The PROGRESS randomised trial (ClinicalTrials.gov: NCT03333304) showed that early stopof antibiotics guided by procalcitonin (PCT) decreased the incidence of infections by multidrug-resistant organisms and/or Clostridioides difficile and was associated with survival benefit. This study was conducted to investigate whether this survival benefit is associated with microbiome dysbiosis. Patients with sepsis due to lung infection, acute pyelonephritis or primary bacteraemia were randomised to standard-of-care (SoC) duration of antibiotics or early stop using PCT. Faecal samples were collected before, and 7 and 28 days after randomisation and analysed using 16S rRNA Nanopore sequencing. Calprotectin was measured using an enzyme immunoassay. Median (Q1-Q3) antimicrobial duration was 5 (5-7.5) days in the PCT arm and 11 (8-15) days in the SoC arm (P < 0.001). Faecal calprotectin levels were similar in the two treatment arms at baseline. By day 7, the levels of faecal calprotectin were significantly increased in the SoC arm (P = 0.002) but were unchanged in the PCT arm. Microbiome α- and β-diversity was similar at baseline in the PCT (n=81) and SoC (n=76) treatment arms. Shannon's index was significantly lower in the SoC arm on day 7 compared with baseline (median [Q1-Q3], 2.88 [2.37-3.39] at day 1 vs. 2.24 [1.52-3.08] at day 7; Pt-test = 0.0013). This was not the case for the PCT arm (median [Q1-Q3], 2.73 [2.26-3.4] at day 1 vs. 2.43 [1.81-3.21] at day 7; Pt-test = 0.037, Bonferroni corrected α = 0.0125). The relative abundance of Actinomycetota and Pseudomonadota was decreased in the PCT arm by day 7 and that of Bacillota was increased. Early PCT-guided stop of antibiotics contributes to decreased microbiome dysbiosis by day 7.

Antibiotics are used in animal husbandry to control infectious diseases. Different stressors can compromise animal health, leaving piglets vulnerable to pathogens, especially enterotoxigenic Escherichia coli (ETEC), which causes post-weaning diarrhoea (PWD), the major source of mortality and morbidity in swine production. Furthermore, PWD is a recurrent disease for certain farms, suggesting a link between gut microbial composition and animal health. The aim of this study was to identify the intestinal microbiota of pigs on farms with high health status (HHS) and low health status (LHS) to determine the relationships between sanitary status and gut health. Therefore, three pig farms with LHS presenting recurrent problems of PWD and three farms with HHS were selected to characterise the intestinal microbiome of sows and their piglets. 16 S rRNA gene sequencing technology was used to determine the associations of the gut microbiome with health. With the aim of bringing the MinION Nanopore device to the field for its portability and taxonomic resolution, the results obtained with Illumina were compared to those obtained with Nanopore.

Overall, the results indicated remarkable differences in intestinal microbial communities between animals from LHS farms and those from HHS farms, suggesting that the microbiomes of LHS animals were enriched with potential pathogenic microorganisms, mainly from the Pseudomonadota phylum, such as the genus Escherichia-Shigella, and their associated related species. Moreover, animals from HHS were enriched with beneficial microorganisms, such as Lactobacillus spp., Christensenellaceae R7 group, Treponema, Acetitomaculum and Oscillospiraceae UCG-005.

This study identifies potential microorganisms that may contribute to health and disease in pig farms with HHS and LHS, suggesting that tracking their occurrence might provide insight into sanitary conditions. Moreover, this research highlights the compatibility between Illumina and Nanopore sequencing platforms, justifying the use of MinION Nanopore device in field applications for in situ studies of PWD. This application has the potential to enhance sustainable economic growth in swine farms by enabling more effective monitoring and management of animal health.

Functional dyspepsia (FD) is a multifactorial disorder as its development may be based on several different pathophysiological mechanisms. Interaction of gut microbiome with the host has been proposed as a potential mechanism involved in the disease's pathogenesis.

We aimed to characterize microbiome profiling on duodenal luminal content (DLC) of FD patients and compare it to that of controls (CG) and patients with irritable bowel syndrome (IBS). Outpatients fulfilling Rome IV criteria for FD, IBS, and control group (CG) underwent upper gastrointestinal endoscopy and 2 cc of duodenal aspirate (3rd - 4th part) was aspirated in sterile traps. Duodenal microbiome was assessed after DNA extraction and 16S gene-based sequencing on Oxford Nanopore MinION followed by EPI2ME analysis (ONT/Metrich-ore Ltd). Bioanalysis of the microbiome (alpha-, beta-diversity, comparisons of relative abundances for all taxonomic ranks) was implemented in Python. Multiple group means comparisons were performed with one-way Analysis of Variance (ANOVA) and Kruskal-Wallis test with Tuckey's and Dunn's post hoc tests respectively, in case of significance (P-value <0.05).

20 subjects with FD (8 females; age 49.9 ± 13.5 yrs.), 20 with IBS (14 females; age 57.6 ± 14.8 yrs.) and 10 CG (6 females; age 49.2 ± 13.8 yrs.) had their DLC analyzed. The α-diversity index of subjects with FD was significantly lower compared to controls (Shannon's index, p = 0.0218) and similar to that of patients with IBS. Principal Coordinate Analysis (PCoA) generated from species relative abundances (beta-diversity) showed no difference in the DLC profile of subjects with FD and IBS when compared to controls (p = 0.513). Compared to controls, the relative abundance (RA) of Chloroflexota phylum was lower in subjects with FD (p = 0.017) and IBS (p = 0.026), respectively. Additionally, the RA of the Rhodothermota and Thermotogota phyla was lower in FD (p = 0.017 and p = 0.018, respectively) but not in IBS patients (p = 0.15 and p = 0.06, respectively) compared to controls. Interestingly, the RA of specific taxa from Chloroflexota, Rhodothermota and Thermotogota phyla were consistently lower in subjects with FD when compared to CG but similar to IBS, during analysis of all the subsequent major ranks of taxonomy. At the class level, there were significant differences in Syntrophobacteria, Acidithiobacillia, Cytophagia and Flavobacteriia between the FD and CG groups (p < 0.05), but no such difference between FD and IBS was found. Finally, multiple significant differences at the order, family, genus and species level between the FD and CG groups were also detected. A positive relationship between the RA of Streptococcus and those from genus Granulicatella was observed both in FD (p = 0.014) and IBS (p = 0.014) patients.

The microbiome profiling from duodenal luminal content of FD patients is significantly different to that of controls, including lower microflora diversity, different microflora structure/composition and specific taxa. Similar differences in the DLC between FD and IBS patients were not evident.

Biotinidase deficiency (BTD) is an autosomal recessive disorder characterized by impaired recycling of the water-soluble vitamin biotin which leads to a spectrum of clinical manifestations ranging from mild to severe, including mainly neurological and cutaneous symptoms. Biotin supplementation is a cornerstone of treatment, but diagnosis often relies on measuring serum enzyme activity, which needs to be confirmed by genetic analysis. Thus, molecular methods become necessary in the differential diagnosis of BTD. Accordingly, countries with a high-incidence have implemented next-generation sequencing (NGS) techniques to newborn screening programs for BT. Nevertheless, NGS platforms, while well-established, present challenges in cost, labor, accessibility, and duration for newborn screening programs targeting BTD, therefore these limitations necessitate the exploration of alternative systems to ensure efficient and widespread screening. Here, third-generation sequencing platforms, notably Oxford Nanopore Technology (ONT), present promising solutions to the associated challenges. Hence, in the present study, we aimed to develop an ONT-based assay for the screening of BTD gene. After designing and optimizing primers for long-PCR using reference DNA, we assessed the performance of the ONT assay in BTD patients previously diagnosed by enzyme assay and confirmed using Illumina-based sequencing. The results demonstrate a strong correlation between the two methods, indicating the reliability of the ONT-based assay. Moreover, this first in-house single gene testing specifically tailored for BTD successfully detected previously known genetic variants with high sequencing depths, affirming the effectiveness of ONT-based sequencing in human genetics.

Fungi are talented producers of secondary metabolites with applications in the pharmaceutical and agrochemical sectors. Aspergillus wentii CBS 141173 has gathered research interest due to its ability to produce high-value norditerpenoid compounds, including anticancer molecules. In this study, we aimed to expand the genomic information available for A. wentii to facilitate the identification of terpenoid biosynthetic genes that may be involved in the production of bioactive molecules.

Long-read genome sequencing of Aspergillus wentii CBS 141173 was conducted using Oxford Nanopore Technologies (ONT) MinION MK1C. In addition, paired-end stranded RNA-seq data from two time points, 7 days and 30 days, was used for functional annotation of the assembled genome. Overall, we assembled a genome of approximately 31.2 Mb and identified 66 biosynthetic gene clusters from the annotated genome. Metabolic extracts of A. wentii were analysed and the production of the bioactive terpenoid asperolide A was confirmed. We further mined the assembled and annotated genome for BGCs involved in terpenoid pathways using a combination of antiSMASH and local BlastP and identified 16 terpene synthases. Phylogenetic analysis was conducted and allowed us to establish relationships with other characterised terpene synthases. We identified two terpene clusters potentially involved in pimarane-like diterpenoid biosynthesis. Finally, the analysis of the 16 terpene synthases in our 7-day and 30-day transcriptomic data suggested that only four of them were constitutively expressed under laboratory conditions.

These results provide a scaffold for the future exploration of terpenoid biosynthetic pathways for bioactive molecules in A. wentii. The terpenoid clusters identified in this study are candidates for heterologous gene expression and/or gene disruption experiments. The description and availability of the long-read genome assembly of A. wentii CBS 141173 further provides the basis for downstream genome analysis and biotechnological exploitation of this species.

The rapid advancements in sequencing technologies and bioinformatics have enabled metagenomic research of complex microbial systems, but reliable results depend on consistent laboratory and bioinformatics approaches. Current efforts to identify best practices often focus on optimizing specific steps, making it challenging to understand the influence of each stage on microbial population analysis and compare data across studies. This study evaluated DNA extraction, library construction methodologies, sequencing platforms, and computational approaches using a dog stool sample, two synthetic microbial community mixtures, and various sequencing data sources. Our work, the most comprehensive evaluation of metagenomic methods to date. We developed a software tool, termed minitax, which provides consistent results across the range of platforms and methodologies. Our findings showed that the Zymo Research Quick-DNA HMW MagBead Kit, Illumina DNA Prep library preparation method, and the minitax bioinformatics tool were the most effective for high-quality microbial diversity analysis. However, the effectiveness of pipelines or method combinations is sample-specific, making it difficult to identify a universally optimal approach. Therefore, employing multiple approaches is crucial for obtaining reliable outcomes in microbial systems.

Small subunit (SSU) ribosomal RNA (rRNA) gene amplicon sequencing is a foundational method in microbial ecology. Currently, short-read platforms are commonly employed for high-throughput applications of SSU rRNA amplicon sequencing, but at the cost of poor taxonomic classification due to limited fragment lengths. The Oxford Nanopore Technologies (ONT) platform can sequence full-length SSU rRNA genes, but its lower raw-read accuracy has so-far limited accurate taxonomic classification and de novo feature generation. Here, we present a sequencing workflow, termed ssUMI, that combines unique molecular identifier (UMI)-based error correction with newer (R10.4+) ONT chemistry and sample barcoding to enable high throughput near full-length SSU rRNA (e.g. 16S rRNA) amplicon sequencing. The ssUMI workflow generated near full-length 16S rRNA consensus sequences with 99.99% mean accuracy using a minimum subread coverage of 3×, surpassing the accuracy of Illumina short reads. The consensus sequences generated with ssUMI were used to produce error-free de novo sequence features with no false positives with two microbial community standards. In contrast, Nanopore raw reads produced erroneous de novo sequence features, indicating that UMI-based error correction is currently necessary for high-accuracy microbial profiling with R10.4+ ONT sequencing chemistries. We showcase the cost-competitive scalability of the ssUMI workflow by sequencing 87 time-series wastewater samples and 27 human gut samples, obtaining quantitative ecological insights that were missed by short-read amplicon sequencing. ssUMI, therefore, enables accurate and low-cost full-length 16S rRNA amplicon sequencing on Nanopore, improving accessibility to high-resolution microbiome science.

Metagenomics has been transformative in our understanding of the diversity and function of soil microbial communities. Applying long read sequencing to whole genome shotgun metagenomics has the potential to revolutionise soil microbial ecology through improved taxonomic classification, functional characterisation and metagenome assembly. However, optimisation of robust methods for long read metagenomics of environmental samples remains undeveloped. In this study, Oxford Nanopore sequencing using samples from five commercially available soil DNA extraction kits was compared across four soil types, in order to optimise read length and reproducibility for comparative long read soil metagenomics. Average extracted DNA lengths varied considerably between kits, but longer DNA fragments did not translate consistently into read lengths. Highly variable decreases in the length of resulting reads from some kits were associated with poor classification rate and low reproducibility in microbial communities identified between technical repeats. Replicate samples from other kits showed more consistent conversion of extracted DNA fragment size into read length and resulted in more congruous microbial community representation. Furthermore, extraction kits showed significant differences in the community representation and structure they identified across all soil types. Overall, the QIAGEN DNeasy PowerSoil Pro Kit displayed the best suitability for reproducible long-read WGS metagenomic sequencing, although further optimisation of DNA purification and library preparation may enable translation of higher molecular weight DNA from other kits into longer read lengths. These findings provide a novel insight into the importance of optimising DNA extraction for achieving replicable results from long read metagenomic sequencing of environmental samples.

Nanopore sequencing technology has enabled the rapid, on-site taxonomic identification of samples from anything and anywhere. However, sequencing errors, inadequate databases, as well as the need for bioinformatic expertise and powerful computing resources, have hampered the widespread use of the technology for pathogen identification in the agricultural sector. Here we present RAPiD, a lightweight and accurate real-time taxonomic profiling pipeline. Compared to other metagenomic profilers, RAPiD had a higher classification precision achieved through the use of a curated, non-redundant database of common agricultural pathogens and extensive quality filtering of alignments. On a fungal, bacterial and mixed mock community RAPiD was the only pipeline to detect all members of the communities. We also present a protocol for in-field sample processing enabling pathogen identification from plant sample to sequence within 3 h using low-cost equipment. With sequencing costs continuing to decrease and more high-quality reference genomes becoming available, nanopore sequencing provides a viable method for rapid and accurate pathogen identification in the field. A web implementation of the RAPiD pipeline for real-time analysis is available at https://agrifuture.senckenberg.de.

Escherichia coli and total coliforms are important tools for identifying potential faecal contamination in drinking water. However, metagenomics offers a powerful approach for delving deeper into a bacterial community when E. coli or total coliforms are detected. Metagenomics can identify microbes native to water systems, track community changes and potential pathogens introduced by contamination events, and evaluate the effectiveness of treatment processes. Here, we demonstrate how the dual application of traditional monitoring practices and metagenomics can improve monitoring and surveillance for water resource management. The robustness of long-read metagenomics across replicates is demonstrated by the effect and interaction between manganese filters and bacterial communities, as well as the impact of chlorination after coliform detection. These examples reveal how metagenomics can identify the complex bacterial communities in the distribution system and the source waters used to supply drinking water treatment plants (DWTPs). The knowledge gained increases confidence in identified causes and mitigations of potential contamination events. By exploring bacterial communities, we can gain additional insights into the impact of faecal contamination events and treatment processes. This insight enables more precise remediation actions and enhances confidence in communicating health risks to drinking water operators and the public.

Fish were kept for six weeks at three different initial stocking densities and water O2 concentrations (low-LD, 8.5 kg/m3 and 95-70% O2 saturation; medium-MD, 17 kg/m3 and 55-75% O2 saturation; high-HD, 25 kg/m3 and 60-45% O2 saturation), with water temperature increasing from 19 °C to 26-27 °C. The improvement in growth performance with the decrease in stocking density was related to changes in skin and intestinal mucosal microbiomes. Changes in microbiome composition were higher in skin, with an increased abundance of Alteromonas and Massilia in HD fish. However, these bacteria genera were mutually exclusive, and Alteromonas abundance was related to a reactive behavior and systemic growth regulation via the liver Gh/Igf system, while Massilia was correlated to a proactive behavior and a growth regulatory transition towards muscle rather than liver. At the intestinal level, microbial abundance showed an opposite trend for two bacteria taxa, rendering in a low abundance of Reyranella and a high abundance of Prauserella in HD fish. This trend was correlated with up-regulated host gene expression, affecting the immune response, epithelial cell turnover, and abiotic stress response. Most of the observed responses are adaptive in nature, and they would serve to infer new welfare indicators for increased stress resilience.

Metagenome community analyses, driven by the continued development in sequencing technology, is rapidly providing insights in many aspects of microbiology and becoming a cornerstone tool. Illumina, Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio) are the leading technologies, each with their own advantages and drawbacks. Illumina provides accurate reads at a low cost, but their length is too short to close bacterial genomes. Long reads overcome this limitation, but these technologies produce reads with lower accuracy (ONT) or with lower throughput (PacBio high-fidelity reads). In a critical first analysis step, reads are assembled to reconstruct genomes or individual genes within the community. However, to date, the performance of existing assemblers has never been challenged with a complex mock metagenome. Here, we evaluate the performance of current assemblers that use short, long or both read types on a complex mock metagenome consisting of 227 bacterial strains with varying degrees of relatedness. We show that many of the current assemblers are not suited to handle such a complex metagenome. In addition, hybrid assemblies do not fulfil their potential. We conclude that ONT reads assembled with CANU and Illumina reads assembled with SPAdes offer the best value for reconstructing genomes and individual genes of complex metagenomes, respectively.

Filarial worms are important vector-borne pathogens of a large range of animal hosts, including humans, and are responsible for numerous debilitating neglected tropical diseases such as, lymphatic filariasis caused by Wuchereria bancrofti and Brugia spp., as well as loiasis caused by Loa loa. Moreover, some emerging or difficult-to-eliminate filarioid pathogens are zoonotic using animals like canines as reservoir hosts, for example Dirofilaria sp. 'hongkongensis'. Diagnosis of filariasis through commonly available methods, like microscopy, can be challenging as microfilaremia may wane below the limit of detection. In contrast, conventional PCR methods are more sensitive and specific but may show limited ability to detect coinfections as well as emerging and/or novel pathogens. Use of deep-sequencing technologies obviate these challenges, providing sensitive detection of entire parasite communities, whilst also being better suited for the characterisation of rare or novel pathogens. Therefore, we developed a novel long-read metabarcoding assay for deep-sequencing the filarial nematode cytochrome c oxidase subunit I gene on Oxford Nanopore Technologies' (ONT) MinION™ sequencer. We assessed the overall performance of our assay using kappa statistics to compare it to commonly used diagnostic methods for filarial worm detection, such as conventional PCR (cPCR) with Sanger sequencing and the microscopy-based modified Knott's test (MKT).

We confirmed our metabarcoding assay can characterise filarial parasites from a diverse range of genera, including, Breinlia, Brugia, Cercopithifilaria, Dipetalonema, Dirofilaria, Onchocerca, Setaria, Stephanofilaria and Wuchereria. We demonstrated proof-of-concept for this assay by using blood samples from Sri Lankan dogs, whereby we identified infections with the filarioids Acanthocheilonema reconditum, Brugia sp. Sri Lanka genotype and zoonotic Dirofilaria sp. 'hongkongensis'. When compared to traditionally used diagnostics, such as the MKT and cPCR with Sanger sequencing, we identified an additional filarioid species and over 15% more mono- and coinfections.

Our developed metabarcoding assay may show broad applicability for the metabarcoding and diagnosis of the full spectrum of filarioids from a wide range of animal hosts, including mammals and vectors, whilst the utilisation of ONT' small and portable MinION™ means that such methods could be deployed for field use.

Metabarcoding approaches for the identification of plant disease pathogens and characterization of plant microbial populations constitute a rapidly evolving research field. Fungal plant diseases are of major phytopathological concern; thus, the development of metabarcoding approaches for the detection of phytopathogenic fungi is becoming increasingly imperative in the context of plant disease prognosis. We developed a multiplex metabarcoding method for the identification of fungal phytopathogens and endophytes in olive young shoots, using the MinION sequencing platform (Oxford Nanopore Technologies). Selected fungal-specific primers were used to amplify three different genomic DNA loci (ITS, beta-tubulin, and 28S LSU) originating from olive twigs. A multiplex metabarcoding approach was initially evaluated using healthy olive twigs, and further assessed with naturally infected olive twig samples. Bioinformatic analysis of basecalled reads was carried out using MinKNOW, BLAST+ and R programming, and results were also evaluated using the BugSeq cloud platform. Data analysis highlighted the approaches based on ITS and their combination with beta-tubulin as the most informative ones according to diversity estimations. Subsequent implementation of the method on symptomatic samples identified major olive pathogens and endophytes including genera such as Cladosporium, Didymosphaeria, Paraconiothyrium, Penicillium, Phoma, Verticillium, and others.

Urinary tract infections are the most common bacterial infections worldwide. Infections can range from mild, recurrent (rUTI) to complicated (cUTIs), and are predominantly caused by uropathogenic Escherichia coli (UPEC). Antibiotic therapy is important to tackle infection; however, with the continued emergence of antibiotic resistance there is an urgent need to monitor the use of effective antibiotics through better stewardship measures. Currently, clinical diagnosis of UTIs relies on empiric methods supported by laboratory testing including cellular analysis (of both human and bacterial cells), dipstick analysis and phenotypic culture. Therefore, development of novel, sensitive and specific diagnostics is an important means to rationalise antibiotic therapy in patients. This review discusses the current diagnostic landscape and highlights promising novel diagnostic technologies in development that could aid in treatment and management of antibiotic-resistant UTIs.

The rapid assessment of microbiomes from ultra-low biomass environments such as cleanrooms or hospital operating rooms has a number of applications for human health and spacecraft manufacturing. Current techniques often employ lengthy protocols using short-read DNA sequencing technology to analyze amplified DNA and have the disadvantage of a longer analysis time and lack of portability. Here, we demonstrate a rapid (~24 hours) on-site nanopore-based sequencing approach to characterize the microbiome of a NASA Class 100K cleanroom where spacecraft components are assembled. This approach employs a modified protocol of Oxford Nanopore's Rapid PCR Barcoding Kit in combination with the recently developed Squeegee-Aspirator for Large Sampling Area (SALSA) surface sampling device. Results for these ultra-low biomass samples revealed DNA amplification ~1 to 2 orders of magnitude above process control samples and were dominated primarily by Paracoccus and Acinetobacter species. Negative control samples were collected to provide critical data on background contamination, including Cutibacerium acnes, which most likely originated from the sampling reagents-associated microbiome (kitome). Overall, these results provide data on a novel approach for rapid low-biomass DNA profiling using the SALSA sampler combined with modified nanopore sequencing. These data highlight the critical need for employing multiple negative controls, along with using DNA-free reagents and techniques, to enable a proper assessment of ultra-low biomass samples.

The aim of this study was to investigate the microbial diversity encompassing bacteria, fungi, and viruses within the composite microbial community associated with Aedes aegypti mosquitoes in Manado, Indonesia, using a whole-genome shotgun metagenomics approach. Female mosquitoes were collected and grouped into pools of 50 individuals, from which genomic DNA (gDNA) and RNA were extracted separately. Whole-genome shotgun metagenomics were performed on gDNA samples. The bioinformatics analysis encompassed quality assessment, taxonomic classification, and visualization. The evaluation of the microbial community entailed an assessment of taxa abundance and diversity using Kraken version 2.1.2. The study delineated the prevalence of dominant bacterial phyla, including Proteobacteria, with varying abundance of Firmicutes, Bacteroidota, and Actinobacteria, and notable occurrence of Tenericutes. Furthermore, the presence of the fungal phylum Ascomycota was also detected. Among the identified barcodes, Barcode04 emerged as the most abundant and diverse, while Barcode06 exhibited greater evenness. Barcode03, 05, and 07 displayed moderate richness and diversity. Through an analysis of the relative abundance, a spectrum of viruses within Ae. aegypti populations was unveiled, with Negarnaviricota constituting the most prevalent phylum, followed by Nucleocytoviricota, Uroviricota, Artverviricota, Kitrinoviricota, Peploviricota, Phixviricota, and Cossaviricota. The presence of Negarnaviricota viruses raises pertinent public health concerns. The presence of other viral phyla underscores the intricate nature of virus-mosquito interactions. The analysis of viral diversity provides valuable insights into the range of viruses carried by Ae. aegypti. The community exhibits low biodiversity, with a few dominant species significantly influencing its composition. This has implications for healthcare and ecological management, potentially simplifying control measures but also posing risks if the dominant species are harmful. This study enriches our comprehension of the microbiome and virome associated with Ae. aegypti mosquitoes, emphasizing the importance of further research to fully comprehend their ecological significance and impact on public health. The findings shed light on the microbial ecology of Ae. aegypti, offering potential insights into mosquito biology, disease transmission, and strategies for vector control. Future studies should endeavor to establish specific associations with Ae. aegypti, elucidate the functional roles of the identified microbial and viral species, and investigate their ecological implications.

Illumina MiSeq is the current standard for characterizing microbial communities in soil. The newer alternative, Oxford Nanopore Technologies MinION sequencer, is quickly gaining popularity because of the low initial cost and longer sequence reads. However, the accuracy of MinION, per base, is much lower than MiSeq (95% versus 99.9%). The effects of this difference in base-calling accuracy on taxonomic and diversity estimates remains unclear. We compared the effects of platform, primers, and bioinformatics on mock community and agricultural soil samples using short MiSeq, and short and full-length MinION 16S rRNA amplicon sequencing. For all three methods, we found that taxonomic assignments of the mock community at both the genus and species level matched expectations with minimal deviation (genus: 80.9-90.5%; species: 70.9-85.2% Bray-Curtis similarity); however, the short MiSeq with error correction (DADA2) resulted in the correct estimate of mock community species richness and much lower alpha diversity for soils. Several filtering strategies were tested to improve these estimates with varying results. The sequencing platform also had a significant influence on the relative abundances of taxa with MiSeq resulting in significantly higher abundances Actinobacteria, Chloroflexi, and Gemmatimonadetes and lower abundances of Acidobacteria, Bacteroides, Firmicutes, Proteobacteria, and Verrucomicrobia compared to the MinION platform. When comparing agricultural soils from two different sites (Fort Collins, CO and Pendleton, OR), methods varied in the taxa identified as significantly different between sites. At all taxonomic levels, the full-length MinION method had the highest similarity to the short MiSeq method with DADA2 correction with 73.2%, 69.3%, 74.1%, 79.3%, 79.4%, and 82.28% of the taxa at the phyla, class, order, family, genus, and species levels, respectively, showing similar patterns in differences between the sites. In summary, although both platforms appear suitable for 16S rRNA microbial community composition, biases for different taxa may make the comparison between studies problematic; and even with a single study (i.e., comparing sites or treatments), the sequencing platform can influence the differentially abundant taxa identified.

Microbiome analysis through 16S rRNA gene sequencing is a crucial tool for understanding the microbial ecology of any habitat or ecosystem. However, workflows require large equipment, stable internet, and extensive computing power such that most of the work is performed far away from sample collection in both space and time. Performing amplicon sequencing and analysis at sample collection would have positive implications in many instances including remote fieldwork and point-of-care medical diagnoses. Here we present SituSeq, an offline and portable workflow for the sequencing and analysis of 16S rRNA gene amplicons using Nanopore sequencing and a standard laptop computer. SituSeq was validated by comparing Nanopore 16S rRNA gene amplicons, Illumina 16S rRNA gene amplicons, and Illumina metagenomes, sequenced using the same environmental DNA. Comparisons revealed consistent community composition, ecological trends, and sequence identity across platforms. Correlation between the abundance of taxa in each taxonomic level in Illumina and Nanopore data sets was high (Pearson's r > 0.9), and over 70% of Illumina 16S rRNA gene sequences matched a Nanopore sequence with greater than 97% sequence identity. On board a research vessel on the open ocean, SituSeq was used to analyze amplicon sequences from deep sea sediments less than 2 h after sequencing, and 8 h after sample collection. The rapidly available results informed decisions about subsequent sampling in near real-time while the offshore expedition was still underway. SituSeq is a portable and user-friendly workflow that helps to bring the power of microbial genomics and diagnostics to many more researchers and situations.

Nanopore sequencing is a promising technology used for 16S rRNA gene amplicon sequencing as it can provide full-length 16S reads and has a low up-front cost that allows research groups to set up their own sequencing workflows. To assess whether Nanopore with the improved error rate of the Kit 12 chemistry should be adopted as the preferred sequencing technology instead of Illumina for 16S amplicon sequencing of the gut microbiota, we used a mock community and human faecal samples to compare diversity, richness, and species-level community structure, as well as the replicability of the results. Nanopore had less noise, better accuracy with the mock community, a higher proportion of reads from the faecal samples classified to species, and better replicability. The difference between the Nanopore and Illumina results of the faecal bacterial community structure was significant but small compared to the variation between samples. The results show that Nanopore is a better choice for 16S rRNA gene amplicon sequencing when the focus is on species-level taxonomic resolution, the investigation of rare taxa, or an accurate estimation of richness. Illumina 16S sequencing should be reserved for communities with many unknown species, and for studies that require the resolution of amplicon sequence variants.

Incorporation of plant biomass into soil as green manures can reduce soilborne diseases and improve crop and soil health in agricultural ecosystems. Soil microbial communities can mediate beneficial effects of these amendments, but their response to different types of green manures is poorly understood. This study tested the effect of green manures from broccoli, marigold, and sudangrass on taxonomic and functional characteristics of soil bacterial communities. Green manures were amended to field soil and maintained in microcosms artificially infested with the soilborne plant pathogen Verticillium dahliae. Lettuce seedlings were transplanted into green manure amended and fallow soil and maintained under growth chamber conditions for 12 weeks. Bacterial communities in bulk and rhizosphere soils were characterized using nanopore sequencing of 16S rRNA and shotgun metagenome libraries. Under microcosm conditions, all green manures reduced the abundance of the soilborne plant pathogen V. dahliae and altered the taxonomic composition of bacterial communities. Twelve weeks following amendment, green manures had differential effects on lettuce yield as well as the taxonomic diversity and composition of soil bacterial communities. In addition, multiple green manures increased the abundance of bacterial functional traits in rhizosphere soil related to iron and polysaccharide acquisition and decreased the abundance of functional traits related to bacterial protein secretion systems. This study demonstrates green manures alter the taxonomic composition and functional traits in soil bacterial communities suggesting these changes may impact beneficial effects of green manures on plant and soil health.

The utilization and improper use of crude oil can have irreparable damage on the environment and human populations. This study sought to isolate hydrocarbon utilizing bacteria from 1% v/v pristine seawater and 1% v/v crude oil using enrichment culture techniques. Whole genome sequencing of DNA using the Oxford Nanopore sequencing technique with Fastq WIMP as the workflow at 3% abundance was undertaken. The results showed that the most abundant isolates identified using this technique at specific sampling sites were, Acinetobacter junii (51.9%), Alcanivarax pacificus (15.8%), Acinetobacter haemolyticus (21.6%), Pseudomonas aeruginosa (23.4%), Alcanivorax xenomutans (24.7%), Alcanivorax xenomutans (23.0%) Acinetobacter baumannii (40.0%) and Acinetobacter junii (14.2%). Cumulatively, the most abundant isolates in the 8 sampling sites were Acinetobacter junii (17.91%), Alcanivorax xenomutans (11.68%), Pseudomonas aeruginosa (7.68%), Escherichia coli (7.67%), Acinetobacter haemolyticus (3.40%), and Alkanivorax pacificus (3.10%). Spearman's rank correlation analysis to examine the strength of relationship between the physicochemical parameters and type of bacteria isolated, revealed that salinity (0.8046) and pH (0.7252) were the highest. Isolated bacteria from pristine seawater, especially Escherichia coli have shown their capacity for bioremediating oil spill pollution in oceanic environments in Ghana.

Unambiguous evidence indicates that microbes are closely linked to various human diseases, including cancer. Most prior work investigating the microbiome of breast tissue describes an association between compositional differences of microbial species in benign and malignant tissues, but few studies have examined the relative abundance of microbial communities within human breast tissue at the species level. In this work, a total of 44 breast tissue samples including benign and malignant tissues with adjacent normal breast tissue pairs were collected, and Oxford Nanopore long-read sequencing was employed to assess breast tissue microbial signatures. Nearly 900 bacterial species were detected from the four dominant phyla: Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes. The bacteria with the highest abundance in all breast tissues was Ralstonia pickettii, and its relative abundance increased with decreasing malignancy. We further examined the breast-tissue microbiome composition with different hormone-receptor statuses, and the relative abundance of the genus Pseudomonas increased most significantly in breast tissues. Our study provides a rationale for exploring microbiomes associated with breast carcinogenesis and cancer development. Further large-cohort investigation of the breast microbiome is necessary to characterize a microbial risk signature and develop potential microbial-based prevention therapies.

Microbes in the built environment have been implicated as a source of infectious diseases. Bacterial culture is the standard method for assessing the risk of exposure to pathogens in urban environments, but this method only accounts for <1% of the diversity of bacteria. Recently, full-length 16S rRNA gene analysis using nanopore sequencing has been applied for microbial evaluations, resulting in a rise in the development of long-read taxonomic tools for species-level classification. Regarding their comparative performance, there is, however, a lack of information.

Here, we aim to analyze the concordance of the microbial community in the urban environment inferred by multiple taxonomic classifiers, including ARGpore2, Emu, Kraken2/Bracken and NanoCLUST, using our 16S-nanopore dataset generated by MegaBLAST, as well as assess their abilities to identify culturable species based on the conventional culture results.

According to our results, NanoCLUST was preferred for 16S microbial profiling because it had a high concordance of dominant species and a similar microbial profile to MegaBLAST, whereas Kraken2/Bracken, which had similar clustering results as NanoCLUST, was also desirable. Second, for culturable species identification, Emu with the highest accuracy (81.2%) and F1 score (29%) for the detection of culturable species was suggested.

In addition to generating datasets in complex communities for future benchmarking studies, our comprehensive evaluation of the taxonomic classifiers offers recommendations for ongoing microbial community research, particularly for complex communities using nanopore 16S rRNA sequencing.

Dogs across the globe are afflicted by diverse blood- and vector-borne bacteria (VBB), many of which cause severe disease and can be fatal. Diagnosis of VBB infections can be challenging due to the low concentration of bacteria in the blood, the frequent occurrence of coinfections, and the wide range of known, emerging, and potentially novel VBB species encounterable. Therefore, there is a need for diagnostics that address these challenges by being both sensitive and capable of detecting all VBB simultaneously. We detail the first employment of a nanopore-based sequencing methodology conducted on the Oxford Nanopore Technologies (ONT) MinION device to accurately elucidate the "hemobacteriome" from canine blood through sequencing of the full-length 16S rRNA gene. We detected a diverse range of important canine VBB, including Ehrlichia canis, Anaplasma platys, Mycoplasma haemocanis, Bartonella clarridgeiae, "Candidatus Mycoplasma haematoparvum", a novel species of hemotropic mycoplasma, and Wolbachia endosymbionts of filarial worms, indicative of filariasis. Our nanopore-based protocol was equivalent in sensitivity to both quantitative PCR (qPCR) and Illumina sequencing when benchmarked against these methods, achieving high agreement as defined by the kappa statistics (k > 0.81) for three key VBB. Utilizing the ability of the ONT' MinION device to sequence long read lengths provides an excellent alternative diagnostic method by which the hemobacteriome can be accurately characterized to the species level in a way previously unachievable using short reads. We envision our method to be translatable to multiple contexts, such as the detection of VBB in other vertebrate hosts, including humans, while the small size of the MinION device is highly amenable to field use. IMPORTANCE Blood- and vector-borne bacteria (VBB) can cause severe pathology and even be lethal for dogs in many regions across the globe. Accurate characterization of all the bacterial pathogens infecting a canine host is critical, as coinfections are common and emerging and novel pathogens that may go undetected by traditional diagnostics frequently arise. Deep sequencing using devices from Oxford Nanopore Technologies (ONT) provides a solution, as the long read lengths achievable provide species-level taxonomic identification of pathogens that previous short-read technologies could not accomplish. We developed a protocol using ONT' MinION sequencer to accurately detect and classify a wide spectrum of VBB from canine blood at a sensitivity comparable to that of regularly used diagnostics, such as qPCR. This protocol demonstrates great potential for use in biosurveillance and biosecurity operations for the detection of VBB in a range of vertebrate hosts, while the MinION sequencer's portability allows this method to be used easily in the field.

Wastewater surveillance (WS), when coupled with advanced molecular techniques, offers near real-time monitoring of community-wide transmission of SARS-CoV-2 and allows assessing and mitigating COVID-19 outbreaks, by evaluating the total microbial assemblage in a community. Composite wastewater samples (24 h) were collected weekly from a manhole between December 2020 and November 2021 in Maryland, USA. RT-qPCR results showed concentrations of SARS-CoV-2 RNA recovered from wastewater samples reflected incidence of COVID-19 cases. When a drastic increase in COVID-19 was detected in February 2021, samples were selected for microbiome analysis (DNA metagenomics, RNA metatranscriptomics, and targeted SARS-CoV-2 sequencing). Targeted SARS-CoV-2 sequencing allowed for detection of important genetic mutations, such as spike: K417N, D614G, P681H, T716I, S982A, and D1118H, commonly associated with increased cell entry and reinfection. Microbiome analysis (DNA and RNA) provided important insight with respect to human health-related factors, including detection of pathogens and their virulence/antibiotic resistance genes. Specific microbial species comprising the wastewater microbiome correlated with incidence of SARS-CoV-2 RNA, suggesting potential association with SARS-CoV-2 infection. Climatic conditions, namely, temperature, were related to incidence of COVID-19 and detection of SARS-CoV-2 in wastewater, having been monitored as part of an environmental risk score assessment carried out in this study. In summary, the wastewater microbiome provides useful public health information, and hence, a valuable tool to proactively detect and characterize pathogenic agents circulating in a community. In effect, metagenomics of wastewater can serve as an early warning system for communicable diseases, by providing a larger source of information for health departments and public officials. IMPORTANCE Traditionally, testing for COVID-19 is done by detecting SARS-CoV-2 in samples collected from nasal swabs and/or saliva. However, SARS-CoV-2 can also be detected in feces of infected individuals. Therefore, wastewater samples can be used to test all individuals of a community contributing to the sewage collection system, i.e., the infrastructure, such as gravity pipes, manholes, tanks, lift stations, control structures, and force mains, that collects used water from residential and commercial sources and conveys the flow to a wastewater treatment plant. Here, we profile community wastewater collected from a manhole, detect presence of SARS-CoV-2, identify genetic mutations of SARS-CoV-2, and perform COVID-19 risk score assessment of the study area. Using metagenomics analysis, we also detect other microorganisms (bacteria, fungi, protists, and viruses) present in the samples. Results show that by analyzing all microorganisms present in wastewater, pathogens circulating in a community can provide an early warning for contagious diseases.

Genetic data from nonmodel species can inform ecology and physiology, giving insight into a species' distribution and abundance as well as their responses to changing environments, all of which are important for species conservation and management. Moreover, reduced sequencing costs and improved long-read sequencing technology allows researchers to readily generate genomic resources for nonmodel species. Here, we apply Oxford Nanopore long-read sequencing and low-coverage (∼1x) whole genome short-read sequencing technology (Illumina) to assemble a genome and examine population genetics of an abundant tropical and subtropical fish, the hardhead silverside (Atherinomorus stipes). These fish are found in shallow coastal waters and are frequently included in ecological models because they serve as abundant prey for commercially and ecologically important species. Despite their importance in sub-tropical and tropical ecosystems, little is known about their population connectivity and genetic diversity. Our A. stipes genome assembly is about 1.2 Gb with comparable repetitive element content (∼47%), number of protein duplication events, and DNA methylation patterns to other teleost fish species. Among five sampled populations spanning 43 km of South Florida and the Florida Keys, we find little population structure suggesting high population connectivity.

Soils are fundamental resources for agricultural production and play an essential role in food security. They represent the keystone of the food value chain because they harbor a large fraction of biodiversity-the backbone of the regulation of ecosystem services and "soil health" maintenance. In the face of the numerous causes of soil degradation such as unsustainable soil management practices, pollution, waste disposal, or the increasing number of extreme weather events, it has become clear that (i) preserving the soil biodiversity is key to food security, and (ii) biodiversity-based solutions for environmental monitoring have to be developed. Within the soil biodiversity reservoir, microbial diversity including Archaea, Bacteria, Fungi and protists is essential for ecosystem functioning and resilience. Microbial communities are also sensitive to various environmental drivers and to management practices; as a result, they are ideal candidates for monitoring soil quality assessment. The emergence of meta-omics approaches based on recent advances in high-throughput sequencing and bioinformatics has remarkably improved our ability to characterize microbial diversity and its potential functions. This revolution has substantially filled the knowledge gap about soil microbial diversity regulation and ecology, but also provided new and robust indicators of agricultural soil quality. We reviewed how meta-omics approaches replaced traditional methods and allowed developing modern microbial indicators of the soil biological quality. Each meta-omics approach is described in its general principles, methodologies, specificities, strengths and drawbacks, and illustrated with concrete applications for soil monitoring. The development of metabarcoding approaches in the last 20 years has led to a collection of microbial indicators that are now operational and available for the farming sector. Our review shows that despite the recent huge advances, some meta-omics approaches (e.g., metatranscriptomics or meta-proteomics) still need developments to be operational for environmental bio-monitoring. As regards prospects, we outline the importance of building up repositories of soil quality indicators. These are essential for objective and robust diagnosis, to help actors and stakeholders improve soil management, with a view to or to contribute to combining the food and environmental quality of next-generation farming systems in the context of the agroecological transition.

Fecal microbiota transplantation (FMT) is currently used for treating Clostridium difficile infection and explored for other clinical applications in experimental trials. However, the effectiveness of this therapy could vary, and partly depend on the donor's bacterial species engraftment, whose evaluation is challenging because there are no cost-effective strategies for accurately tracking the microbe transference. In this regard, the precise identification of bacterial species inhabiting the human gut is essential to define their role in human health unambiguously. We used Nanopore-based device to sequence bacterial rrn operons (16S-ITS-23S) and to reveal species-level abundance changes in the human gut microbiota of a FMT trial. By assessing the donor and recipient microbiota before and after FMT, we further evaluated whether this molecular approach reveals strain-level genetic variation to demonstrate microbe transfer and engraftment. Strict control over sequencing data quality and major microbiota covariates was critical for accurately estimating the changes in gut microbial species abundance in the recipients after FMT. We detected strain-level variation via single-nucleotide variants (SNVs) at rrn regions in a species-specific manner. We showed that it was possible to explore successfully the donor-bacterial strain (e.g., Parabacteroides merdae) engraftment in recipients of the FMT by assessing the nucleotide frequencies at rrn-associated SNVs. Our findings indicate that the engraftment of donors' microbiota is to some extent correlated with the improvement of metabolic health in recipients and that parameters such as the baseline gut microbiota configuration, sex, and age of donors should be considered to ensure the success of FMT in humans. The study was prospectively registered at the Dutch Trial registry - NTR4488 (https://www.trialregister.nl/trial/4488).

Microplastic contamination is an increasing concern worldwide. Biofilms rapidly develop on surfaces in aquatic habitats, but the processes of biofilm formation and variation in bacterial community succession on different microplastics introduced into freshwater and estuarine environments are not well understood. In this study, the biofilm bacterial communities that developed on three different types of microplastics that are prevalent in the environment, high-density polyethylene (HDPE), polyethylene terephthalate (PET), and polystyrene (PS), was investigated. Virgin microplastics were incubated in microcosms over a period of 31 days with water collected along a freshwater-estuarine gradient of the Raritan River in New Jersey. Through long-read MinION sequencing of bacterial ribosomal operons, we were able to examine biofilm bacterial communities at a species- and strain-level resolution. Results indicated that both salinity level and microplastic type impacted biofilm formation and promoted colonization by distinct microbial communities. Limnobacter thiooxidans was found to be one of the most abundant microplastics colonizing-bacteria, and it is hypothesized that different types of microplastics could select for different strains. Our findings indicate that multiple groups of highly similar L. thiooxidans rRNA operons could be discerned within the community profiles. Phylogenetic reconstruction further established that various Linmobacter species uniquely colonized the different microplastics from the different sampling sites. Our findings indicate that microplastics support abundant and diverse bacterial communities and that the various types of microplastics can influence how different bacterial biofilms develop, which may have ecological impacts on aquatic ecosystems.