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Objective: Many studies have reported microbial signatures in thrombi at major vascular sites, such as the coronary artery and the middle cerebral artery, which are critical for maintaining proper blood flow and oxygenation. Chronic thromboembolic pulmonary hypertension (CTEPH) is a condition involving non-resolving thrombosis that has not been fully studied. This study explored the microbial taxonomy and functional profiles of both fresh and organized thrombi associated with CTEPH to investigate the role of microbiota in thrombus non-resolving., Methods: In this study, 12 CTEPH fresh thrombi and 12 organized thrombi were collected from 14 patients with CTEPH. Metagenomic sequencing was employed to explore the genomic information of all microorganisms in the thrombus samples., Results: Our data demonstrated a diverse range of microorganisms in CTEPH thrombi, whether fresh or organized. Notably, a considerable proportion (54.7 %) of sequencing data could not be classified into the relative microbial taxa, highlighting the complexity and novelty of the thrombus ecosystem. Although there were no significant differences in microbial community structure between the two groups, the abundance of dominant microbial species varied. Leuconostoc sp. DORA 2, Staphylococcus aureus, and Aliidongia dinghuensis were common dominant species in CTEPH thrombus. Organized thrombus significantly increased the relative abundance of Staphylococcus aureus, which was confirmed to effectively distinguish between organized and fresh thrombi by LeFSe analysis and random forest analysis. Functional annotation using both the KEGG and eggNOG databases revealed that organized thrombi exhibit stronger metabolic functions, particularly in amino acid metabolism., Conclusions: Our findings suggest that microbial composition and function may play an important role in thrombus organization. Targeting inflammation to prevent thrombosis presents promising opportunities for further research in this area., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Metagenomic next-generation sequencing (mNGS) is increasingly being recognized as a valuable diagnostic tool for periprosthetic joint infections (PJIs). This study reviews the diagnostic utility of mNGS, highlighting its improved sensitivity in detecting pathogens, particularly in culture-negative and polymicrobial infections. However, the clinical application of this method is hindered by challenges such as the prevalence of host DNA, the necessity for extensive bioinformatic analysis, and the potential for contamination, which can lead to misinterpretation of results. As mNGS continues to evolve, it holds significant potential to improve the management of PJI and enhance the application of precision medicine in orthopedic infections., Competing Interests: Disclosure A.J. Tande reports honoraria from UpToDate not related to this article. There are no other financial disclosures or conflicts of interest to report., (Copyright © 2024 Elsevier Inc. All rights reserved.)

To investigate the impact of Poa alpigena Lindm on rhizosphere and bulk soil microorganisms in Haixin Mountain, Qinghai Lake, this study employed metagenomics technology to analyze the microbial communities of the samples. Results showed that 65 phyla, 139 classes, 278 orders, 596 families, 2376 genera, and 5545 species of soil microorganisms were identified from rhizosphere and bulk soil samples. Additionally, a microbial gene library specific to Poa alpigena Lindm was established for Qinghai Lake. Through α-diversity analysis, the richness and diversity of bulk microorganisms both significantly had a higher value than that in rhizosphere soil. The indicator microorganisms of rhizosphere and bulk soil at class level were Actinobacteria and Alphaproteobacteria, respectively. KEGG pathway analysis indicated that Carotenoid biosynthesis, Starch and sucrose metabolism, Bacterial chemotaxis, MAPK signaling pathway, Terpenoid backbone biosynthesis, and vancomycin resistance were the key differential metabolic pathways of rhizosphere soil microorganisms; in contrast, in bulk soil, the key differential metabolic were Benzoate degradation, Glycolysis gluconeogenesis, Aminobenzoate degradation, ABC transporters, Glyoxylate and dicarboxylate metabolism, oxidative phosphorylation, Degradation of aromatic compounds, Methane metabolism, Pyruvate metabolism and Microbial metabolism diverse environments. Our results indicated that Poa alpigena Lindm rhizosphere soil possessed selectivity for microorganisms in Qinghai Lake Haixin Mountain, and the rhizosphere soil also provided a suitable survival environment for microorganisms., (© 2024. The Author(s) under exclusive licence to Sociedade Brasileira de Microbiologia.)

Metagenomics data provide rich information for the detection of foodborne pathogens from food and environmental samples that are mixed with complex background bacteria strains. While pathogen detection from metagenomic sequencing data has become an activity of increasing interest, shotgun sequencing of uncultured food samples typically produces data that contain reads from many different organisms, making accurate strain typing a challenging task. Particularly, as many pathogens may contain a common set of genes that are highly similar to those from normal bacteria in food samples, traditional strain-level abundance profiling approaches do not perform well at detecting pathogens of very low abundance levels. To overcome this limitation, we propose an abundance correction method based on species-specific genomic regions to achieve high sensitivity and high specificity in target pathogen detection at low abundance., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Omics data usually have ultra-high dimension (p) and small sample size (n). Standard support vector machines (SVMs), which minimize the L 2 norm for the primal variables, only lead to sparse solutions for the dual variables. L 1 based SVMs, directly minimizing the L 1 norm, have been used for feature selection with omics data. However, most current methods directly solve the primal formulations of the problem, which are not computationally scalable. The computational complexity increases with the number of features. In addition, L 1 norm is known to be asymptotically biased and not consistent for feature selection. In this paper, we develop an efficient method for sparse support vector machines with L 0 norm approximation. The proposed method approximates the L 0 minimization through solving a series of L 2 optimization problems, which can be formulated with dual variables. It finds the optimal solution for p primal variables through estimating n dual variables, which is more efficient as long as the sample size is small. L 0 approximation leads to sparsity in both dual and primal variables, and can be used for both feature and sample selections. The proposed method identifies much less number of features and achieves similar performances in simulations. We apply the proposed method to feature selections with metagenomic sequencing and gene expression data. It can identify biologically important genes and taxa efficiently., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Metagenomic sequencing has emerged as a transformative tool in infectious disease diagnosis, offering a comprehensive and unbiased approach to pathogen detection. Leveraging international standards and guidelines is essential for ensuring the quality and reliability of metagenomic sequencing in clinical practice. This review explores the implications of international standards and guidelines for the application of metagenomic sequencing in infectious disease diagnosis. By adhering to established standards, such as those outlined by regulatory bodies and expert consensus, healthcare providers can enhance the accuracy and clinical utility of metagenomic sequencing. The integration of international standards and guidelines into metagenomic sequencing workflows can streamline diagnostic processes, improve pathogen identification, and optimize patient care. Strategies in implementing these standards for infectious disease diagnosis using metagenomic sequencing are discussed, highlighting the importance of standardized approaches in advancing precision infectious disease diagnosis initiatives. [ABSTRACT FROM AUTHOR]

The top-gray chalkiness of hybrid rice (Oryza sativa L.) seeds is a typical phenomenon in hybrid rice seeds. The chalky part of the grain is infected and is the inoculum to infect the normal seeds during storage and soaking. These seed-associated microorganisms were cultivated and sequenced using metagenomics shotgun sequencing to obtain more comprehensive information on the seed-associated microorganisms in this experiment. The results showed that fungi could grow well on the rice flour medium, similar to the ingredients of rice seed endosperms. After the assembly of metagenomic data, a gene catalog was established, comprising 250,918 genes. Function analysis showed that glycoside hydrolases were the dominant enzymes, and the genus Rhizopus accounted for the dominant microorganisms. The fungal species R. microspores, R. delemar, and R. oryzae were likely to be the candidate pathogens in the top-gray chalky grains of hybrid rice seeds. These results will provide a reference for improving hybrid rice processing after harvest. [ABSTRACT FROM AUTHOR]

The microbiome is of great interest due to its potential influence on the occurrence and treatment of some human illnesses. It may be regarded as disruptions to the delicate equilibrium that humans ordinarily maintain with their microorganisms or the microbiota in their environment. The focus of this review is on the methodologies and current understanding of the functional microbiome in pregnancy outcomes. We present how novel techniques bring new insights to the contemporary field of maternal–fetal medicine with a critical analysis. The maternal microbiome in late pregnancy has been extensively studied, although data on maternal microbial changes during the first trimester are rare. Research has demonstrated that, in healthy pregnancies, the origin of the placental microbiota is oral (gut) rather than vaginal. Implantation, placental development, and maternal adaptation to pregnancy are complex processes in which fetal and maternal cells interact. Microbiome dysbiosis or microbial metabolites are rising as potential moderators of antenatal illnesses related to the placenta, such as fetal growth restriction, preeclampsia, and others, including gestational diabetes and preterm deliveries. However, because of the presence of antimicrobial components, it is likely that the bacteria identified in placental tissue are (fragments of) bacteria that have been destroyed by the placenta's immune cells. Using genomic techniques (metagenomics, metatranscriptomics, and metaproteomics), it may be possible to predict some properties of a microorganism's genome and the biochemical (epigenetic DNA modification) and physical components of the placenta as its environment. Despite the results described in this review, this subject needs further research on some major and crucial aspects. The phases of an in utero translocation of the maternal gut microbiota to the fetus should be explored. With a predictive knowledge of the impacts of the disturbance on microbial communities that influence human health and the environment, genomics may hold the answer to the development of novel therapies for the health of pregnant women. [ABSTRACT FROM AUTHOR]

Most zoonotic pathogens originate from mammals and avians, but viral diversity and related biosafety risk assessment in lower vertebrates also need to be explored. Amphibians are an important group of lower vertebrates that played a momentous role in animal evolution. To elucidate the diversity of RNA viruses in one important species of amphibians, the Asiatic toad (Bufo gargarizans), we obtained 44 samples including lung, gut, liver, and kidney tissues from Asiatic toads in Sichuan and Jilin provinces, China, for viral metagenomics sequencing. More than 20 novel RNA viruses derived from the order Bunyavirales and 7 families of Astroviridae, Dicistroviridae, Leviviridae, Partitiviridae, Picornaviridae, Rhabdoviridae, and Virgaviridae were discovered, which were distinct from previously described viruses and formed new clusters, as revealed by phylogenetic analyses. Notably, a novel bastrovirus, AtBastV/GCCDC11/2022, of the family Astroviridae was identified from the gut library, the genome of which contains three open reading frames, with the RNA-dependent RNA polymerase (RdRp) coded by ORF1 closely related to that of hepeviruses, and ORF2 encoding an astrovirus-related capsid protein. Notably, phenuiviruses were discovered for the first time in amphibians. AtPhenV1/GCCDC12/2022 and AtPhenV2/GCCDC13/2022 clustered together and formed a clade with the group of phenuiviruses identified from rodents. Picornaviruses and several invertebrate RNA viruses were also detected. These findings improve our understanding of the high RNA viral diversity in the Asiatic toad and provide new insights in the evolution of RNA viruses in amphibians. [ABSTRACT FROM AUTHOR]

The widespread occurrence of clinically relevant antibiotic resistance within humans, animals, and environment motivates the development of sensitive and accurate detection and quantification methods. Metagenomics and quantitative PCR (qPCR) are amongst the most used approaches. In this study, we aimed to evaluate and compare the performance of these methods to screen antibiotic resistance genes in animal faecal, wastewater, and water samples. Water and wastewater samples were from hospital effluent, different treatment stages of two treatment plants, and of the receiving river at the discharge point. The animal samples were from pig and chicken faeces. Antibiotic resistance gene coverage, sensitivity, and usefulness of the quantitative information were analyzed and discussed. While both methods were able to distinguish the resistome profiles and detect gradient stepwise mixtures of pig and chicken faeces, qPCR presented higher sensitivity for the detection of a few antibiotic resistance genes in water/wastewater. In addition, the comparison of predicted and observed antibiotic resistance gene quantifications unveiled the higher accuracy of qPCR. Metagenomics analyses, while less sensitive, provided a markedly higher coverage of antibiotic resistance genes compared to qPCR. The complementarity of both methods and the importance of selecting the bestmethod according to the study purpose are discussed. [ABSTRACT FROM AUTHOR]

Nitrate-dependent anaerobic methane oxidation (Nitrate-DAMO) is a novel and sustainable process that removes both nitrogen and methane. Previously, the metabolic pathway of Nitrate-DAMO has been intensively studied with some results. However, the production and consumption of nitrous oxide (N 2 O) in the Nitrate-DAMO system were widely disregarded. In this study, a Nitrate-DAMO system was used to investigate the effect of operational parameters (C/N ratio, pH, and temperature) on N 2 O accumulation, and the optimal operating conditions were determined (C/N = 3, pH = 6.5, and temperature = 20 °C). In this study, an enzyme kinetic model was used to fit the nitrate nitrogen degradation and the nitrous oxide production and elimination under different operating conditions. The thermodynamic model of N 2 O production and elimination in the system also has been constructed. Multiple linear regression analysis found that pH was the most important factor influencing N 2 O accumulation. The Metagenomics sequencing results showed that alkaline pH promoted the abundance of Nor genes and denitrifying bacteria, which were significantly and positively correlated with N 2 O emissions. And alkaline pH also promoted the production of Mdo genes related to the N 2 O-driven AOM reaction, indicating that part of the N 2 O was consumed by denitrifying bacteria and the other part was consumed by the N 2 O-driven AOM reaction. These findings reveal the mechanism of N 2 O production and consumption in DAMO systems and provide a theoretical basis for reducing N 2 O production and greenhouse gas emissions in actual operation. [Display omitted] • The optimum operation conditions of the N-DAMO system were explored. • The enzyme kinetic model well fitted to the measured N 2 O production. • Alkaline increased the abundance of Nor genes, leading to N 2 O accumulation. • N 2 O reductase activity decreased with increasing pH. • The production and consumption pathways of N 2 O in the N-DAMO system were proposed. [ABSTRACT FROM AUTHOR]

Background: Increasing evidence has shown that alterations in the intestinal microbiota play an important role in the pathogenesis of psoriasis. The existing relevant studies focus on 16S rRNA gene sequencing, but in-depth research on gene functions and comprehensive identification of microbiota is lacking. Objectives: To comprehensively identify characteristic gut microbial compositions, genetic functions and relative metabolites of patients with psoriasis and to reveal the potential pathogenesis of psoriasis. Methods: DNA was extracted from the faecal microbiota of 30 psoriatic patients and 15 healthy subjects, and metagenomics sequencing and bioinformatic analyses were performed. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database, cluster of orthologous groups (COG) annotations, and metabolic analyses were used to indicate relative target genes and pathways to reveal the pathogenesis of psoriasis. Results: Compared with healthy individuals, the gut microbiota of psoriasis patients displayed an alteration in microbial taxa distribution, but no significant difference in microbial diversity. A distinct gut microbial composition in patients with psoriasis was observed, with an increased abundance of the phyla Firmicutes , Actinobacteria and Verrucomicrobia and genera Faecalibacterium, Bacteroides , Bifidobacterium , Megamonas and Roseburia and a decreased abundance of the phyla Bacteroidetes, Euryarchaeota and Proteobacteria and genera Prevotella, Alistipes , and Eubacterium. A total of 134 COGs were predicted with functional analysis, and 15 KEGG pathways, including lipopolysaccharide (LPS) biosynthesis, WNT signaling, apoptosis, bacterial secretion system, and phosphotransferase system, were significantly enriched in psoriasis patients. Five metabolites, hydrogen sulfide (H2S), isovalerate, isobutyrate, hyaluronan and hemicellulose, were significantly dysregulated in the psoriatic cohort. The dysbiosis of gut microbiota, enriched pathways and dysregulated metabolites are relevant to immune and inflammatory response, apoptosis, the vascular endothelial growth factor (VEGF) signaling pathway, gut-brain axis and brain-skin axis that play important roles in the pathogenesis of psoriasis. Conclusions: A clear dysbiosis was displayed in the gut microbiota profile, genetic functions and relative metabolites of psoriasis patients. This study is beneficial for further understanding the inflammatory pathogenesis of psoriasis and could be used to develop microbiome-based predictions and therapeutic approaches. [ABSTRACT FROM AUTHOR]

• Nitrogen and COD removal performance were well obtained with COD/N ratio of 0.63. • The anammox coupled with DNRA pathway was main reason for SAA increase. • The acetate was mainly used by AnAOB with functional genes ADP-acs and AMP-acs. • The propionate stimulated the enrichment of DB. In current study, the underlying mechanism of coupling dissimilatory nitrate reduction to ammonium (DNRA) pathway with anaerobic ammonium oxidation (anammox) process was explored through metagenomics sequencing analysis in an anammox granular system treating pharmaceutical wastewater under varying COD/N ratios. It was found that average NH 4 +-N and NO 2 --N concentration in effluent was stabled around 2.89 ± 2.53 and 14.23 ± 9.23 mg L-1 with nitrogen removal efficiency (NRE) increase to 85.3% when influent COD/N ratio was around 0.63. Besides, metagenomics sequencing analysis revealed that different COD/N ratios significantly influenced the abundances of functional nitrogen and carbon metabolic genes and microbial community succession. The low COD/N ratio strengthened DNRA pathway in Ca. Kuenenia_stuttgartiensis , as well as the abundance of functional gene nrf. The abundance of the genes encoding acetate degradation, for example, AMP-acs , ADP-acs and AckA increased, suggesting the acetate could stimulate the multiple carbon metabolic potentials of AnAOB. On the contrary, the genes encoding for propionate metabolism were enriched in denitrification bacteria. Our findings revealed the new insight into the mixotrophic characteristic of AnAOB which might help widen engineering application of anammox proocess in various industrial wastewater. [ABSTRACT FROM AUTHOR]

Porcine epidemic diarrhea virus (PEDV) frequently causes diarrhea outbreaks. However, whether newly discovered enteric viruses such as porcine kobuvirus (PKV) and porcine astroviruses (PAstVs) are also correlated with diarrhea is still unclear. Diarrhea outbreaks were reported in a PEDV-vaccinated pig farm in Xinjiang Uygur Autonomous Region of China from 2019 to 2020. PEDV was a common pathogen detected in fecal samples by routine RT-PCR assays. The PEDV positive fecal sample was used for pathogenic analysis due to the failure isolation of PEDV. The challenged neonatal piglets appeared watery diarrhea within one day post infection (dpi) and all died within 6 dpi. Histopathological and immunohistochemical examinations supported that PEDV is a major pathogen causing intestinal lesions. To further explore enteric viruses associated with neonatal piglet diarrhea, metagenomics sequencing was performed for the diarrheic piglets. Remarkably, PKV was the most abundant virus (58.33%) followed by PEDV (34.45%) and PAstVs (7.22%), which were also confirmed by real-time RT-PCR assays. Significant in vivo replications of PEDV and PKV could only be observed in challenged piglets whilst PAstVs maintained similar virus loads in both challenged and mock infected piglets. Overall, this study provides first pathogenic and metagenomic evidence that significant proliferations of PEDV and PKV are closely associated with severe diarrhea in neonatal piglets, while PAstVs likely play limited roles in neonatal piglet diarrhea. • Pathogenic analysis suggested that PEDV is likely associated with 2019–2020 Xinjiang diarrhea outbreaks. • Metagenomics sequencing identified PEDV, PKV and PAstVs from severe diarrheic piglets. • Significant in vivo replications of PEDV and PKV were only detected in diarrheic neonatal piglets. • PAstVs maintained similar virus loads in both challenged and mock infected piglets during the animal study. • PEDV and PKV are closely associated with diarrheic diseases while PAstVs may play a limited role in neonatal piglet diarrhea. [ABSTRACT FROM AUTHOR]