A comprehensive method for amplicon-based and metagenomic characterization of viruses, bacteria, and eukaryotes in freshwater samples

Application and Comparison of Machine Learning and Database-Based Methods in Taxonomic Classification of High-Throughput Sequencing Data

The advent of high-throughput sequencing technologies has not only revolutionized the field of bioinformatics but has also heightened the demand for efficient taxonomic classification. Despite technological advancements, efficiently processing and analyzing the deluge of sequencing data for precise taxonomic classification remains a formidable challenge. Existing classification approaches primarily fall into two categories, database-based methods and machine learning methods, each presenting its own set of challenges and advantages. On this basis, the aim of our study was to conduct a comparative analysis between these two methods while also investigating the merits of integrating multiple database-based methods. Through an in-depth comparative study, we evaluated the performance of both methodological categories in taxonomic classification by utilizing simulated data sets. Our analysis revealed that database-based methods excel in classification accuracy when backed by a rich and comprehensive reference database. Conversely, while machine learning methods show superior performance in scenarios where reference sequences are sparse or lacking, they generally show inferior performance compared with database methods under most conditions. Moreover, our study confirms that integrating multiple database-based methods does, in fact, enhance classification accuracy. These findings shed new light on the taxonomic classification of high-throughput sequencing data and bear substantial implications for the future development of computational biology. For those interested in further exploring our methods, the source code of this study is publicly available on https://github.com/LoadStar822/Genome-Classifier-Performance-Evaluator. Additionally, a dedicated webpage showcasing our collected database, data sets, and various classification software can be found at http://lab.malab.cn/~tqz/project/taxonomic/.

Impact of artisanal refining activities on bacterial diversity in a Niger Delta fallow land

Hydrocarbon pollution is a major ecological problem facing oil-producing countries, especially in the Niger Delta region of Nigeria. In this study, a site that had been previously polluted by artisanal refining activity was investigated using 16S rRNA Illumina high-throughput sequencing technology and bioinformatics tools. These were used to investigate the bacterial diversity in soil with varying degrees of contamination, determined with a gas chromatography-flame ionization detector (GC-FID). Soil samples were collected from a heavily polluted (HP), mildly polluted (MP), and unpolluted (control sample, CS) portion of the study site. DNA was extracted using the Zymo Research (ZR) Fungi/Bacteria DNA MiniPrep kit, followed by PCR amplification and agarose gel electrophoresis. The microbiome was characterized based on the V3 and V4 hypervariable regions of the 16S rRNA gene. QIIME (Quantitative Insights Into Microbial Ecology) 2 software was used to analyse the sequence data. The final data set covered 20,640 demultiplexed high-quality reads and a total of 160 filtered bacterial OTUs. Proteobacteria dominated samples HP and CS, while Actinobacteria dominated sample MP. Denitratisoma, Pseudorhodoplanes, and Spirilospora were the leading genera in samples HP, CS, and MP respectively. Diversity analysis indicated that CS [with 25.98 ppm of total petroleum hydrocarbon (TPH)] is more diverse than HP (with 490,630 ppm of TPH) and MP (with 5398 ppm of TPH). A functional prediction study revealed that six functional modules dominated the dataset, with metabolism covering up to 70%, and 11 metabolic pathways. This study demonstrates that a higher hydrocarbon concentration in soil adversely impacts microbial diversity, creating a narrow bacterial diversity dominated by hydrocarbon-degrading species, in addition to the obvious land and ecosystem degradation caused by artisanal refining activities. Overall, the artisanal refining business is significantly driving ecosystem services losses in the Niger Delta, which calls for urgent intervention, with focus on bioremediation.

Merging and concatenation of sequencing reads: a bioinformatics workflow for the comprehensive profiling of microbiome from amplicon data

A comprehensive profiling of microbial diversity is essential to understand the ecosystem functions. Universal primer sets such as the 515Y/926R could amplify a part of 16S and 18S rRNA and infer the diversity of prokaryotes and eukaryotes. However, the analyses of mixed sequencing data pose a bioinformatics challenge; the 16S and 18S rRNA sequences need to be separated first and analysed individually/independently due to variations in the amplicon length. This study describes an alternative strategy, a merging and concatenation workflow, to analyse the mixed amplicon data without separating the 16S and 18S rRNA sequences. The workflow was tested with 24 mock community (MC) samples, and the analyses resolved the composition of prokaryotes and eukaryotes adequately. In addition, there was a strong correlation (cor = 0.950; P-value = 4.754e-10) between the observed and expected abundances in the MC samples, which suggests that the computational approach could infer the microbial proportions accurately. Further, 18 samples collected from the Sundarbans mangrove region were analysed as a case study. The analyses identified Proteobacteria, Bacteroidota, Actinobacteriota, Cyanobacteria, and Crenarchaeota as dominant bacterial phyla and eukaryotic divisions such as Metazoa, Gyrista, Cryptophyta, Chlorophyta, and Dinoflagellata were found to be dominant in the samples. Thus, the results support the applicability of the method in environmental microbiome research. The merging and concatenation workflow presented here requires considerably less computational resources and uses widely/commonly used bioinformatics packages, saving researchers analyses time (for equivalent sample numbers, compared to the conventional approach) required to infer the diversity of major microbial domains from mixed amplicon data at comparable accuracy.

Metagenomics in the fight against zoonotic viral infections: A focus on SARS-CoV-2 analogues

Zoonotic viral infections continue to pose significant threats to global public health, as highlighted by the COVID-19 pandemic caused by the SARS-CoV-2 virus. The emergence of SARS-CoV-2 served as a stark reminder of the potential for zoonotic transmission of viruses from animals to humans. Understanding the origins and dynamics of zoonotic viruses is critical for early detection, prevention, and effective management of future outbreaks. Metagenomics has emerged as a powerful tool for investigating the virome of diverse ecosystems, shedding light on the diversity of viral populations, their hosts, and potential zoonotic spillover events. We provide an in-depth examination of metagenomic approaches, including, NGS metagenomics, shotgun metagenomics, viral metagenomics, and single-virus metagenomics, highlighting their strengths and limitations in identifying and characterizing zoonotic viral pathogens. This review underscores the pivotal role of metagenomics in enhancing our ability to detect, monitor, and mitigate zoonotic viral infections, using SARS-CoV-2 analogues as a case study. We emphasize the need for continued interdisciplinary collaboration among virologists, ecologists, and bioinformaticians to harness the full potential of metagenomic approaches in safeguarding public health against emerging zoonotic threats.

Diatoms Reduce Decomposition of and Fungal Abundance on Less Recalcitrant Leaf Litter via Negative Priming

Heterotrophic microbial decomposers colonize submerged leaf litter in close spatial proximity to periphytic algae that exude labile organic carbon during photosynthesis. These exudates are conjectured to affect microbial decomposers' abundance, resulting in a stimulated (positive priming) or reduced (negative priming) leaf litter decomposition. Yet, the occurrence, direction, and intensity of priming associated with leaf material of differing recalcitrance remains poorly tested. To assess priming, we submerged leaf litter of differing recalcitrance (Alnus glutinosa [alder; less recalcitrant] and Fagus sylvatica [beech; more recalcitrant]) in microcosms and quantified bacterial, fungal, and diatom abundance as well as leaf litter decomposition over 30 days in absence and presence of light. Diatoms did not affect beech decomposition but reduced alder decomposition by 20% and alder-associated fungal abundance by 40% in the treatments including all microbial groups and light, thus showing negative priming. These results suggest that alder-associated heterotrophs acquired energy from diatom exudates rather than from leaf litter. Moreover, it is suggested that these heterotrophs have channeled energy to alternative (reproductive) pathways that may modify energy and nutrient availability for the remaining food web and result in carbon pools protected from decomposition in light-exposed stream sections.

Functional gene transcription variation in bacterial metatranscriptomes in large freshwater Lake Ecosystems: Implications for ecosystem and human health

Little is known regarding the temporal and spatial functional variation of freshwater bacterial community (BC) under non-bloom conditions, especially in winter. To address this, we used metatranscriptomics to assess bacterial gene transcription variation among three sites across three seasons. Our metatranscriptome data for freshwater BCs at three public beaches (Ontario, Canada) sampled in the winter (no ice), summer and fall (2019) showed relatively little spatial, but a strong temporal variation. Our data showed high transcriptional activity in summer and fall but surprisingly, 89% of the KEGG pathway genes and 60% of the selected candidate genes (52 genes) associated with physiological and ecological activity were still active in freezing temperatures (winter). Our data also supported the possibility of an adaptively flexible gene expression response of the freshwater BC to low temperature conditions (winter). Only 32% of the bacterial genera detected in the samples were active, indicating that the majority of detected taxa were non-active (dormant). We also identified high seasonal variation in the abundance and activity of taxa associated with health risks (i.e., Cyanobacteria and waterborne bacterial pathogens). This study provides a baseline for further characterization of freshwater BCs, health-related microbial activity/dormancy and the main drivers of their functional variation (such as rapid human-induced environmental change and climate change).

Oral dysbiosis in the onset and carcinogenesis of oral epithelial dysplasia: A systematic review

OBJECTIVE

This systematic review aims to investigate possible connections between the oral microbiome and the onset and carcinogenesis of oral epithelial dysplasia (OED).

METHODS

A systematic search was performed on PubMed, Embase, Cochrane Database, and SCOPUS by two authors independently, addressing the focused question- "Has oral microbiome dysbiosis been involved in the onset and carcinogenesis of oral epithelial dysplasia?" We used the Newcastle-Ottawa scale to assess the quality of studies included in the review.

RESULTS

Out of 580 references screened, ten studies were found eligible for inclusion. All studies were case-control studies, and only qualitative analysis was conducted due to heterogeneous characteristics. The overall risk of bias in the eligible studies was considered as high. Microbiome diversity indices showed inconsistent evidence among studies. A significant increase of phylum Bacteroidetes in OED patients was reported in five studies. Five studies reported an increase of genus Fusobacterium in both the OED and oral squamous cell carcinoma (OSCC) patients and six different studies respectively reported a reduction of genus Streptococcus in both the OED and OSCC groups when compared to normal controls. Other predominant bacteria that were specific to different patient groups varied in each study.

CONCLUSIONS

The results of the included studies showed that the composition of the oral microbiome in patients with OED compared to healthy controls and OSCC patients was inconsistent. However, all ten studies showed non-negligible heterogeneity in the type and size of the sample, and the comparability between groups, which strongly limited the external validity of results. Further studies are strongly recommended.

Microbiota DNA isolation, 16S rRNA amplicon sequencing, and bioinformatic analysis for bacterial microbiome profiling of rodent fecal samples

Fecal samples are frequently used to characterize bacterial populations of the gastrointestinal tract. A protocol is provided to profile gut bacterial populations using rodent fecal samples. We describe the optimal procedures for collecting rodent fecal samples, isolating genomic DNA, 16S rRNA gene V4 region sequencing, and bioinformatic analyses. This protocol includes detailed instructions and example outputs to ensure accurate, reproducible results and data visualization. Comprehensive troubleshooting and limitation sections address technical and statistical issues that may arise when profiling microbiota. For complete details on the use and execution of this protocol, please refer to Gubert et al. (2022).

Fate of resistome components and characteristics of microbial communities in constructed wetlands and their receiving river

Currently, most researches focus on that constructed wetlands (CWs) achieve desirable removal of antibiotics, antibiotic resistance genes (ARGs) and human pathogens. However, few studies have assessed the fate of resistome components, especially the behavior and cooccurrence of ARGs, mobile genetic elements (MGEs) and virulence factors (VFs). Therefore, characteristics of microbial communities (MCs) in CWs and their receiving rivers also deserve attention. These factors are critical to water ecological security. This study used two CWs to explore the fate of resistome components and characteristics of MCs in the CWs and their receiving river. Eleven samples were collected from the two CWs and their receiving river. High-throughput profiles of ARGs and microbial taxa in the samples were characterized. 31 ARG types consisting of 400 subtypes with total relative abundance 42.63-84.94× /Gb of sequence were detected in CWs, and 62.07-88.08× /Gb of sequence in river, evidencing that ARG pollution covered CWs and the river, and implying huge potential risks from ARGs. MGEs and VFs were detected, and tnpA, IS91 and intI1 were the three dominant MGEs, while Flagella. Type IV pili and peritrichous flagella were main VFs. Both CWs can remove ARGs, MGEs and VFs efficiently. However, some ARGs were difficult to remove, such as sul1 and sul2, and certain ARGs remained in the effluent of the CWs. The co-occurrence of ARGs, MGEs, and VFs implies the risk of antibiotic resistance and dissemination of ARGs. Eighty-five types of human pathogen were detected in the river samples, particularly Pseudomonas aeruginosa, Bordetella bronchiseptica, Aeromonas hydrophila and Helicobacter pylori. Correlation analysis indicated that MCs had significant effects on the profiles of ARGs in the water environment. This study reveals potential risks of the reuse of reclaimed water, and illustrates the removal ability of ARGs and related elements by CWs. This study will be helpful for monitoring and managing resistomes in water environments.

Diagnostic Methods of Common Intestinal Protozoa: Current and Future Immunological and Molecular Methods

Intestinal protozoan infection is a persisting public health problem affecting the populations of developing countries in the tropical and subtropical regions. The diagnosis of intestinal protozoa remains a challenge especially in developing countries due to a shortage of laboratory facilities, limited health funding, and the remoteness of communities. Despite still being widely used, conventional diagnoses using microscopy and staining methods pose important limitations, particularly due to their low sensitivities and specificities. The selection of diagnostic methods needs to be carefully considered based on the objective of examination, availability of resources, and the expected parasite to be found. In this review, we describe various immunodiagnosis and molecular diagnostic methods for intestinal protozoa infection, including their advantages, disadvantages, and suitability for different settings, with a focus on Entamoeba histolytica, Giardia duodenalis, and Cryptosporidium spp.

Metagenomics versus total RNA sequencing: most accurate data-processing tools, microbial identification accuracy and perspectives for ecological assessments

Metagenomics and total RNA sequencing (total RNA-Seq) have the potential to improve the taxonomic identification of diverse microbial communities, which could allow for the incorporation of microbes into routine ecological assessments. However, these target-PCR-free techniques require more testing and optimization. In this study, we processed metagenomics and total RNA-Seq data from a commercially available microbial mock community using 672 data-processing workflows, identified the most accurate data-processing tools, and compared their microbial identification accuracy at equal and increasing sequencing depths. The accuracy of data-processing tools substantially varied among replicates. Total RNA-Seq was more accurate than metagenomics at equal sequencing depths and even at sequencing depths almost one order of magnitude lower than those of metagenomics. We show that while data-processing tools require further exploration, total RNA-Seq might be a favorable alternative to metagenomics for target-PCR-free taxonomic identifications of microbial communities and might enable a substantial reduction in sequencing costs while maintaining accuracy. This could be particularly an advantage for routine ecological assessments, which require cost-effective yet accurate methods, and might allow for the incorporation of microbes into ecological assessments.

Detection of SARS-CoV-2 RNA throughout wastewater treatment plants and a modeling approach to understand COVID-19 infection dynamics in Winnipeg, Canada

Although numerous studies have detected SARS-CoV-2 RNA in wastewater and attempted to find correlations between the concentration of SARS-CoV-2 RNA and the number of cases, no consensus has been reached on sample collection and processing, and data analysis. Moreover, the fate of SARS-CoV-2 in wastewater treatment plants is another issue, specifically regarding the discharge of the virus into environmental settings and the water cycle. The current study monitored SARS-CoV-2 RNA in influent and effluent wastewater samples with three different concentration methods and sludge samples over six months (July to December 2020) to compare different virus concentration methods, assess the fate of SARS-CoV-2 RNA in wastewater treatment plants, and describe the potential relationship between SARS-CoV-2 RNA concentrations in influent and infection dynamics. Skimmed milk flocculation (SMF) resulted in 15.27 ± 3.32% recovery of an internal positive control, Armored RNA, and a high positivity rate of SARS-CoV-2 RNA in stored wastewater samples compared to ultrafiltration methods employing a prefiltration step to eliminate solids in fresh wastewater samples. Our results suggested that SARS-CoV-2 RNA may predominate in solids, and therefore, concentration methods focusing on both supernatant and solid fractions may result in better recovery. SARS-CoV-2 RNA was detected in influent and primary sludge samples but not in secondary and final effluent samples, indicating a significant reduction during primary and secondary treatments. SARS-CoV-2 RNA was first detected in influent on September 30th, 2020. A decay-rate formula was applied to estimate initial concentrations of late-processed samples with SMF. A model based on shedding rate and new cases was applied to estimate SARS-CoV-2 RNA concentrations and the number of active shedders. Inferred sensitivity of observed and modeled concentrations to the fluctuations in new cases and test-positivity rates indicated a potential contribution of newly infected individuals to SARS-CoV-2 RNA loads in wastewater.

Quantification of human enteric viruses as alternative indicators of fecal pollution to evaluate wastewater treatment processes

We investigated the potential use and quantification of human enteric viruses in municipal wastewater samples of Winnipeg (Manitoba, Canada) as alternative indicators of contamination and evaluated the processing stages of the wastewater treatment plant. During the fall 2019 and winter 2020 seasons, samples of raw sewage, activated sludge, effluents, and biosolids (sludge cake) were collected from the North End Sewage Treatment Plant (NESTP), which is the largest wastewater treatment plant in the City of Winnipeg. DNA (Adenovirus and crAssphage) and RNA enteric viruses (Pepper mild mottle virus, Norovirus genogroups GI and GII, Rotavirus Astrovirus, and Sapovirus) as well as the uidA gene found in Escherichia coli were targeted in the samples collected from the NESTP. Total nucleic acids from each wastewater treatment sample were extracted using a commercial spin-column kit. Enteric viruses were quantified in the extracted samples via quantitative PCR using TaqMan assays. Overall, the average gene copies assessed in the raw sewage were not significantly different (p-values ranged between 0.1023 and 0.9921) than the average gene copies assessed in the effluents for DNA and RNA viruses and uidA in terms of both volume and biomass. A significant reduction (p-value ≤ 0.0438) of Adenovirus and Noroviruses genogroups GI and GII was observed in activated sludge samples compared with those for raw sewage per volume. Higher GCNs of enteric viruses were observed in dewatered sludge samples compared to liquid samples in terms of volume (g of sample) and biomass (ng of nucleic acids). Enteric viruses found in gene copy numbers were at least one order of magnitude higher than the E. coli marker uidA, indicating that enteric viruses may survive the wastewater treatment process and viral-like particles are being released into the aquatic environment. Viruses such as Noroviruses genogroups GI and GII, and Rotavirus were detected during colder months. Our results suggest that Adenovirus, crAssphage, and Pepper mild mottle virus can be used confidently as complementary viral indicators of human fecal pollution.

Production of microalgae with high lipid content and their potential as sources of nutraceuticals

In the current global scenario, the world is under a serious dilemma due to the increasing human population, industrialization, and urbanization. The ever-increasing need for fuels and increasing nutritional problems have made a serious concern on the demand for nutrients and renewable and eco-friendly fuel sources. Currently, the use of fossil fuels is creating ecological and economic problems. Microalgae have been considered as a promising candidate for high-value metabolites and alternative renewable energy sources. Microalgae offer several advantages such as rapid growth rate, efficient land utilization, carbon dioxide sequestration, ability to cultivate in wastewater, and most importantly, they do not participate in the food crop versus energy crop dilemma or debate. An efficient microalgal biorefinery system for the production of lipids and subsequent byproduct for nutraceutical applications could well satisfy the need. But, the current microalgal cultivation systems for the production of lipids and nutraceuticals do not offer techno-economic feasibility together with energy and environmental sustainability. This review article has its main focus on the production of lipids and nutraceuticals from microalgae, covering the current strategies used for lipid production and the major high-value metabolites from microalgae and their nutraceutical importance. This review also provides insights on the future strategies for enhanced microalgal lipid production and subsequent utilization of microalgal biomass.

GRAPHICAL ABSTRACT

Metagenomic community composition and resistome analysis in a full-scale cold climate wastewater treatment plant

BACKGROUND

Wastewater treatment plants are an essential part of maintaining the health and safety of the general public. However, they are also an anthropogenic source of antibiotic resistance genes. In this study, we characterized the resistome, the distribution of classes 1-3 integron-integrase genes (intI1, intI2, and intI3) as mobile genetic element biomarkers, and the bacterial and phage community compositions in the North End Sewage Treatment Plant in Winnipeg, Manitoba. Samples were collected from raw sewage, returned activated sludge, final effluent, and dewatered sludge. A total of 28 bacterial and viral metagenomes were sequenced over two seasons, fall and winter. Integron-integrase genes, the 16S rRNA gene, and the coliform beta-glucuronidase gene were also quantified during this time period.

RESULTS

Bacterial classes observed above 1% relative abundance in all treatments were Actinobacteria (39.24% ± 0.25%), Beta-proteobacteria (23.99% ± 0.16%), Gamma-proteobacteria (11.06% ± 0.09%), and Alpha-proteobacteria (9.18 ± 0.04%). Families within the Caudovirales order: Siphoviridae (48.69% ± 0.10%), Podoviridae (23.99% ± 0.07%), and Myoviridae (19.94% ± 0.09%) were the dominant phage observed throughout the NESTP. The most abundant bacterial genera (in terms of average percent relative abundance) in influent, returned activated sludge, final effluent, and sludge, respectively, includes Mycobacterium (37.4%, 18.3%, 46.1%, and 7.7%), Acidovorax (8.9%, 10.8%, 5.4%, and 1.3%), and Polaromonas (2.5%, 3.3%, 1.4%, and 0.4%). The most abundant class of antibiotic resistance in bacterial samples was tetracycline resistance (17.86% ± 0.03%) followed by peptide antibiotics (14.24% ± 0.03%), and macrolides (10.63% ± 0.02%). Similarly, the phage samples contained a higher prevalence of macrolide (30.12% ± 0.30%), peptide antibiotic (10.78% ± 0.13%), and tetracycline (8.69% ± 0.11%) resistance. In addition, intI1 was the most abundant integron-integrase gene throughout treatment (1.14 × 104 gene copies/mL) followed by intI3 (4.97 × 103 gene copies/mL) while intI2 abundance remained low (6.4 × 101 gene copies/mL).

CONCLUSIONS

Wastewater treatment successfully reduced the abundance of bacteria, DNA phage and antibiotic resistance genes although many antibiotic resistance genes remained in effluent and biosolids. The presence of integron-integrase genes throughout treatment and in effluent suggests that antibiotic resistance genes could be actively disseminating resistance between both environmental and pathogenic bacteria.

Considerations for Constructing a Protein Sequence Database for Metaproteomics

Mass spectrometry-based metaproteomics has emerged as a prominent technique for interrogating the functions of specific organisms in microbial communities, in addition to total community function. Identifying proteins by mass spectrometry requires matching mass spectra of fragmented peptide ions to a database of protein sequences corresponding to the proteins in the sample. This sequence database determines which protein sequences can be identified from the measurement, and as such the taxonomic and functional information that can be inferred from a metaproteomics measurement. Thus, the construction of the protein sequence database directly impacts the outcome of any metaproteomics study. Several factors, such as source of sequence information and database curation, need to be considered during database construction to maximize accurate protein identifications traceable to the species of origin. In this review, we provide an overview of existing strategies for database construction and the relevant studies that have sought to test and validate these strategies. Based on this review of the literature and our experience we provide a decision tree and best practices for choosing and implementing database construction strategies.

Fungal-fungal and fungal-bacterial interactions in aquatic decomposer communities: bacteria promote fungal diversity

Fungi produce a variety of extracellular enzymes making recalcitrant substrates bioavailable. Thus, fungi are central for decomposition of dead organic matter such as leaf litter. Despite their ecological importance, our understanding of relationships between fungal species diversity and ecosystem functioning is limited, especially with regard to aquatic habitats. Moreover, fungal interactions with other groups of microorganisms such as bacteria are rarely investigated. This lack of information may be attributed to methodological limitations in tracking the biomass of individual fungal species in communities, impeding a detailed assessment of deviations from the overall performance expected from the sum of individual species' performances, so-called net diversity effects (NDEs). We used fungal species-specific biomolecular tools to target fungal-fungal and fungal-bacterial interactions on submerged leaves using four cosmopolitan aquatic fungal species and a stream microbial community dominated by bacteria. In microcosms, we experimentally manipulated fungal diversity and bacterial absence/presence and assessed functional performances and fungal community composition after 14 days of incubation. Fungal community data was used to evaluate NDEs on leaf colonization. The individual fungal species were functionally distinct and fungal cultures were on average more efficient than the bacterial culture. In absence of bacteria, NDEs correlated with growth rate (negatively) and genetic divergence (positively), but were predominantly negative, suggesting that higher fungal diversity led to a lower colonization success (niche overlap). In both absence and presence of bacteria, the overall functional performances of the communities were largely defined by their composition (i.e., no interactions at the functional level). In presence of bacteria, NDEs correlated with genetic divergence (positively) and were largely positive, suggesting higher fungal diversity stimulated colonization (niche complementarity). This stimulation may be driven by a bacteria-induced inhibition of fungal growth, alleviating competition among fungi. Resulting feedback loops eventually promote fungal coexistence and synergistic interactions. Nonetheless, overall functional performances are reduced compared to bacteria-free cultures. These findings highlight the necessity to conduct future studies, investigating biodiversity-ecosystem functioning relationships using artificial systems, without exclusion of key organisms naturally co-occurring in the compartment of interest. Otherwise, study outcomes might not reflect true ecological relationships and ultimately misguide conservation strategies.

A review on application of next-generation sequencing methods for profiling of protozoan parasites in water: Current methodologies, challenges, and perspectives

The advancement in metagenomic techniques has provided novel tools for profiling human parasites in environmental matrices, such as water and wastewater. However, application of metagenomic techniques for the profiling of protozoan parasites in environmental matrices is not commonly reported in the literature. The key factors leading to the less common use of metagenomics are the complexity and large eukaryotic genome, the prevalence of small parasite populations in environmental samples compared to bacteria, difficulties in extracting DNA from (oo)cysts, and limited reference databases for parasites. This calls for further research to develop optimized methods specifically looking at protozoan parasites in the environment. This study reviews the current workflow, methods and provide recommendations for the standardization of techniques. The article identifies and summarizes the key methods, advantages, and limitations associated with metagenomic analysis, like sample pre-processing, DNA extraction, sequencing approaches, and analysis methods. The study enhances the understanding and application of standardized protocols for profiling of protozoan parasite community from highly complexe samples and further creates a resourceful comparison among datasets without any biases.

Comparison of ultrafiltration and iron chloride flocculation in the preparation of aquatic viromes from contrasting sample types

Viral metagenomes (viromes) are a valuable untargeted tool for studying viral diversity and the central roles viruses play in host disease, ecology, and evolution. Establishing effective methods to concentrate and purify viral genomes prior to sequencing is essential for high quality viromes. Using virus spike-and-recovery experiments, we stepwise compared two common approaches for virus concentration, ultrafiltration and iron chloride flocculation, across diverse matrices: wastewater influent, wastewater secondary effluent, river water, and seawater. Viral DNA was purified by removing cellular DNA via chloroform cell lysis, filtration, and enzymatic degradation of extra-viral DNA. We found that viral genomes were concentrated 1-2 orders of magnitude more with ultrafiltration than iron chloride flocculation for all matrices and resulted in higher quality DNA suitable for amplification-free and long-read sequencing. Given its widespread use and utility as an inexpensive field method for virome sampling, we nonetheless sought to optimize iron flocculation. We found viruses were best concentrated in seawater with five-fold higher iron concentrations than the standard used, inhibition of DNase activity reduced purification effectiveness, and five-fold more iron was needed to flocculate viruses from freshwater than seawater—critical knowledge for those seeking to apply this broadly used method to freshwater virome samples. Overall, our results demonstrated that ultrafiltration and purification performed better than iron chloride flocculation and purification in the tested matrices. Given that the method performance depended on the solids content and salinity of the samples, we suggest spike-and-recovery experiments be applied when concentrating and purifying sample types that diverge from those tested here.

Advances in Microbiome Detection Technologies and Application in Antirheumatic Drug Design

Rheumatic diseases are a kind of chronic inflammatory and autoimmune disease affecting the connection or supporting structures of the human body, such as the most common diseases Ankylosing spondylitis (AS), gout and Systemic lupus erythematosus (SLE). Although the precise etiology and pathogenesis of the different types of rheumatic diseases remain mostly unknown, it is now commonly believed that these diseases are attributed to some complex interactions between genetics and environmental factors, especially the gut microbiome. Altered microbiome showed clinical improvement in disease symptoms and partially restored to normality after prescribing disease-modifying antirheumatic drugs (DMARDs) or other treatment strategies. Recent advances in next-generation sequencing-based microbial profiling technology, especially metagenomics, have identified alteration of the composition and function of the gut microbiota in patients. Clinical and experimental data suggest that dysbiosis may play a pivotal role in the pathogenesis of these diseases. In this paper, we provide a brief review of the advances in the microbial profiling technology and up-to-date resources for accurate taxonomic assignment of metagenomic reads, which is a key step for metagenomics studies. In addition, we review the altered gut microbiota signatures that have been reported so far across various studies, upon which diagnostics classification models can be constructed, and the drug-induced regulation of the host microbiota can be used to control disease progression and symptoms.

Next generation sequencing approaches to evaluate water and wastewater quality

The emergence of next generation sequencing (NGS) is revolutionizing the potential to address complex microbiological challenges in the water industry. NGS technologies can provide holistic insight into microbial communities and their functional capacities in water and wastewater systems, thus eliminating the need to develop a new assay for each target organism or gene. However, several barriers have hampered wide-scale adoption of NGS by the water industry, including cost, need for specialized expertise and equipment, challenges with data analysis and interpretation, lack of standardized methods, and the rapid pace of development of new technologies. In this critical review, we provide an overview of the current state of the science of NGS technologies as they apply to water, wastewater, and recycled water. In addition, a systematic literature review was conducted in which we identified over 600 peer-reviewed journal articles on this topic and summarized their contributions to six key areas relevant to the water and wastewater fields: taxonomic classification and pathogen detection, functional and catabolic gene characterization, antimicrobial resistance (AMR) profiling, bacterial toxicity characterization, Cyanobacteria and harmful algal bloom identification, and virus characterization. For each application, we have presented key trends, noteworthy advancements, and proposed future directions. Finally, key needs to advance NGS technologies for broader application in water and wastewater fields are assessed.

Metagenomic exploration of antibiotic resistome in treated wastewater effluents and their receiving water

Environmental dissemination of antimicrobial resistance is a global health problem. Antimicrobial-resistant bacteria and antibiotic-resistant genes (ARGs) are constantly released into the environment through effluents (EFs) from wastewater treatment plants (WWTPs). Thus, requiring a better understanding of the selection and fate of ARGs in wastewater treatment processes. Therefore, we investigated the impacts of urban WWTP EFs on receiving water in the context of their resistomes and mobilomes. We used a HiSeq-based short read metagenomic approach to address the dynamics and diversity of ARGs in WWTP EF as well as the upstream (UP) and downstream (DN) river waters, followed by an investigation of plasmid-mediated ARGs. The abundance of ARGs at each site varied from 7.2 × 10^-2 to 7.4 × 10^-1 ARG copies per 16S rRNA gene copy, and EF samples showed the highest abundance, followed by DN and UP water samples. ARG diversity ranged from 121 to 686 types per site, and EF had the most diverse ARGs. Commonly identified ARGs in the EF and DN samples were clinically important and were absent in UP samples. The abundance of ARGs, mobile genetic elements (MGEs), and plasmid contigs found only in EF and DN were positively correlated with each other, indicating the importance of mobilomes in the dissemination of ARGs in the environment. Moreover, the proportions of plasmid-mediated ARGs was highest in the EF samples, followed by the DN and UP samples. These findings suggest that WWTP EF may act as a driving factor shaping the resistomes and mobilomes of receiving waters. In particular, a higher abundance of plasmid-mediated ARGs in WWTP EF suggests higher transmissibility in the DN environment.

Expanding ecological assessment by integrating microorganisms into routine freshwater biomonitoring

Bioindication has become an indispensable part of water quality monitoring in most countries of the world, with the presence and abundance of bioindicator taxa, mostly multicellular eukaryotes, used for biotic indices. In contrast, microbes (bacteria, archaea and protists) are seldom used as bioindicators in routine assessments, although they have been recognized for their importance in environmental processes. Recently, the use of molecular methods has revealed unexpected diversity within known functional groups and novel metabolic pathways that are particularly important in energy and nutrient cycling. In various habitats, microbial communities respond to eutrophication, metals, and natural or anthropogenic organic pollutants through changes in diversity and function. In this review, we evaluated the common trends in these changes, documenting that they have value as bioindicators and can be used not only for monitoring but also for improving our understanding of the major processes in lotic and lentic environments. Current knowledge provides a solid foundation for exploiting microbial taxa, community structures and diversity, as well as functional genes, in novel monitoring programs. These microbial community measures can also be combined into biotic indices, improving the resolution of individual bioindicators. Here, we assess particular molecular approaches complemented by advanced bioinformatic analysis, as these are the most promising with respect to detailed bioindication value. We conclude that microbial community dynamics are a missing link important for our understanding of rapid changes in the structure and function of aquatic ecosystems, and should be addressed in the future environmental monitoring of freshwater ecosystems.

Students in a Course-Based Undergraduate Research Experience Course Discovered Dramatic Changes in the Bacterial Community Composition Between Summer and Winter Lake Samples

Course-based undergraduate research experience (CURE) courses incorporate high-impact pedagogies that have been shown to increase undergraduate retention among underrepresented minorities and women. As part of the Building Infrastructure Leading to Diversity program at the University of Detroit Mercy, a CURE metagenomics course was established in the winter of 2019. Students investigated the bacterial community composition in a eutrophic cove in Lake Saint Clair (Harrison Township, MI, United States) from water samples taken in the summer and winter. The students created 16S rRNA libraries that were sequenced using next-generation sequencing technology. They used a public web-based supercomputing resource to process their raw sequencing data and web-based tools to perform advanced statistical analysis. The students discovered that the most common operational taxonomic unit, representing 31% of the prokaryotic sequences in both summer and winter samples, corresponded to an organism that belongs to a previously unidentified phylum. This result showed the students the power of metagenomics because the approach was able to detect unclassified organisms. Principal Coordinates Analysis of Bray-Curtis dissimilarity index data showed that the winter community was distinct from the summer community [Analysis of Similarities (ANOSIM) r = 0.59829, n = 18, and p < 0.001]. Dendrograms based on hierarchically clustered Pearson correlation coefficients of phyla were divided into a winter clade and a summer clade. The conclusion is that the winter bacterial population was fundamentally different from the summer population, even though the samples were taken from the same locations in a protected cove. Because of the small class sizes, qualitative as well as statistical methods were used to evaluate the course's impact on student attitudes. Results from the Laboratory Course Assessment Survey showed that most of the respondents felt they were contributing to scientific knowledge and the course fostered student collaboration. The majority of respondents agreed or strongly agreed that the course incorporated iteration aspects of scientific investigations, such as repeating procedures to fix problems. In summary, the metagenomics CURE course was able to add to scientific knowledge and allowed students to participate in authentic research.

Metagenomic Sequencing and Quantitative Real-Time PCR for Fecal Pollution Assessment in an Urban Watershed

Microbial contamination of recreation waters is a major concern globally, with pollutants originating from many sources, including human and other animal wastes often introduced during storm events. Fecal contamination is traditionally monitored by employing culture methods targeting fecal indicator bacteria (FIB), namely E. coli and enterococci, which provides only limited information of a few microbial taxa and no information on their sources. Host-associated qPCR and metagenomic DNA sequencing are complementary methods for FIB monitoring that can provide enhanced understanding of microbial communities and sources of fecal pollution. Whole metagenome sequencing (WMS), quantitative real-time PCR (qPCR), and culture-based FIB tests were performed in an urban watershed before and after a rainfall event to determine the feasibility and application of employing a multi-assay approach for examining microbial content of ambient source waters. Cultivated E. coli and enterococci enumeration confirmed presence of fecal contamination in all samples exceeding local single sample recreational water quality thresholds (E. coli, 410 MPN/100 mL; enterococci, 107 MPN/100 mL) following a rainfall. Test results obtained with qPCR showed concentrations of E. coli, enterococci, and human-associated genetic markers increased after rainfall by 1.52-, 1.26-, and 1.11-fold log₁₀ copies per 100 mL, respectively. Taxonomic analysis of the surface water microbiome and detection of antibiotic resistance genes, general FIB, and human-associated microorganisms were also employed. Results showed that fecal contamination from multiple sources (human, avian, dog, and ruminant), as well as FIB, enteric microorganisms, and antibiotic resistance genes increased demonstrably after a storm event. In summary, the addition of qPCR and WMS to traditional surrogate techniques may provide enhanced characterization and improved understanding of microbial pollution sources in ambient waters.

High-accuracy long-read amplicon sequences using unique molecular identifiers with Nanopore or PacBio sequencing

High-throughput amplicon sequencing of large genomic regions remains challenging for short-read technologies. Here, we report a high-throughput amplicon sequencing approach combining unique molecular identifiers (UMIs) with Oxford Nanopore Technologies (ONT) or Pacific Biosciences circular consensus sequencing, yielding high-accuracy single-molecule consensus sequences of large genomic regions. We applied our approach to sequence ribosomal RNA operon amplicons (~4,500 bp) and genomic sequences (>10,000 bp) of reference microbial communities in which we observed a chimera rate <0.02%. To reach a mean UMI consensus error rate <0.01%, a UMI read coverage of 15× (ONT R10.3), 25× (ONT R9.4.1) and 3× (Pacific Biosciences circular consensus sequencing) is needed, which provides a mean error rate of 0.0042%, 0.0041% and 0.0007%, respectively.

Microbial communities and gene contributions in smokeless tobacco products

Smokeless tobacco products (STP) contain bacteria, mold, and fungi due to exposure from surrounding environments and tobacco processing. This has been a cause for concern since the presence of microorganisms has been linked to the formation of highly carcinogenic tobacco-specific nitrosamines. These communities have also been reported to produce toxins and other pro-inflammatory molecules that can cause mouth lesions and elicit inflammatory responses in STP users. Moreover, microbial species in these products could transfer to the mouth and gastrointestinal tract, potentially altering the established respective microbiotas of the consumer. Here, we present the first metagenomic analysis of select smokeless tobacco products, specifically US domestic moist and dry snuff. Bacterial, eukaryotic, and viral species were found in all tobacco products where 68% of the total species was comprised of Bacteria with 3 dominant phyla but also included 32% Eukarya and 1% share abundance for Archaea and Viruses. Furthermore, 693,318 genes were found to be present and included nitrate and nitrite reduction and transport enzymes, antibiotic resistance genes associated with resistance to vancomycin, β-lactamases, their derivatives, and other antibiotics, as well as genes encoding multi-drug transporters and efflux pumps. Additional analyses showed the presence of endo- and exotoxin genes in addition to other molecules associated with inflammatory responses. Our results present a novel aspect of the smokeless tobacco microbiome and provide a better understanding of these products' microbiology. KEY POINTS: • The findings presented will help understand microbial contributions to overall STP chemistries. • Gene function categorization reveals harmful constituents outside canonical forms. • Pathway genes for TSNA precursor activity may occur at early stages of production. • Bacteria in STPs carry antibiotic resistance genes and gene transfer mechanisms.

A Targeted Metagenomics Approach to Study the Diversity of Norovirus GII in Shellfish Implicated in Outbreaks

Human noroviruses (NoV) cause epidemics of acute gastroenteritis (AGE) worldwide and can be transmitted through consumption of contaminated foods. Fresh products such as shellfish can be contaminated by human sewage during production, which results in the presence of multiple virus strains, at very low concentrations. Here, we tested a targeted metagenomics approach by deep-sequencing PCR amplicons of the capsid (VP1) and polymerase (RdRp) viral genes, on a set of artificial samples and on shellfish samples associated to AGE outbreaks, to evaluate its advantages and limitations in the identification of strains from the NoV genogroup (G) II. Using artificial samples, the method allowed the sequencing of most strains, but not all, and displayed variability between replicates especially with lower viral concentrations. Using shellfish samples, targeted metagenomics was compared to Sanger-sequencing of cloned amplicons and was able to identify a higher diversity of NoV GII and GIV strains. It allowed phylogenetic analyses of VP1 sequences and the identification, in most samples, of GII.17[P17] strains, also identified in related clinical samples. Despite several limitations, combining RdRp- and VP1-targeted metagenomics is a sensitive approach allowing the study NoV diversity in low-contaminated foods and the identification of NoV strains implicated in outbreaks.

A Soluble Fiber Diet Increases Bacteroides fragilis Group Abundance and Immunoglobulin A Production in the Gut

Immunoglobulin A (IgA) is essential for defense of the intestinal mucosa against harmful pathogens. Previous studies have shown that Bacteroidetes, the major phylum of gut microbiota together with Firmicutes, impact IgA production. However, the relative abundances of species of Bacteroidetes responsible for IgA production were not well understood. In the present study, we identified some specific Bacteroidetes species that were associated with gut IgA induction by hsp60-based profiling of species distribution among Bacteroidetes The levels of IgA and the expression of the gene encoding activation-induced cytidine deaminase (AID) in the large intestine lamina propria, which is crucial for class switch recombination from IgM to IgA, were increased in soluble high-fiber diet (sHFD)-fed mice. We found that Bacteroides acidifaciens was the most abundant Bacteroidetes species in both sHFD- and normal diet-fed mice. In addition, the gut IgA levels were associated with the relative abundance of Bacteroides fragilis group species such as Bacteroides faecis, Bacteroides caccae, and Bacteroides acidifaciens Conversely, the ratio of B. acidifaciens to other Bacteroidetes species was reduced in insoluble high-fiber diet fed- and no-fiber diet-fed mice. To investigate whether B. acidifaciens increases IgA production, we generated B. acidifaciens monoassociated mice and found increased gut IgA production and AID expression. Collectively, soluble dietary fiber increases the ratio of gut Bacteroides fragilis group, such as B. acidifaciens, and IgA production. This might improve gut immune function, thereby protecting against bowel pathogens and reducing the incidence of inflammatory bowel diseases.IMPORTANCE Immunoglobulin A (IgA) is essential for defense of the intestinal mucosa against harmful pathogens. Gut microbiota impact IgA production, but the specific species responsible for IgA production remain largely elusive. Previous studies have shown that IgA and Bacteroidetes, the major phyla of gut microbiota, were increased in soluble high-fiber diet-fed mice. We show here that the levels of IgA in the gut and the expression of activation-induced cytidine deaminase (AID) in the large intestine lamina propria, which is crucial for class switch recombination from IgM to IgA, were correlated with the abundance of Bacteroides fragilis group species such as Bacteroides faecis, Bacteroides caccae, and Bacteroides acidifaciens B. acidifaciens monoassociated mice increased gut IgA production and AID expression. Soluble dietary fiber may improve gut immune function, thereby protecting against bowel pathogens and reducing inflammatory bowel diseases.

Method for the Identification of Plant DNA in Food Using Alignment-Free Analysis of Sequencing Reads: A Case Study on Lupin

Fast and reliable analytical methods for the identification of plants from metagenomic samples play an important role in identifying the components of complex mixtures of processed biological materials, including food, herbal products, gut contents or environmental samples. Different PCR-based methods that are commonly used for plant identification from metagenomic samples are often inapplicable due to DNA degradation, a low level of successful amplification or a lack of detection power. We introduce a method that combines metagenomic sequencing and an alignment-free k-mer based approach for the identification of plant DNA in processed metagenomic samples. Our method identifies plant DNA directly from metagenomic sequencing reads and does not require mapping or assembly of the reads. We identified more than 31,000 Lupinus-specific 32-mers from assembled chloroplast genome sequences. We demonstrate that lupin DNA can be detected from controlled mixtures of sequences from target species (different Lupinus species) and closely related non-target species (Arachis hypogaea, Glycine max, Pisum sativum, Vicia faba, Phaseolus vulgaris, Lens culinaris, and Cicer arietinum). Moreover, these 32-mers are detectable in the following processed samples: lupin flour, conserved seeds and baked cookies containing different amounts of lupin flour. Under controlled conditions, lupin-specific components are detectable in baked cookies containing a minimum of 0.05% of lupin flour in wheat flour.

DNA sequencing, genomes and genetic markers of microbes on fruits and vegetables

The development of DNA sequencing technology has provided an effective method for studying foodborne and phytopathogenic microorganisms on fruits and vegetables (F & V). DNA sequencing has successfully proceeded through three generations, including the tens of operating platforms. These advances have significantly promoted microbial whole‐genome sequencing (WGS) and DNA polymorphism research. Based on genomic and regional polymorphisms, genetic markers have been widely obtained. These molecular markers are used as targets for PCR or chip analyses to detect microbes at the genetic level. Furthermore, metagenomic analyses conducted by sequencing the hypervariable regions of ribosomal DNA (rDNA) have revealed comprehensive microbial communities in various studies on F & V. This review highlights the basic principles of three generations of DNA sequencing, and summarizes the WGS studies of and available DNA markers for major bacterial foodborne pathogens and phytopathogenic fungi found on F & V. In addition, rDNA sequencing‐based bacterial and fungal metagenomics are summarized under three topics. These findings deepen the understanding of DNA sequencing and its application in studies of foodborne and phytopathogenic microbes and shed light on strategies for the monitoring of F & V microbes and quality control.

Control of Waterborne Human Viruses by Indigenous Bacteria and Protists Is Influenced by Temperature, Virus Type, and Microbial Species

Human viruses are ubiquitous contaminants in surface waters, where they can persist over extended periods of time. Among the factors governing their environmental persistence, the control (removal or inactivation) by microorganisms remains poorly understood. Here, we determined the contribution of indigenous bacteria and protists to the decay of human viruses in surface waters. Incubation of echovirus 11 (E11) in freshwater from Lake Geneva and seawater from the Mediterranean Sea led to a 2.5-log₁₀ reduction in the infectious virus concentration within 48 h at 22°C, whereas E11 was stable in sterile controls. The observed virus reduction was attributed to the action of both bacteria and protists in the biologically active matrices. The effect of microorganisms on viruses was temperature dependent, with a complete inhibition of microbial virus control in lake water at temperatures of ≤16°C. Among three protist isolates tested (Paraphysomonas sp., Uronema marinum, and Caecitellus paraparvulus), Caecitellus paraparvulus was particularly efficient at controlling E11 (2.1-log₁₀ reduction over 4 days with an initial protist concentration of 10³ cells ml^-1). In addition, other viruses (human adenovirus type 2 and bacteriophage H6) exhibited different grazing kinetics than E11, indicating that the efficacy of antiviral action also depended on the type of virus. In conclusion, indigenous bacteria and protists in lake water and seawater can modulate the persistence of E11. These results pave the way for further research to understand how microorganisms control human viral pathogens in aquatic ecosystems and to exploit this process as a treatment solution to enhance microbial water safety.IMPORTANCE Waterborne human viruses can persist in the environment, causing a risk to human health over long periods of time. In this work, we demonstrate that in both freshwater and seawater environments, indigenous bacteria and protists can graze on waterborne viruses and thereby reduce their persistence. We furthermore demonstrate that the efficiency of the grazing process depends on temperature, virus type, and protist species. These findings may facilitate the design of biological methods for the disinfection of water and wastewater.

Metagenomic analysis of viruses, bacteria and protozoa in irrigation water

Viruses (e.g., noroviruses and hepatitis A and E virus), bacteria (e.g., Salmonella spp. and pathogenic Escherichia coli) and protozoa (e.g., Cryptosporidium parvum and Giardia intestinalis) are well-known contributors to food-borne illnesses linked to contaminated fresh produce. As agricultural irrigation increases the total amount of water used annually, reclaimed water is a good alternative to reduce dependency on conventional irrigation water sources. European guidelines have established acceptable concentrations of certain pathogens and/or indicators in irrigation water, depending on the irrigation system used and the irrigated crop. However, the incidences of food-borne infections are known to be underestimated and all the different pathogens contributing to these infections are not known. Next-generation sequencing (NGS) enables the determination of the viral, bacterial and protozoan populations present in a water sample, providing an opportunity to detect emerging pathogens and develop improved tools for monitoring the quality of irrigation water. This is a descriptive study of the virome, bacteriome and parasitome present in different irrigation water sources. We applied the same concentration method for all the studied samples and specific metagenomic approaches to characterize both DNA and RNA viruses, bacteria and protozoa. In general, most of the known viral species corresponded to plant viruses and bacteriophages. Viral diversity in river water varied over the year, with higher bacteriophage prevalences during the autumn and winter. Reservoir water contained Enterobacter cloacae, an opportunistic human pathogen and an indicator of fecal contamination, as well as Naegleria australiensis and Naegleria clarki. Hepatitis E virus and Naegleria fowleri, emerging human pathogens, were detected in groundwater. Reclaimed water produced in a constructed wetland system presented a virome and bacteriome that resembled those of freshwater samples (river and reservoir water). Viral, bacterial and protozoan pathogens were occasionally detected in the different irrigation water sources included in this study, justifying the use of improved NGS techniques to get a comprehensive evaluation of microbial species and potential environmental health hazards associated to irrigation water.

VHost-Classifier: virus-host classification using natural language processing

MOTIVATION

When analyzing viral metagenomic sequences, it is often desired to filter the results of a BLAST analysis by the host species of the virus. VHost-Classifier automates this procedure using a natural language processing algorithm written in Python 3, which takes a list of taxonomic identifiers (taxids) returned from a BLAST query using viral sequences as input. The taxid output is binned by the evolutionary lineage of their host, based on string matching the words in their English names. If VHost-Classifier cannot identify a host, it attempts to bin the sequences by the environment from which the sample originated. VHost-Classifier predicts the evolutionary lineage of the host from the virus name and does not rely on referencing taxids against a database; therefore, it is not constrained by the size of a database and can host classify newly characterized viruses.

RESULTS

Benchmarked on a test dataset of 1000 randomly selected viral taxids on the NCBI taxonomy database, VHost-Classifier assigned, with 100% accuracy, a host to the rank of Class for >93% of viruses, and to the rank of Family for >37% of viruses.

AVAILABILITY AND IMPLEMENTATION

For more information about VHost-Classifier as well as implementation instructions, visit https://github.com/Kzra/VHost-Classifier.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

16S rRNA Gene Sequencing Reveals a Shift in the Microbiota of Diaphorina citri During the Psyllid Life Cycle

The Asian citrus psyllid (Diaphorina citri) is a major pest of citrus trees as it transmits Candidatus Liberibacter asiaticus (CLas). The composition of a host’s microbiota can affect the evolution and ecological distribution of the host. This study monitored the compositional shifts in the citrus psyllid microbiota through all the life stages (egg, nymph 1–5 stages, and adult) by next-generation sequencing (NGS) and quantitative real-time PCR. There were clear differences in both α- and β-diversity of microbiota through the psyllid life stages. Microbiota diversity was markedly higher in the nymph 2–5 stages than in the adult, egg, and nymph 1 stages. Proteobacteria were dominant in all the life stages of D. citri, representing >97.5% of the total bacterial community, and Candidatus Profftella armature was the dominant genus in all the life stages. Data from the qPCR analysis showed an exponential increase in the populations of three D. citri endosymbionts: Candidatus Profftella armature, Candidatus Carsonella ruddii, and Wolbachia. The gut bacterium Pantoea was present in all the life stages, but it was markedly higher in the nymph 2–5 stages. The microbiota composition substantially differed among the egg–nymph 1, nymphs 2–5, and adult stages. Therefore, we successfully characterized the microbiota dynamics and thus identified a microbiota shift during the life cycle of D. citri by 16S rRNA gene sequencing and quantitative PCR. Moreover, 16S rRNA gene sequencing suggested that D. citri acquired the ability to bear CLas in the nymph 1 stage. This study enhances our understanding of microbial establishment in the developing D. citri and provides a reference resource for the identification of potential biocontrol approaches against this pest.

ITSoneDB: a comprehensive collection of eukaryotic ribosomal RNA Internal Transcribed Spacer 1 (ITS1) sequences

A holistic understanding of environmental communities is the new challenge of metagenomics. Accordingly, the amplicon-based or metabarcoding approach, largely applied to investigate bacterial microbiomes, is moving to the eukaryotic world too. Indeed, the analysis of metabarcoding data may provide a comprehensive assessment of both bacterial and eukaryotic composition in a variety of environments, including human body. In this respect, whereas hypervariable regions of the 16S rRNA are the de facto standard barcode for bacteria, the Internal Transcribed Spacer 1 (ITS1) of ribosomal RNA gene cluster has shown a high potential in discriminating eukaryotes at deep taxonomic levels. As metabarcoding data analysis rely on the availability of a well-curated barcode reference resource, a comprehensive collection of ITS1 sequences supplied with robust taxonomies, is highly needed. To address this issue, we created ITSoneDB (available at http://itsonedb.cloud.ba.infn.it/) which in its current version hosts 985 240 ITS1 sequences spanning over 134 000 eukaryotic species. Each ITS1 is mapped on the NCBI reference taxonomy with its start and end positions precisely annotated. ITSoneDB has been developed in agreement to the FAIR guidelines by enabling the users to query and download its content through a simple web-interface and access relevant metadata by cross-linking to European Nucleotide Archive.

Dependency of DNA extraction efficiency on cell concentration confounds molecular quantification of microorganisms in groundwater

Quantification of microbes in water systems is essential to industrial practices ranging from drinking water and wastewater treatment to groundwater remediation. While quantification using DNA-based molecular methods is precise, the accuracy is dependent on DNA extraction efficiencies. We show that the DNA yield is strongly impacted by the cell concentration in groundwater samples (r = -0.92, P < 0.0001). This has major implications for industrial applications using quantitative polymerase chain reaction (qPCR) to determine cell concentrations in water, including bioremediation. We propose a simple normalization method using a DNA recovery ratio, calculated with the total cell count and DNA yield. Application of this method to enumeration of bacteria and archaea in groundwater samples targeting phylogenetic markers (16S rRNA) demonstrated an increased goodness of fit after normalization (7.04 vs 0.94 difference in Akaike's information criteria). Furthermore, normalization was applied to qPCR quantification of functional genes and combined with DNA sequencing of archaeal and bacterial 16S rRNA genes to monitor changes in abundance of methanogenic archaea and sulphate-reducing bacteria in groundwater. The integration of qPCR and DNA sequencing with appropriate normalization enables high-throughput quantification of microbial groups using increasingly affordable and accessible techniques. This research has implications for microbial ecology and engineering research as well as industrial practice.

Proliferation of hydrocarbon-degrading microbes at the bottom of the Mariana Trench

BACKGROUND

The Mariana Trench is the deepest known site in the Earth's oceans, reaching a depth of ~ 11,000 m at the Challenger Deep. Recent studies reveal that hadal waters harbor distinctive microbial planktonic communities. However, the genetic potential of microbial communities within the hadal zone is poorly understood.

RESULTS

Here, implementing both culture-dependent and culture-independent methods, we perform extensive analysis of microbial populations and their genetic potential at different depths in the Mariana Trench. Unexpectedly, we observed an abrupt increase in the abundance of hydrocarbon-degrading bacteria at depths > 10,400 m in the Challenger Deep. Indeed, the proportion of hydrocarbon-degrading bacteria at > 10,400 m is the highest observed in any natural environment on Earth. These bacteria were mainly Oleibacter, Thalassolituus, and Alcanivorax genera, all of which include species known to consume aliphatic hydrocarbons. This community shift towards hydrocarbon degraders was accompanied by increased abundance and transcription of genes involved in alkane degradation. Correspondingly, three Alcanivorax species that were isolated from 10,400 m water supplemented with hexadecane were able to efficiently degrade n-alkanes under conditions simulating the deep sea, as did a reference Oleibacter strain cultured at atmospheric pressure. Abundant n-alkanes were observed in sinking particles at 2000, 4000, and 6000 m (averaged 23.5 μg/gdw) and hadal surface sediments at depths of 10,908, 10,909, and 10,911 m (averaged 2.3 μg/gdw). The δ²H values of n-C_16/18 alkanes that dominated surface sediments at near 11,000-m depths ranged from - 79 to - 93‰, suggesting that these sedimentary alkanes may have been derived from an unknown heterotrophic source.

CONCLUSIONS

These results reveal that hydrocarbon-degrading microorganisms are present in great abundance in the deepest seawater on Earth and shed a new light on potential biological processes in this extreme environment.

Metagenomes of a Freshwater Charavirus from British Columbia Provide a Window into Ancient Lineages of Viruses

Charophyte algae, not chlorophyte algae, are the ancestors of ‘higher plants’; hence, viruses infecting charophytes may be related to those that first infected higher plants. Streamwaters from British Columbia, Canada, yielded single-stranded RNA metagenomes of Charavirus canadensis (CV-Can), that are similar in genomic architecture, length (9593 nt), nucleotide identity (63.4%), and encoded amino-acid sequence identity (53.0%) to those of Charavirus australis (CV-Aus). The sequences of their RNA-dependent RNA-polymerases (RdRp) resemble those found in benyviruses, their helicases those of hepaciviruses and hepegiviruses, and their coat-proteins (CP) those of tobamoviruses; all from the alphavirus/flavivirus branch of the ‘global RNA virome’. The 5’-terminus of the CV-Can genome, but not that of CV-Aus, is complete and encodes a methyltransferase domain. Comparisons of CP sequences suggests that Canadian and Australian charaviruses diverged 29–46 million years ago (mya); whereas, the CPs of charaviruses and tobamoviruses last shared a common ancestor 212 mya, and the RdRps of charaviruses and benyviruses 396 mya. CV-Can is sporadically abundant in low-nutrient freshwater rivers in British Columbia, where Chara braunii, a close relative of C. australis, occurs, and which may be its natural host. Charaviruses, like their hosts, are ancient and widely distributed, and thus provide a window to the viromes of early eukaryotes and, even, Archaea.

Keanu: a novel visualization tool to explore biodiversity in metagenomes

Background

One of the main challenges when analyzing complex metagenomics data is the fact that large amounts of information need to be presented in a comprehensive and easy-to-navigate way. In the process of analyzing FASTQ sequencing data, visualizing which organisms are present in the data can be useful, especially with metagenomics data or data suspected to be contaminated. Here, we describe the development and application of a command-line tool, Keanu, for visualizing and exploring sample content in metagenomics data. We developed Keanu as an interactive tool to make viewing complex data easier.

Results

Keanu, a tool for exploring sequence content, helps a user to understand the presence and abundance of organisms in a sample by analyzing alignments against a database that contains taxonomy data and displaying them in an interactive web page. The content of a sample can be presented either as a collapsible tree, with node size indicating abundance, or as a bilevel partition graph, with arc size indicating abundance. Here, we illustrate how Keanu works by exploring shotgun metagenomics data from a sample collected from a bluff that contained paleosols and a krotovina in an alpine site in Ft. Greely, Alaska.

Conclusions

Keanu provides a simple means by which researchers can explore and visualize species present in sequence data generated from complex communities and environments. Keanu is written in Python and is freely available at https://github.com/IGBB/keanu.

Biodiversity of biological soil crusts from the Polar Regions revealed by metabarcoding

Biological soil crusts (BSCs) are amalgamations of autotrophic, heterotrophic and saprotrophic organisms. In the Polar Regions, these unique communities occupy essential ecological functions such as primary production, nitrogen fixation and ecosystem engineering. Here, we present the first molecular survey of BSCs from the Arctic and Antarctica focused on both eukaryotes and prokaryotes as well as passive and active biodiversity. Considering sequence abundance, Bryophyta is among the most abundant taxa in all analyzed BSCs suggesting that they were in a late successional stage. In terms of algal and cyanobacterial biodiversity, the genera Chloromonas, Coccomyxa, Elliptochloris and Nostoc were identified in all samples regardless of origin confirming their ubiquitous distribution. For the first time, we found the chrysophyte Spumella to be common in polar BSCs as it was present in all analyzed samples. Co-occurrence analysis revealed the presence of sulfur metabolizing microbes indicating that BSCs also play an important role for the sulfur cycle. In general, phototrophs were most abundant within the BSCs but there was also a diverse community of heterotrophs and saprotrophs. Our results show that BSCs are unique microecosystems in polar environments with an unexpectedly high biodiversity.

The Microbial Composition of Bacteroidetes Species in Ulcerative Colitis Is Effectively Improved by Combination Therapy With Fecal Microbiota Transplantation and Antibiotics

BACKGROUND

We previously reported that fresh fecal microbiota transplantation (FMT) after triple-antibiotic therapy (amoxicillin, fosfomycin, and metronidazole [AFM]; A-FMT) synergistically contributed to the recovery of phylum Bacteroidetes composition associated with the endoscopic severity and treatment efficacy of ulcerative colitis (UC). Here, we performed further microbial analyses using a higher-resolution method to identify the key bacterial species in UC and determine whether viable Bacteroidetes species from donor feces were successfully colonized by A-FMT.

METHODS

The taxonomic composition of Bacteroidetes in 25 healthy donors and 27 UC patients at baseline was compared at the species level using a heat-shock protein (hsp) 60-based microbiome method. Microbiota alterations before and after treatment of UC patients were also analyzed in 24 cases (n = 17 A-FMT; n = 3 mono-AFM; n = 4 mono-FMT).

RESULTS

We found species-level dysbiosis within the phylum Bacteroidetes in UC samples, which was associated with reduced species diversity, resulting from hyperproliferation and hypoproliferation of particular species. Moreover, in responders treated with A-FMT, diversity was significantly recovered at 4 weeks after a fresh round of FMT, after which high degrees of similarity in Bacteroidetes species composition among recipients and donors were observed.

CONCLUSIONS

A-FMT alleviated intestinal dysbiosis, which is caused by the loss of Bacteroidetes species diversity in patients with UC. Eradication of dysbiotic indigenous Bacteroidetes species by AFM pretreatment might promote the colonization of viable Bacteroidetes cells, thereby improving the intestinal microbiota dysbiosis induced by UC. Our findings serve as a basis for further investigations into the mechanisms of FMT.

Do you cov me? Effect of coverage reduction on metagenome shotgun sequencing studies

Shotgun metagenomics sequencing is a powerful tool for the characterization of complex biological matrices, enabling analysis of prokaryotic and eukaryotic organisms and viruses in a single experiment, with the possibility of reconstructing de novo the whole metagenome or a set of genes of interest. One of the main factors limiting the use of shotgun metagenomics on wide scale projects is the high cost associated with the approach. We set out to determine if it is possible to use shallow shotgun metagenomics to characterize complex biological matrices while reducing costs. We used a staggered mock community to estimate the optimal threshold for species detection. We measured the variation of several summary statistics simulating a decrease in sequencing depth by randomly subsampling a number of reads. The main statistics that were compared are diversity estimates, species abundance, and ability of reconstructing de novo the metagenome in terms of length and completeness. Our results show that diversity indices of complex prokaryotic, eukaryotic and viral communities can be accurately estimated with 500,000 reads or less, although particularly complex samples may require 1,000,000 reads. On the contrary, any task involving the reconstruction of the metagenome performed poorly, even with the largest simulated subsample (1,000,000 reads). The length of the reconstructed assembly was smaller than the length obtained with the full dataset, and the proportion of conserved genes that were identified in the meta-genome was drastically reduced compared to the full sample. Shallow shotgun metagenomics can be a useful tool to describe the structure of complex matrices, but it is not adequate to reconstruct—even partially—the metagenome.

Development of a New Application for Comprehensive Viability Analysis Based on Microbiome Analysis by Next-Generation Sequencing: Insights into Staphylococcal Carriage in Human Nasal Cavities

The nasal carriage rate of Staphylococcus aureus in human is 25 to 30%, and S. aureus sporadically causes severe infections. However, the mechanisms underlying staphylococcal carriage remain largely unknown. In the present study, we constructed an rpoB-based microbiome method for staphylococcal species discrimination. Based on a microbiome scheme targeting viable cell DNA using propidium monoazide (PMA) dye (PMA microbiome method), we also developed a new method to allow the comprehensive viability analysis of any bacterial taxon. To clarify the ecological distribution of staphylococci in the nasal microbiota, we applied these methods in 46 nasal specimens from healthy adults. PMA microbiome results showed that Staphylococcaceae and Corynebacteriaceae were the most predominant viable taxa (average relative abundance: 0.435262 and 0.375195, respectively), and Staphylococcus epidermidis exhibited the highest viability in the nasal microbiota. Staphylococcus aureus detection rates from nasal specimens by rpoB-based conventional and PMA microbiome methods were 84.8% (39 of 46) and 69.5% (32 of 46), respectively, which substantially exceeded the values obtained by a culture method using identical specimens (36.9%). Our results suggest that Staphylococcaceae species, especially S. epidermidis, adapted most successfully to human nasal cavity. High detection of S. aureus DNA by microbiome methods suggests that almost all healthy adults are consistently exposed to S. aureus in everyday life. Furthermore, the large difference in S. aureus detection rates between culture and microbiome methods suggests that S. aureus cells frequently exist in a viable but nonculturable state in nasal cavities. Our method and findings will contribute to a better understanding of the mechanisms underlying carriage of indigenous bacteria.IMPORTANCE Metagenomic analyses, such as 16S rRNA microbiome methods, have provided new insights in various research fields. However, conventional 16S rRNA microbiome methods do not permit taxonomic analysis of only the viable bacteria in a sample and have poor resolving power below the genus level. Our new schemes allowed for viable cell-specific analysis and species discrimination, and nasal microbiome data using these methods provided some interesting findings regarding staphylococcal nasal carriage. According to our comprehensive viability analysis, the high viability of Staphylococcus species, especially Staphylococcus epidermidis, in human nasal carriage suggests that this taxon has adapted most successfully to human nasal tissue. Also, a higher detection rate of S. aureus DNA by microbiome methods (84.8%) than by a culture method (36.9%) suggests that almost all healthy adults are consistently exposed to Staphylococcus aureus in the medium and long term. Our findings will contribute to a better understanding of the mechanisms underlying the carriage of indigenous bacteria.

Human Activity Determines the Presence of Integron-Associated and Antibiotic Resistance Genes in Southwestern British Columbia

The dissemination of antibiotic resistant bacteria from anthropogenic sources into the environment poses an emerging public health threat. Antibiotic resistance genes (ARGs) and gene-capturing systems such as integron-associated integrase genes (intI) play a key role in alterations of microbial communities and the spread of antibiotic resistant bacteria into the environment. In order to assess the effect of anthropogenic activities on watersheds in southwestern British Columbia, the presence of putative antibiotic resistance and integrase genes was analyzed in the microbiome of agricultural, urban influenced, and protected watersheds. A metagenomics approach and high-throughput quantitative PCR (HT qPCR) were used to screen for elements of resistance including ARGs and intI. Metagenomic sequencing of bacterial genomic DNA was used to characterize the resistome of microbial communities present in watersheds over a 1-year period. There was a low prevalence of ARGs relative to the microbial population (<1%). Analysis of the metagenomic sequences detected a total of 60 elements of resistance including 46 ARGs, intI1, and groEL/intI1 genes and 12 quaternary ammonium compounds (qac) resistance genes across all watershed locations. The relative abundance and richness of ARGs was found to be highest in agriculture impacted watersheds compared to urban and protected watersheds. A downstream transport pattern was observed in the impacted watersheds (urban and agricultural) during dry months. Similar to other reports, this study found a strong association between intI1 and ARGs (e.g., sul1), an association which may be used as a proxy for anthropogenic activities. Chemical analysis of water samples for three major groups of antibiotics was below the detection limit. However, the high richness and gene copy numbers (GCNs) of ARGs in impacted sites suggest that the effects of effluents on microbial communities are occurring even at low concentrations of antimicrobials in the water column. Antibiotic resistance and integrase genes in a year-long metagenomic study showed that ARGs were driven mainly by environmental factors from anthropogenized sites in agriculture and urban watersheds. Environmental factors such as land-use and water quality parameters accounted for 45% of the variability observed in watershed locations.

Recent insights into the tick microbiome gained through next-generation sequencing

The tick microbiome comprises communities of microorganisms, including viruses, bacteria and eukaryotes, and is being elucidated through modern molecular techniques. The advent of next-generation sequencing (NGS) technologies has enabled the genes and genomes within these microbial communities to be explored in a rapid and cost-effective manner. The advantages of using NGS to investigate microbiomes surpass the traditional non-molecular methods that are limited in their sensitivity, and conventional molecular approaches that are limited in their scalability. In recent years the number of studies using NGS to investigate the microbial diversity and composition of ticks has expanded. Here, we provide a review of NGS strategies for tick microbiome studies and discuss the recent findings from tick NGS investigations, including the bacterial diversity and composition, influential factors, and implications of the tick microbiome.

Lifestyle alters GUT-bacteria function: Linking immune response and host

Microbiota in human is a "mixture society" of different species (i.e. bacteria, viruses, funguses) populations with a different way of relationship classification to Human. Human GUT serves as the host of the majority of different bacterial populations (GUT flora, more than 500 species), which are with us ("from the beginning") in an innate manner known as the commensal (no harm to each other) and symbiotic (mutual benefit) relationship. A homeostatic balance of host-bacteria relationship is very important and vital for a normal health process. However, this beneficial relationship and delicate homeostatic state can be disrupted by the imbalance of microbiome-composition of gut microbiota, expressing a pathogenic state. A strict homeostatic balance of microbiome-composition strongly depends on several factors; 1- lifestyle, 2- geography, 3- ethnicities, 4- "mom" as prime of the type of bacterial colonization in infant and 5- the disease. With such diversity in individuals combined with huge number of different bacterial species and their interactions, it is wise to perform an in-depth systems biology (e.g. genomics, proteomics, glycomics, and etcetera) analysis of personalized microbiome. Only in this way, we are able to generate a map of complete GUT microbiota and, in turn, to determine its interaction with host and intra-interaction with pathogenic bacteria. A specific microbiome analysis provides us the knowledge to decipher the nature of interactions between the GUT microbiota and the host and its response to the invading bacteria in a pathogenic state. The GUT-bacteria composition is independent of geography and ethnicity but lifestyle well affects GUT-bacteria composition and function. Microbiome knowledge obtained by systems biology also helps us to change the behavior of GUT microbiota in response to the pathogenic microbes as protection. Functional microbiome changes in response to environmental factors will be discussed in this review.