medications. RESULTS: Our research identified nine significant CYP2D6 polymorphisms associated with the efficacy of ARB treatment in the Bai hypertensive cohort. Specifically, patients possessing certain mutant genotype at rs111564371 exhibited substantially greater reductions in SBP and DBP, with P -values of 0.021 and 0.016, respectively, compared to those carrying the wild genotype. Additionally, these mutant genotype at rs111564371 and rs112568578 were linked to approximately 20% higher overall efficacy rates and a 10% increased achievement rate relative to the wild genotype. CONCLUSION: Our research with the Bai hypertensive group shows that certain CYP2D6 polymorphisms significantly influence ARB treatment outcomes. Mutations at rs111564371 led to better blood pressure control ( P -values: 0.021 for SBP, 0.016 for DBP), improving ARB efficacy by appromixately 20% and increasing treatment goal achievement by 10% over the wild-type genotype. STATEMENTS: Our investigation into CYP2D6 polymorphisms within the Bai hypertensive cohort marks a substantial advancement towards personalized healthcare, underscoring the pivotal influence of genetic constitution on the effectiveness of ARB therapy.

Dissecting and tracing the gut microbiota of infants with botulism: a cross sectional and longitudinal study.

Background: Infant botulism is caused by botulinum neurotoxin (BoNT), which is mainly produced by Clostridium botulinum. However, there is a lack of longitudinal cohort studies on infant botulism. Herein, we have constructed a cross-sectional and longitudinal cohort of infants infected with C. botulinum. Our goal was to reveal the differences in the intestinal microbiota of botulism-infected and healthy infants as well as the dynamic changes over time through multi-omics analysis. Methods: We performed 16S rRNA sequencing of 20 infants' stools over a period of 3 months and conducted whole genome sequencing of isolated C. botulinum strains from these laboratory-confirmed cases of infant botulism. Through bioinformatics analysis, we focused on the changes in the infants' intestinal microbiota as well as function over time series. Results: We found that Enterococcus was significantly enriched in the infected group and declined over time, whereas Bifidobacterium was significantly enriched in the healthy group and gradually increased over time. 18/20 isolates carried the type B 2 botulinum toxin gene with identical sequences. In silico Multilocus sequence typing found that 20\u00B0C. botulinum isolates from the patients were typed into ST31 and ST32. Conclusion: Differences in intestinal microbiota and functions in infants were found with botulism through cross-sectional and longitudinal studies and Bifidobacterium may play a role in the recovery of infected infants.

Genomic epidemiology reveals multiple mechanisms of linezolid resistance in clinical enterococci in China.

BACKGROUND: Infections caused by linezolid-resistant enterococci (LRE) are clinically difficult to treat and threaten patient health. However, there is a lack of studies on long time-span LRE strains in China. For this reason, our study comprehensively revealed the resistance mechanisms of LRE strains collected in a Chinese tertiary care hospital from 2011 to 2022. METHODS: Enterococcal strains were screened and verified after retrospective analysis of microbial data. Subsequently, 65 LRE strains (61 Enterococcus faecalis and 4 Enterococcus faecium, MIC ≥ 8 µg/ml), 1 linezolid-intermediate Enterococcus faecium (MIC = 4 µg/ml) and 1 linezolid-susceptible Enterococcus faecium (MIC = 1.5 µg/ml) were submitted for whole-genome sequencing (WGS) analysis and bioinformatics analysis. RESULTS: The optrA gene was found to be the most common linezolid resistance mechanism in our study. We identified the wild-type OptrA and various OptrA variants in 98.5% of LRE strains (61 Enterococcus faecalis and 3 Enterococcus faecium). We also found one linezolid-resistant Enterococcus faecium strain carried both optrA and cfr(D) gene, while one linezolid-resistant Enterococcus faecium only harbored the poxtA gene. Most optrA genes (55/64) were located on plasmids, with impB-fexA-optrA, impB-fexA-optrA-erm(A), fexA-optrA-erm(A), and fexA-optrA segments. A minority of optrA genes (9/64) were found on chromosomes with the Tn6674-like platform. Besides, other possible linezolid resistance-associated mechanisms (mutations in the rplC and rplD genes) were also found in 26 enterococcal strains. CONCLUSIONS: Our study suggested that multiple mechanisms of linezolid resistance exist among clinical LRE strains in China.

Dynamic analysis of SARS-CoV-2 evolution based on different countries.

Since late 2019, COVID-19 has significantly impacted the world. Understanding the evolution of SARS-CoV-2 is crucial for protecting against future infectious pathogens. In this study, we conducted a comprehensive chronological analysis of SARS-CoV-2 evolution by examining mutation prevalence from the source countries of VOCs: United Kingdom, India, Brazil, South Africa, plus two countries: United States, Russia, utilizing genomic sequences from GISAID. Our methodological approach involved large-scale genomic sequence alignment using MAFFT, Python-based data processing on a high-performance computing platform, and advanced statistical methods the Maximal Information Coefficient (MIC), and also Long Short-Term Memory (LSTM) models for correlation analysis. Our findings elucidate the dynamics of SARS-CoV-2 evolution, highlighting the virus's changing behaviour over various pandemic stages. Key results include the discovery of three temporal mutation patterns-lineage distinct, long-span, and competitive mutations-with varying levels of impact on the virus. Notably, we observed a convergence of advantageous mutations in the spike protein, especially in the later stages of the pandemic, indicating a substantial evolutionary pressure on the virus. One of the most significant revelations is the predominant role of natural immunity over vaccination-induced immunity in driving these evolutionary changes. This emphasizes the critical need for regular vaccine updates to maintain efficacy against evolving strains. In conclusion, our study not only sheds light on the evolutionary trajectory of SARS-CoV-2 but also underscores the urgency for robust, continuous global data collection and sharing. It highlights the necessity for rapid adaptations in medical countermeasures, including vaccine development, to stay ahead of pathogen evolution. This research provides valuable insights for future pandemic preparedness and response strategies.

Impact of LDLR polymorphisms on lipid levels and atorvastatin's efficacy in a northern Chinese adult Han cohort with dyslipidemia.

BACKGROUND: Dyslipidemia, a significant risk factor for atherosclerotic cardiovascular disease (ASCVD), is influenced by genetic variations, particularly those in the low-density lipoprotein receptor (LDLR) gene. This study aimed to elucidate the effects of LDLR polymorphisms on baseline serum lipid levels and the therapeutic efficacy of atorvastatin in an adult Han population in northern China with dyslipidemia. METHODS: In this study, 255 Han Chinese adults receiving atorvastatin therapy were examined and followed up. The 3' untranslated region (UTR) of the LDLR gene was sequenced to identify polymorphisms. The associations between gene polymorphisms and serum lipid levels, as well as changes in lipid levels after intervention, were evaluated using the Wilcoxon rank sum test, with a P < 0.05 indicating statistical significance. Assessment of linkage disequilibrium patterns and haplotype structures was conducted utilizing Haploview. RESULTS: Eleven distinct polymorphisms at LDLR 3' UTR were identified. Seven polymorphisms (rs1433099, rs14158, rs2738466, rs5742911, rs17249057, rs55971831, and rs568219285) were correlated with the baseline serum lipid levels (P < 0.05). In particular, four polymorphisms (rs14158, rs2738466, rs5742911, and rs17249057) were in strong linkage disequilibrium (r2 = 1), and patients with the AGGC haplotype had higher TC and LDL-C levels at baseline. Three polymorphisms (rs1433099, rs2738467, and rs7254521) were correlated with the therapeutic efficacy of atorvastatin (P < 0.05). Furthermore, carriers of the rs2738467 T allele demonstrated a significantly greater reduction in low-density lipoprotein cholesterol (LDL-C) levels post-atorvastatin treatment (P = 0.03), indicating a potentially crucial genetic influence on therapeutic outcomes. Two polymorphisms (rs751672818 and rs566918949) were neither correlated with the baseline serum lipid levels nor atorvastatin's efficacy. CONCLUSIONS: This research outlined the complex genetic architecture surrounding LDLR 3' UTR polymorphisms and their role in lipid metabolism and the response to atorvastatin treatment in adult Han Chinese patients with dyslipidemia, highlighting the importance of genetic profiling in enhancing tailored therapeutic strategies. Furthermore, this investigation advocates for the integration of genetic testing into the management of dyslipidemia, paving the way for customized therapeutic approaches that could significantly improve patient care. TRIAL REGISTRATION: This multicenter study was approved by the Ethics Committee of Xiangya Hospital Central South University (ethics number K22144). It was a general ethic. In addition, this study was approved by The First Hospital of Hebei Medical University (ethics number 20220418).

Anaerostipes hadrus, a butyrate-producing bacterium capable of metabolizing 5-fluorouracil.

Anaerostipes hadrus (A. hadrus) is a dominant species in the human gut microbiota and considered a beneficial bacterium for producing probiotic butyrate. However, recent studies have suggested that A. hadrus may negatively affect the host through synthesizing fatty acid and metabolizing the anticancer drug 5-fluorouracil, indicating that the impact of A. hadrus is complex and unclear. Therefore, comprehensive genomic studies on A. hadrus need to be performed. We integrated 527 high-quality public A. hadrus genomes and five distinct metagenomic cohorts. We analyzed these data using the approaches of comparative genomics, metagenomics, and protein structure prediction. We also performed validations with culture-based in vitro assays. We constructed the first large-scale pan-genome of A. hadrus (n = 527) and identified 5-fluorouracil metabolism genes as ubiquitous in A. hadrus genomes as butyrate-producing genes. Metagenomic analysis revealed the wide and stable distribution of A. hadrus in healthy individuals, patients with inflammatory bowel disease, and patients with colorectal cancer, with healthy individuals carrying more A. hadrus. The predicted high-quality protein structure indicated that A. hadrus might metabolize 5-fluorouracil by producing bacterial dihydropyrimidine dehydrogenase (encoded by the preTA operon). Through in vitro assays, we validated the short-chain fatty acid production and 5-fluorouracil metabolism abilities of A. hadrus. We observed for the first time that A. hadrus can convert 5-fluorouracil to α-fluoro-ß-ureidopropionic acid, which may result from the combined action of the preTA operon and adjacent hydA (encoding bacterial dihydropyrimidinase). Our results offer novel understandings of A. hadrus, exceptionally functional features, and potential applications. IMPORTANCE: This work provides new insights into the evolutionary relationships, functional characteristics, prevalence, and potential applications of Anaerostipes hadrus.

VarEPS-Influ:an risk evaluation system of occurred and virtual variations of influenza virus genomes.

Influenza viruses undergo frequent genomic mutations, leading to potential cross-species transmission, phenotypic changes, and challenges in diagnostic reagents and vaccines. Accurately evaluating and predicting the risk of such variations remain significant challenges. To address this, we developed the VarEPS-Influ database, an influenza virus variations risk evaluation system (VarEPS-Influ). This database employs a 'multi-dimensional evaluation of mutations' strategy, utilizing various tools to assess the physical and chemical properties, primary, secondary, and tertiary structures, receptor affinity, antibody binding capacity, antigen epitopes, and other aspects of the variation's impact. Additionally, we consider space-time distribution, host species distribution, pedigree analysis, and frequency of mutations to provide a comprehensive risk evaluation of mutations and viruses. The VarEPS-Influ database evaluates both observed variations and virtual variations (variations that have not yet occurred), thereby addressing the time-lag issue in risk predictions. Our current one-stop evaluation system for influenza virus genomic variation integrates 1065290 sequences from 224 927 Influenza A, B and C isolates retrieved from public resources. Researchers can freely access the data at https://nmdc.cn/influvar/.

Large-scale genomic survey and characterization of mcr genes carried by foodborne Cronobacter isolates.

IMPORTANCE: Cronobacter is an emerging foodborne opportunistic pathogen, which can cause neonatal meningitis, bacteremia, and NEC by contaminating food. However, the entire picture of foodborne Cronobacter carriage of the mcr genes is not known. Here, we investigated the mcr genes of Cronobacter isolates by whole-genome sequencing and found 133 previously undescribed Cronobacter isolates carrying mcr genes. Further genomic analysis revealed that these mcr genes mainly belonged to the mcr-9 and mcr-10. Genomic analysis of the flanking structures of mcr genes revealed that two core flanking structures were prevalent in foodborne Cronobacter isolates, and the flanking structure carrying IS1R was found for the first time in this study.

Comparative genomic analysis of Fusobacterium nucleatum reveals high intra-species diversity and cgmlst marker construction.

BACKGROUND: Fusobacterium nucleatum is a one of the most important anaerobic opportunistic pathogens in the oral and intestinal tracts of human and animals. It can cause various diseases such as infections, Lemierre's syndrome, oral cancer and colorectal cancer. The comparative genomic studies on the population genome level, have not been reported. RESULTS: We analyzed all publicly available Fusobacterium nucleatums' genomic data for a comparative genomic study, focusing on the pan-genomic features, virulence genes, plasmid genomes and developed cgmlst molecular markers. We found the pan-genome shows a clear open tendency and most of plasmids in Fusobacterium nucleatum are mainly transmitted intraspecifically. CONCLUSIONS: Our comparative analysis of Fusobacterium nucleatum systematically revealed the open pan-genomic features and phylogenetic tree based on cgmlst molecular markers. What's more, we also identified common plasmid typing among genomes. We hope that our study will provide a theoretical basis for subsequent functional studies.

A Novel Prognostic Signature of comprising Nine NK Cell signatures Based on Both Bulk RNA Sequencing and Single-Cell RNA Sequencing for Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) has limited prognostic prediction due to its heterogeneity. Understanding the role of natural killer (NK) cells in HCC is vital for prognosis and immunotherapy guidance. We aimed to identify NK cell marker genes through scRNA-seq and develop a prognostic signature for HCC. Methods: We analyzed scRNA-seq data (GSE149614) from 10 patients and bulk RNA-seq data from 786 patients with clinicopathological information. NK cell marker genes were identified using clustering and marker finding functions. A predictive risk signature was constructed using LASSO-COX algorithm. Functional annotations and immune cell infiltration analysis were performed, and the nomogram's performance was evaluated. Results: We identified 79 NK cell marker genes associated with NK cell-mediated cytotoxicity, apoptosis, and immune response. The multigene signature significantly correlated with overall survival (OS) in TCGA-LIHC cohort and was validated in other cohorts. Low-risk patients exhibited higher immune cell infiltration, including CD8+ T cells. The risk signature was an independent prognostic factor for OS (HR > 1, p < 0.001). The nomogram combining the risk signature and clinical predictors demonstrated robust prognostic ability. Conclusion: We developed a nine-gene signature prognostic model based on NK cell marker genes to accurately assess the prognostic risk of HCC. This model can be a valuable tool for personalized evaluation post-surgery. Our study underscores the potential of NK cells in HCC prognosis and highlights the importance of scRNA-seq analysis in identifying prognostic markers.

Plasmer: an Accurate and Sensitive Bacterial Plasmid Prediction Tool Based on Machine Learning of Shared k-mers and Genomic Features.

Identification of plasmids in bacterial genomes is critical for many factors, including horizontal gene transfer, antibiotic resistance genes, host-microbe interactions, cloning vectors, and industrial production. There are several in silico methods to predict plasmid sequences in assembled genomes. However, existing methods have evident shortcomings, such as unbalance in sensitivity and specificity, dependency on species-specific models, and performance reduction in sequences shorter than 10 kb, which has limited their scope of applicability. In this work, we proposed Plasmer, a novel plasmid predictor based on machine-learning of shared k-mers and genomic features. Unlike existing k-mer or genomic-feature based methods, Plasmer employs the random forest algorithm to make predictions using the percent of shared k-mers with plasmid and chromosome databases combined with other genomic features, including alignment E value and replicon distribution scores (RDS). Plasmer can predict on multiple species and has achieved an average the area under the curve (AUC) of 0.996 with accuracy of 98.4%. Compared to existing methods, tests of both sliding sequences and simulated and de novo assemblies have consistently shown that Plasmer has outperforming accuracy and stable performance across long and short contigs above 500 bp, demonstrating its applicability for fragmented assemblies. Plasmer also has excellent and balanced performance on both sensitivity and specificity (both >0.95 above 500 bp) with the highest F1-score, which has eliminated the bias on sensitivity or specificity that was common in existing methods. Plasmer also provides taxonomy classification to help identify the origin of plasmids. IMPORTANCE In this study, we proposed a novel plasmid prediction tool named Plasmer. Technically, unlike existing k-mer or genomic features-based methods, Plasmer is the first tool to combine the advantages of the percent of shared k-mers and the alignment score of genomic features. This has given Plasmer (i) evident improvement in performance compared to other methods, with the best F1-score and accuracy on sliding sequences, simulated contigs, and de novo assemblies; (ii) applicability for contigs above 500 bp with highest accuracy, enabling plasmid prediction in fragmented short-read assemblies; (iii) excellent and balanced performance between sensitivity and specificity (both >0.95 above 500 bp) with the highest F1-score, which eliminated the bias on sensitivity or specificity that commonly existed in other methods; and (iv) no dependency of species-specific training models. We believe that Plasmer provides a more reliable alternative for plasmid prediction in bacterial genome assemblies.

A food poisoning caused by ST7 Staphylococcal aureus harboring sea gene in Hainan province, China.

ST7 Staphylococcus aureus is highly prevalent in humans, pigs, as well as food in China; however, staphylococcal food poisoning (SFP) caused by this ST type has rarely been reported. On May 13, 2017, an SFP outbreak caused by ST7 S. aureus strains occurred in two campuses of a kindergarten in Hainan Province, China. We investigated the genomic characteristics and phylogenetic analysis of ST7 SFP strains combined with the 91 ST7 food-borne strains from 12 provinces in China by performing whole-genome sequencing (WGS). There was clear phylogenetic clustering of seven SFP isolates. Six antibiotic genes including blaZ, ANT (4')-Ib, tetK, lnuA, norA, and lmrS were present in all SFP strains and also showed a higher prevalence rate in 91 food-borne strains. A multiple resistance plasmid pDC53285 was present in SFP strain DC53285. Among 27 enterotoxin genes, only sea and selx were found in all SFP strains. A ФSa3int prophage containing type A immune evasion cluster (sea, scn, sak, and chp) was identified in SFP strain. In conclusion, we concluded that this SFP event was caused by the contamination of cakes with ST7 S. aureus. This study indicated the potential risk of new emergencing ST7 clone for SFP.

Insights into the genomic evolution and the alkali tolerance mechanisms of Agaricus sinodeliciosus by comparative genomic and transcriptomic analyses.

Agaricus sinodeliciosus is a rare wild edible mushroom from northwest China, and grows naturally in mild saline-alkali soil, which is also unusual in mushrooms. A. sinodeliciosus represents a potential model organism for explaining saline-alkali tolerance mechanisms and revealing related physiological processes in mushrooms. Here, we provide a high-quality genome of A. sinodeliciosus. Comparative genomic analyses reveal A. sinodeliciosus has numerous changes to its genome organization after a solitary evolutionary history under saline-alkali environments, such as gene family contraction, retrotransposon expansion and rapid evolution of adaptative genes. Our saline and alkali tolerance tests show that mycelium growth and fruit body formation of this species are effected by mild alkalinity. Transcriptomic analyses reveal that genes involved in carbon and nitrogen utilization, cell stability and fruit body formation of A. sinodeliciosus could be activated under mildly alkaline conditions. In particular, the 'starch and sucrose metabolism', 'biosynthesis of amino acids' and 'phenylpropanoid biosynthesis' pathways are important for mildly alkaline tolerance of A. sinodeliciosus. Like plants and arbuscular mycorrhizal fungi, in the rot fungus A. sinodeliciosus, the biosynthesis of intracellular small molecules could be enhanced to counter osmotic and oxidative stresses caused by mild alkalinity, and the biosynthesis of monolignol could be suppressed to increase cell wall infiltrates under mildly alkaline conditions. This research provides an understanding of the genomic evolution and mechanisms of A. sinodeliciosus in tolerance to saline-alkali environments. The A. sinodeliciosus genome constitutes a valuable resource for evolutionary and ecological studies of Agaricus.

Gut microbiome and mycobiome in inflammatory bowel disease patients with Clostridioides difficile infection.

Background: Clostridium difficile infection (CDI) is common in patients with inflammatory bowel disease (IBD) and has been reported as a risk factor for poor outcome. However, gut microbiome and mycobiome of IBD patients with CDI have been barely investigated. This study aimed to assess the gut microbiome and mycobiome in IBD patients with CDI. Methods: We collected fecal samples from patients with active IBD and concomitant CDI (IBD-CDI group, n=25), patients with active IBD and no CDI (IBD-only group, n=51), and healthy subjects (HC, n=40). Patients' characteristics including demographic data, disease severity, and medication history were collected. Metagenomic sequencing, taxonomic and functional analysis were carried out in the samples. Results: We found that the bacterial alpha diversity of the IBD-CDI group was decreased. The bacterial and fungal beta diversity variations between IBD patients and HC were significant, regardless of CDI status. But the IBD-CDI group did not significantly cluster separately from the IBD-only group. Several bacterial taxa, including Enterococcus faecium, Ruminococcus gnavus, and Clostridium innocuum were overrepresented in the IBD-CDI group. Furthermore, IBD patients with CDI were distinguished by several fungal taxa, including overrepresentation of Saccharomyces cerevisiae. We also identified functional differences in IBD patients with CDI include enrichment of peptidoglycan biosynthesis. The network analysis indicated specific interactions between microbial markers in IBD-CDI patients. Conclusion: IBD patients with CDI had pronounced microbial dysbiosis. Gut micro-ecological changes in IBD patients with CDI might provide insight into the pathological process and potential strategies for diagnosis and treatment in this subset of patients.