Nanopore Metagenomic Sequencing Research Articles

New insights into honey bee viral and bacterial seasonal infection patterns using third-generation nanopore sequencing on honey bee haemolymph

Honey bees are rapidly declining, which poses a significant threat to our environment and agriculture industry. These vital insects face a disease complex believed to be caused by a combination of parasites, viruses, pesticides, and nutritional deficiencies. However, the real aetiology is still enigmatic. Due to the conventional analysis methods, we still lack complete insights into the honey bee virome and the presence of pathogenic bacteria. To fill this knowledge gap, we employed third-generation nanopore metagenomic sequencing on honey bee haemolymph to monitor the presence of pathogens over almost a year. This study provides valuable insights into the changes in bacterial and viral loads within honey bee colonies. We identified different pathogens in the honey bee haemolymph, which are not included in honey bee screenings. These pathogens comprise the Apis mellifera filamentous virus, Apis rhabdoviruses, and various bacteria such as Frischella sp. and Arsenophonus sp. Furthermore, a sharp contrast was observed between young and old bees. Our research proposes that transgenerational immune priming may play a role in shaping infection patterns in honey bees. We observed a significant increase in pathogen loads in the spring, followed by a notable decrease in pathogen presence during the summer and autumn months. However, certain pathogens seem to be able to evade this priming effect, making them particularly intriguing as potential factors contributing to mortality. In the future, we aim to expand our research on honey bee transgenerational immune priming and investigate its potential in natural settings. This knowledge will ultimately enhance honey bee health and decrease colony mortality.

Evaluation of Commercial RNA Extraction Protocols for Avian Influenza Virus Using Nanopore Metagenomic Sequencing.

Avian influenza virus (AIV) is a significant threat to the poultry industry, necessitating rapid and accurate diagnosis. The current AIV diagnostic process relies on virus identification via real-time reverse transcription-polymerase chain reaction (rRT-PCR). Subsequently, the virus is further characterized using genome sequencing. This two-step diagnostic process takes days to weeks, but it can be expedited by using novel sequencing technologies. We aim to optimize and validate nucleic acid extraction as the first step to establishing Oxford Nanopore Technologies (ONT) as a rapid diagnostic tool for identifying and characterizing AIV from clinical samples. This study compared four commercially available RNA extraction protocols using AIV-known-positive clinical samples. The extracted RNA was evaluated using total RNA concentration, viral copies as measured by rRT-PCR, and purity as measured by a 260/280 absorbance ratio. After NGS testing, the number of total and influenza-specific reads and quality scores of the generated sequences were assessed. The results showed that no protocol outperformed the others on all parameters measured; however, the magnetic particle-based method was the most consistent regarding CT value, purity, total yield, and AIV reads, and it was less error-prone. This study highlights how different RNA extraction protocols influence ONT sequencing performance.

Metagenomic nanopore sequencing for exploring the nature of antimicrobial metabolites of Bacillus haynesii

Multidrug-resistant (MDR) pathogens are a rising global health worry that imposes an urgent need for the discovery of novel antibiotics particularly those of natural origin. In this context, we aimed to use the metagenomic nanopore sequence analysis of soil microbiota coupled with the conventional phenotypic screening and genomic analysis for identifying the antimicrobial metabolites produced by promising soil isolate(s). In this study, whole metagenome analysis of the soil sample(s) was performed using MinION™ (Oxford Nanopore Technologies). Aligning and analysis of sequences for probable secondary metabolite gene clusters were extracted and analyzed using the antiSMASH version 2 and DeepBGC. Results of the metagenomic analysis showed the most abundant taxa were Bifidobacterium, Burkholderia, and Nocardiaceae (99.21%, followed by Sphingomonadaceae (82.03%) and B. haynesii (34%). Phenotypic screening of the respective soil samples has resulted in a promising Bacillus isolate that exhibited broad-spectrum antibacterial activities against various MDR pathogens. It was identified using microscopical, cultural, and molecular methods as Bacillus (B.) haynesii isolate MZ922052. The secondary metabolite gene analysis revealed the conservation of seven biosynthetic gene clusters of antibacterial metabolites namely, siderophore lichenicidin VK21-A1/A2 (95% identity), lichenysin (100%), fengycin (53%), terpenes (100%), bacteriocin (100%), Lasso peptide (95%) and bacillibactin (53%). In conclusion, metagenomic nanopore sequence analysis of soil samples coupled with conventional screening helped identify B. haynesii isolate MZ922052 harboring seven biosynthetic gene clusters of promising antimicrobial metabolites. This is the first report for identifying the bacteriocin, lichenysin, and fengycin biosynthetic gene clusters in B. haynesii MZ922052.

Comprehensive identification of pathogenic microbes and antimicrobial resistance genes in food products using nanopore sequencing-based metagenomics

Foodborne pathogens, particularly antimicrobial-resistant (AMR) bacteria, remain a significant threat to global health. Given the limitations of conventional culture-based approaches, which are limited in scope and time-consuming, metagenomic sequencing of food products emerges as a promising solution. This method provides a fast and comprehensive way to detect the presence of pathogenic microbes and antimicrobial resistance genes (ARGs). Notably, nanopore long-read sequencing provides more accurate bacterial taxonomic classification in comparison to short-read sequencing. Here, we revealed the impact of food types and attributes (origin, retail place, and food processing methods) on microbial communities and the AMR profile using nanopore metagenomic sequencing. We analyzed a total of 260 food products, including raw meat, sashimi, and ready-to-eat (RTE) vegetables. Clostridium botulinum, Acinetobacter baumannii, and Vibrio parahaemolyticus were identified as the top three foodborne pathogens in raw meat and sashimi. Importantly, even with low pathogen abundance, higher percentages of samples containing carbapenem and cephalosporin resistance genes were identified in chicken and RTE vegetables, respectively. In parallel, our results demonstrated that fresh, peeled, and minced foods exhibited higher levels of pathogenic bacteria. In conclusion, this comprehensive study offers invaluable data that can contribute to food safety assessments and serve as a basis for quality indicators.

Nanopore-based metagenomics analysis reveals microbial presence in amniotic fluid: A prospective study

BackgroundCurrent research on amniotic fluid (AF) microbiota yields contradictory data, necessitating an accurate, comprehensive, and scientifically rigorous evaluation. ObjectiveThis study aimed to characterise the microbial features of AF and explore the correlation between microbial information and clinical parameters. Methods76 AF samples were collected in this prospective cohort study. Fourteen samples were utilised to establish the nanopore metagenomic sequencing methodology, whereas the remaining 62 samples underwent a final statistical analysis along with clinical information. Negative controls included the operating room environment (OE), surgical instruments (SI), and laboratory experimental processes (EP) to elucidate the background contamination at each step. Simultaneously, levels of five cytokines (IL-1β, IL-6, IL-8, TNF-α, MMP-8) in AF were assessed. ResultsAmong the 62 AF samples, microbial analysis identified seven without microbes and 55 with low microbial diversity and abundance. No significant clinical differences were observed between AF samples with and without microbes. The correlation between microbes and clinical parameters in AF with normal chromosomal structure revealed noteworthy findings. In particular, the third trimester exhibited richer microbial diversity. Pseudomonas demonstrated higher detection rates and relative abundance in the second trimester and Preterm Birth (PTB) groups. S. yanoikuyae in the PTB group exhibited elevated detection frequencies and relative abundance. Notably, Pseudomonas negatively correlated with activated partial thromboplastin time (APTT) (r = −0.329, P = 0.016), while Staphylococcus showed positive correlations with APTT (r = 0.395, P = 0.003). Furthermore, Staphylococcus negatively correlated with birth weight (r = −0.297, P = 0.034). ConclusionMost AF samples exhibited low microbial diversity and abundance. Certain microbes in AF may correlate with clinical parameters such as gestational age and PTB. However, these associations require further investigation. It is essential to expand the sample size and undertake more comprehensive research to elucidate the clinical implications of microbial presence in AF.

Cross‐Correlation between Biosecurity Measures and the Detection of Viral and Bacterial Agents on German Farms with Respiratory Disease

Effective porcine health management relies majorly on diagnostic tests, vaccination, treatment strategies, and a proper biosecurity management plan. However, understanding the link between circulating microbes and biosecurity measures on a pig farm is not evident. Substantial progress has been made in recent years with the availability of new diagnostic tools (e.g., sequencing‐based diagnostics) and extensive biosecurity management questionnaires. However, the interpretation and correlation of these results are hampered by the abundance of gained (meta)data. Therefore, we aimed to cross‐correlate viral and bacterial pathogens with respiratory tropism detected by third‐generation nanopore metagenomic sequencing with biosecurity measures assessed by Biocheck.UGent™. The study was conducted on 25 sow farms with attached nurseries in Germany with known respiratory distress. The biosecurity level of the study farms complied with the European averages. Interestingly, the farms with the highest biosecurity score showed the lowest overall prevalence of porcine reproductive and respiratory syndrome virus (PRRSV) and Actinobacillus sp.; the circulation of well‐studied pathogenic viruses, such as PRRSV, was correlated with overall lower biosecurity scores, a higher number of stillborn piglets, and cocirculation of porcine parvovirus type 7. Moreover, potential risk factors for lesser‐known agents (e.g., porcine hemagglutinating and encephalomyelitis virus, porcine respiratory coronavirus, and porcine polyomavirus) could also be addressed. For the bacterial pathogen Glaesserella sp., a correlation with increased clinical signs was observed, whereas Lactobacillus sp. and Moraxella sp. are putative biomarkers for pig farms with better biosecurity scores. In conclusion, in‐depth cross‐correlation of (meta)data from new diagnostic platforms with biosecurity measures on pig farms may contribute to a better understanding of new actions in adapting biosecurity measures. This will not only contribute to improved animal welfare and economic productivity but also helping to address (new) zoonotic disease threats and potential treatments.

Performance of metagenomic Next-Generation Sequencing and metagenomic Nanopore Sequencing for the diagnosis of tuberculosis in HIV-positive patients.

Patients who were infected by the Human Immunodeficiency Virus (HIV) could have weakened immunity that is complicated by opportunistic infections, especially for Mycobacterium tuberculosis (MTB). Notably, the HIV-MTB co-infection will accelerate the course of disease progress and greatly increase the mortality of patients. Since the traditional diagnostic methods are time-consuming and have low sensitivity, we aim to investigate the performance of mNGS (metagenomic Next-Generation Sequencing) and mNPS (metagenomic NanoPore Sequencing) for the rapid diagnosis of tuberculosis in HIV-infected patients. The 122 HIV-infected patients were enrolled for the retrospective analysis. All of the patients underwent traditional microbiological tests, mNGS, and (or) mNPS tests. The clinical comprehensive diagnosis was used as the reference standard to compare the diagnostic performance of culture, mNGS, and mNPS on tuberculosis. We also investigate the diagnostic value of mNGS and mNPS on mixed-infection. Furthermore, the treatment adjustment directed by mNGS and mNPS was analyzed. Compared with the composite reference standard, the culture showed 42.6% clinical sensitivity and 100% specificity, and the OMT(other microbiological testing) had 38.9% sensitivity and 100% specificity. The mNGS had 58.6% clinical sensitivity and 96.8% specificity, and the mNPS had 68.0% clinical sensitivity and 100% specificity. The proportion of mixed-infection cases (88.9%) in the TB group was higher than those in the non-TB group (54.8%) and the mNGS and mNPS are more competitive on mixed-infection diagnosis compared with the traditional methods. Furthermore, there are 63 patients (69.2%) and 36 patients (63.2%) achieved effective treatment after receiving the detection of mNPS and mNGS, respectively. Our study indicated that mNPS and mNGS have high sensitivity and specificity for TB diagnosis compared with the traditional methods, and mNPS seems to have better diagnostic performance than mNGS. Moreover, mNGS and mNPS showed apparent advantages in detecting mixed infection. The mNPS and mNGS-directed medication adjustment have effective treatment outcomes for HIV-infected patients who have lower immunity.

Application of Host-Depleted Nanopore Metagenomic Sequencing in the Clinical Detection of Pathogens in Pigs and Cats.

Metagenomic sequencing is a valuable tool for non-specifically detecting various microorganisms in samples, offering unique advantages for detecting emerging pathogens, fastidious or uncultivable pathogens, and mixed infections. It has recently been applied to clinically detect pathogenic microorganisms in animals; however, the high proportion of host genes, expensive sequencing equipment, and the complexity of sequencing and data analysis methods have limited its clinical utility. In this study, a combination of tissue homogenization and nuclease digestion was employed to remove host genes from pig and cat samples; DNA and RNA were then extracted and subjected to nonselective PCR amplification to simultaneously detect DNA and RNA pathogen genomes using R9.4.1 or R10.4.1 flow cells on the MinION platform. Real-time pathogen detection was conducted using EPI2M WIMP, and viral genome assembly was performed using NanoFilt, minimap2, samtools, and ivar. Pathogens in five clinical samples (serum, nasopharyngeal swab, feces, or ascites) from cats and four clinical samples (lung or small intestine tissue) from pigs were examined by metagenomic sequencing, and the results were consistent with those obtained by PCR and bacterial culture. Additionally, we detected four viruses and three bacteria that may be associated with diseases. A comparison of results before and after host gene removal in three samples showed a 9-50% reduction in host genes. We also compared the assembly efficiency of six virus genomes and found that data volumes ranging from 3.3 to 98.3 MB were sufficient to assemble >90% of the viral genomes. In summary, this study utilized optimized nanopore metagenomic sequencing and analysis methods to reduce host genes, decrease the required data volume for sequencing analysis, and enable real-time detection to determine when to stop sequencing. The streamlined sequencing and analysis process overcomes barriers to the veterinary clinical application of metagenomic sequencing and provides a reference for clinical implementation.

CgMSI: pathogen detection within species from nanopore metagenomic sequencing data

BackgroundMetagenomic sequencing is an unbiased approach that can potentially detect all the known and unidentified strains in pathogen detection. Recently, nanopore sequencing has been emerging as a highly potential tool for rapid pathogen detection due to its fast turnaround time. However, identifying pathogen within species is nontrivial for nanopore sequencing data due to the high sequencing error rate.ResultsWe developed the core gene alleles metagenome strain identification (cgMSI) tool, which uses a two-stage maximum a posteriori probability estimation method to detect pathogens at strain level from nanopore metagenomic sequencing data at low computational cost. The cgMSI tool can accurately identify strains and estimate relative abundance at 1× coverage.ConclusionsWe developed cgMSI for nanopore metagenomic pathogen detection within species. cgMSI is available at https://github.com/ZHU-XU-xmu/cgMSI.

Molecular diagnostic approaches for SARS-CoV-2 detection and pathophysiological consequences.

SARS-CoV-2, a novel coronavirus within the Coronaviridae family, is the causative agent behind the respiratory ailment referred to as COVID-19. Operating on a global scale, COVID-19 has led to a substantial number of fatalities, exerting profound effects on both public health and the global economy. The most frequently reported symptoms encompass fever, cough, muscle or body aches, loss of taste or smell, headaches, and fatigue. Furthermore, a subset of individuals may manifest more severe symptoms, including those consistent with viral pneumonitis, which can be so profound as to result in fatalities. Consequently, this situation has spurred the rapid advancement of disease diagnostic technologies worldwide. Predominantly employed in diagnosing COVID-19, the real-time quantitative reverse transcription PCR has been the foremost diagnostic method, effectively detecting SARS-CoV-2 viral RNA. As the pandemic has evolved, antigen and serological tests have emerged as valuable diagnostic tools. Antigen tests pinpoint specific viral proteins of SARS-CoV-2, offering swift results, while serological tests identify the presence of antibodies in blood samples. Additionally, there have been notable strides in sample collection methods, notably with the introduction of saliva-based tests, presenting a non-invasive substitute to nasopharyngeal swabs. Given the ongoing mutations in SARS-CoV-2, there has been a continuous need for genomic surveillance, encompassing full genome sequencing and the identification of new variants through Illumina technology and, more recently, nanopore metagenomic sequencing (SMTN). Consequently, while diagnostic testing methods for COVID-19 have experienced remarkable progress, no test is flawless, and there exist limitations with each technique, including sensitivity, specificity, sample collection, and the minimum viral load necessary for accurate detection. These aspects are comprehensively addressed within this current review.

Porcine ear necrosis: characterization of lesions and associated pathogens

Porcine ear necrosis (PEN) is characterized by ulcerative lesions of the ear auricle. To investigate that problem, three farms with PEN in nursery pigs were included, and the study aim was to characterize PEN and the potential role of pathogens and mycotoxins. Within each farm, one batch of weaned piglets was included and the prevalence and severity of PEN were monitored for 6–7 weeks. Within each batch, 30 PEN-affected/non-affected animals were randomly selected. Blood samples were taken from these animals, to assess the systemic presence of pathogens and mycotoxins, as well as punch biopsies from the ear auricle for histopathological examination. From 10 animals, scrapings and swabs from the lesions were subjected to nanopore metagenomic sequencing and bacteriological cultivation, respectively. In all three farms, lesions appeared within 3–4 weeks post-weaning. The prevalence at the end of the nursery was 33%, 24%, and 46% for farms A, B, and C, respectively. Most affected pigs had mild to moderate lesions. Blood samples revealed low to very low levels of pathogens and mycotoxins. Different bacteria such as Staphylococcus, Streptococcus, Fusobacterium, Mycoplasma, and Clostridium species were identified by sequencing in the scrapings. The first two pathogens were also most often identified in bacterial cultures. Mycoplasma hyopharyngis was only found in PEN-affected pigs. Histopathological changes were primarily observed in the outer layer of the epidermis. The results suggest that PEN lesions develop by damage to the outer part of the skin e.g. by ear suckling or biting, followed by multiplication of opportunistic pathogens.

In situ Nanopore sequencing reveals metabolic characteristics of the Qilian glacier meltwater microbiome.

Nanopore metagenomic sequencing enables rapid annotating microbiological ecosystems, and the previous glacier-related sequencing applications (e.g., targeted ice sheets, ice lake, and cryoconite holes) inspire us to explore high-altitude glacier meltwater at Qilian Mountain, China (3000 to 4000 m above sea level, MASL). Our findings suggest that (1) despite only several hundred meters apart, the microbial communities and functionalities are quite different among vertical alpine distributions; (2) the high-altitude Qilian meltwater microbiome serve several main metabolic functions, including sulfur oxidation, selenite decomposing, photosynthesis, energy production, enzymic, and UV tolerant activities. Meanwhile, our Nanopore metagenomic results indicate that the microbial classifications and functionalities (e.g., chaperones, cold-shock, specific tRNA species, oxidative stress, and resistance to toxic compounds) of Qilian meltwater are highly consistent with the other glacial microbiome, emphasizing that only certain microbial species can survive in the cold environment and the molecular adaptions and lifestyles remain stable all over the world. Besides, we have shown Nanopore metagenomic sequencing can provide reliable prokaryotic classifications within or among studies, which therefore can encourage more applications in the field given faster turnaround time. However, we recommend accumulating at least 400 ng nucleic acids (after extraction) and maximizing Nanopore library preparation efficiency before on-site sequencing to obtain better resolutions.

Focus Issue Articles on Diagnostic Assay Development and Validation: The Science of Getting It Right

Focus Issue Articles on Diagnostic Assay Development and Validation: The Science of Getting It Right

Impact of nanopore-based metagenome sequencing on tick-borne virus detection.

We evaluated metagenomic nanopore sequencing (NS) in field-collected ticks and compared findings from amplification-based assays. Forty tick pools collected in Anatolia, Turkey and screened by broad-range or nested polymerase chain reaction (PCR) for Crimean-Congo Hemorrhagic Fever Virus (CCHFV) and Jingmen tick virus (JMTV) were subjected to NS using a standard, cDNA-based metagenome approach. Eleven viruses from seven genera/species were identified. Miviruses Bole tick virus 3 and Xinjiang mivirus 1 were detected in 82.5 and 2.5% of the pools, respectively. Tick phleboviruses were present in 60% of the pools, with four distinct viral variants. JMTV was identified in 60% of the pools, where only 22.5% were PCR-positive. CCHFV sequences characterized as Aigai virus were detected in 50%, where only 15% were detected by PCR. NS produced a statistically significant increase in detection of these viruses. No correlation of total virus, specific virus, or targeted segment read counts was observed between PCR-positive and PCR-negative samples. NS further enabled the initial description of Quaranjavirus sequences in ticks, where human and avian pathogenicity of particular isolates had been previously documented. NS was observed to surpass broad-range and nested amplification in detection and to generate sufficient genome-wide data for investigating virus diversity. It can be employed for monitoring pathogens in tick vectors or human/animal clinical samples in hot-spot regions for examining zoonotic spillover.

Rapid viral metagenomics using SMART-9N amplification and nanopore sequencing.

Emerging and re-emerging viruses are a global health concern. Genome sequencing as an approach for monitoring circulating viruses is currently hampered by complex and expensive methods. Untargeted, metagenomic nanopore sequencing can provide genomic information to identify pathogens, prepare for or even prevent outbreaks. SMART (Switching Mechanism at the 5' end of RNA Template) is a popular approach for RNA-Seq but most current methods rely on oligo-dT priming to target polyadenylated mRNA molecules. We have developed two random primed SMART-Seq approaches, a sequencing agnostic approach 'SMART-9N' and a version compatible rapid adapters available from Oxford Nanopore Technologies 'Rapid SMART-9N'. The methods were developed using viral isolates, clinical samples, and compared to a gold-standard amplicon-based method. From a Zika virus isolate the SMART-9N approach recovered 10kb of the 10.8kb RNA genome in a single nanopore read. We also obtained full genome coverage at a high depth coverage using the Rapid SMART-9N, which takes only 10 minutes and costs up to 45% less than other methods. We found the limits of detection of these methods to be 6 focus forming units (FFU)/mL with 99.02% and 87.58% genome coverage for SMART-9N and Rapid SMART-9N respectively. Yellow fever virus plasma samples and SARS-CoV-2 nasopharyngeal samples previously confirmed by RT-qPCR with a broad range of Ct-values were selected for validation. Both methods produced greater genome coverage when compared to the multiplex PCR approach and we obtained the longest single read of this study (18.5 kb) with a SARS-CoV-2 clinical sample, 60% of the virus genome using the Rapid SMART-9N method. This work demonstrates that SMART-9N and Rapid SMART-9N are sensitive, low input, and long-read compatible alternatives for RNA virus detection and genome sequencing and Rapid SMART-9N improves the cost, time, and complexity of laboratory work.

Characterization and simulation of metagenomic nanopore sequencing data with Meta-NanoSim.

Nanopore sequencing is crucial to metagenomic studies as its kilobase-long reads can contribute to resolving genomic structural differences among microbes. However, sequencing platform-specific challenges, including high base-call error rate, nonuniform read lengths, and the presence of chimeric artifacts, necessitate specifically designed analytical algorithms. The use of simulated datasets with characteristics that are true to the sequencing platform under evaluation is a cost-effective way to assess the performance of bioinformatics tools with the ground truth in a controlled environment. Here, we present Meta-NanoSim, a fast and versatile utility that characterizes and simulates the unique properties of nanopore metagenomic reads. It improves upon state-of-the-art methods on microbial abundance estimation through a base-level quantification algorithm. Meta-NanoSim can simulate complex microbial communities composed of both linear and circular genomes and can stream reference genomes from online servers directly. Simulated datasets showed high congruence with experimental data in terms of read length, error profiles, and abundance levels. We demonstrate that Meta-NanoSim simulated data can facilitate the development of metagenomic algorithms and guide experimental design through a metagenome assembly benchmarking task. The Meta-NanoSim characterization module investigates read features, including chimeric information and abundance levels, while the simulation module simulates large and complex multisample microbial communities with different abundance profiles. All trained models and the software are freely accessible at GitHub: https://github.com/bcgsc/NanoSim.

Viral and Bacterial Profiles in Endemic Influenza A Virus Infected Swine Herds Using Nanopore Metagenomic Sequencing on Tracheobronchial Swabs.

Swine influenza A virus (swIAV) plays an important role in porcine respiratory infections. In addition to its ability to cause severe disease by itself, it is important in the multietiological porcine respiratory disease complex. Still, to date, no comprehensive diagnostics with which to study polymicrobial infections in detail have been offered. Hence, veterinary practitioners rely on monospecific and costly diagnostics, such as Reverse Transcription quantitative PCR (RT-qPCR), antigen detection, and serology. This prevents the proper understanding of the entire disease context, thereby hampering effective preventive and therapeutic actions. A new, nanopore-based, metagenomic diagnostic platform was applied to study viral and bacterial profiles across 4 age groups on 25 endemic swIAV-infected German farms with respiratory distress in the nursery. Farms were screened for swIAV using RT-qPCR on nasal and tracheobronchial swabs (TBS). TBS samples were pooled per age, prior to metagenomic characterization. The resulting data showed a correlation between the swIAV loads and the normalized reads, supporting a (semi-)quantitative interpretation of the metagenomic data. Interestingly, an in-depth characterization using beta diversity and PERMANOVA analyses allowed for the observation of an age-dependent interplay of known microbial agents. Also, lesser-known microbes, such as porcine polyoma, parainfluenza, and hemagglutinating encephalomyelitis viruses, were observed. Analyses of swIAV incidence and clinical signs showed differing microbial communities, highlighting age-specific observations of various microbes in porcine respiratory disease. In conclusion, nanopore metagenomics were shown to enable a panoramic view on viral and bacterial profiles as well as putative pathogen dynamics in endemic swIAV-infected herds. The results also highlighted the need for better insights into lesser studied agents that are potentially associated with porcine respiratory disease. IMPORTANCE To date, no comprehensive diagnostics for the study of polymicrobial infections that are associated with porcine respiratory disease have been offered. This precludes the proper understanding of the entire disease landscape, thereby hampering effective preventive and therapeutic actions. Compared to the often-costly diagnostic procedures that are applied for the diagnostics of porcine respiratory disease nowadays, a third-generation nanopore sequencing diagnostics workflow presents a cost-efficient and informative tool. This approach offers a panoramic view of microbial agents and contributes to the in-depth observation and characterization of viral and bacterial profiles within the respiratory disease context. While these data allow for the study of age-associated, swIAV-associated, and clinical symptom-associated observations, it also suggests that more effort should be put toward the investigation of coinfections and lesser-known pathogens (e.g., PHEV and PPIV), along with their potential roles in porcine respiratory disease. Overall, this approach will allow veterinary practitioners to tailor treatment and/or management changes on farms in a quicker, more complete, and cost-efficient way.

Comparison of Third-Generation Sequencing Technology and Traditional Microbiological Detection in Pathogen Diagnosis of Lower Respiratory Tract Infection.

It is common to obtain a low detection rate and unsatisfactory detection results in complex infection or rare pathogen detection. This retrospective study aimed to illustrate the application value and prospect of the third-generation sequencing technology in lower respiratory tract infection disease. This study recruited 70 patients with lower respiratory tract infection (LRTI). Pathogen detection of bronchoalveolar lavage fluid (BALF) from all patients was performed using nanopore metagenomic sequencing technology and traditional culture. BALF culture combined with quantitiative PCR (qPCR) was used as a reference standard to analyze the sensitivity and specificity of nanopore sequencing technology. The current study also collected the examination results of enrolled samples using technical methods sputum culture, tuberculosis DNA (TB-DNA), and Xpert MTB/RIF and analyzed the detection efficiency of nanopore sequencing for Mycobacterium tuberculosis. The positive rates of pathogens in 70 BALF samples detected by conventional culture and nanopore sequencing were 25.71% and 84.29%, respectively. Among the 59 positive BALF cases using nanopore sequencing, a total of 31 pathogens were identified, of which the proportions of bacteria, fungi, viruses, and other pathogens were 50%, 17%, 32%, and 1%, respectively. Using the results combined with culture and qPCR detection methods as the standard, the pathogen detection of BALF using nanopore sequencing had a sensitivity of 70% and a specificity of 91.7%. Additionally, the positive rate of the detection of M. tuberculosis using nanopore sequencing was 33.3% (6/18). The clinical medication plans of 74.3% (52/70) of the patients were referred to the nanopore sequencing results, of which 31 cases changed their treatment strategy, 21 supported the previous treatment plans, and 90% (47/52) of the patients finally had clinical improvement. BALF detection using nanopore sequencing technology improves the process of detecting pathogens in patients with LRTI, especially for M. tuberculosis, fungi, and viruses, by reducing the report time from three days to six hours. The clinical application prospect of nanopore sequencing technology is promising in the pathogen diagnosis of LRTI.

Metagenomic nanopore sequencing versus conventional diagnosis for identification of the dieback pathogens of mango trees.

Dieback is one of the most dangerous fungal diseases affecting mango trees. In this study, nanopore metagenome sequencing of the root-soil samples and infected plant tissues was conducted to identify the fungal pathogens present. Soil analysis of the infected mango trees showed the abundance of the Dikarya subkingdom (59%) including Lasiodiplodia theobromae (15%), Alternaria alternata (6%), Ceratocystis huliohia and Colletotrichum gloeosporioides. Analysis of the infected plant tissues revealed the presence of A. alternata (34%). The data were deposited in the National Center of Biotechnology Information (PRJNA767267). In conclusion, nanopore metagenome sequencing analysis was a valuable tool to rapidly identify dieback-associated fungal pathogens.

Metagenomic nanopore sequencing of ocular microbiome in patients with meibomian gland dysfunction.

To explore the composition of the ocular microbiome in patients with Meibomian gland dysfunction (MGD) using metagenomic nanopore sequencing. A total of 98 participants were recruited from September to December 2021, including 86 patients with MGD and 12 controls. Symptoms and signs of dry eye were assessed, and bacterial samples in the conjunctival sac (CS) and meibomian gland (MG) secretions were then identified by bacterial culture identification and metagenomic nanopore sequencing. The positive rate of CS bacterial culture in the MGD group was significantly higher than that in the normal group. A more complex composition of bacterial genera was detected in the mild and moderate MGD groups than in the control. However, the severe MGD groups had the simplest composition of bacteria. Metagenomic nanopore sequencing detected more species of bacteria than traditional culture. The CS and MG of MGD patients may have different degrees of bacterial microbiota imbalance. Metagenomic nanopore sequencing technology provides a new way for us to understand the composition of "real-world" ocular surface microorganisms.