TARGETING THE 16S RRNA GENE FOR BACTERIAL IDENTIFICATION IN COMPLEX MIXED SAMPLES: COMPARATIVE EVALUATION OF SECOND (ILLUMINA) AND THIRD (OXFORD NANOPORE TECHNOLOGIES) GENERATION SEQUENCING TECHNOLOGIES

Cystic fibrosis pathogens persist in the upper respiratory tract following initiation of elexacaftor/tezacaftor/ivacaftor therapy

Elexacaftor/tezacaftor/ivacaftor (ETI) therapy has revolutionized the treatment of cystic fibrosis (CF) for most affected individuals but the effects of treatment on sinus microbiota are still unknown. Changes to the airway microbiota in CF are associated with disease state and alterations to the bacterial community after ETI initiation may require changes to clinical management regimens. We collected sinus swab samples from the middle meatus in an observational study of 38 adults with CF and chronic rhinosinusitis (CRS) from 2017 to 2021 and captured the initiation of ETI therapy. We performed 16S and custom amplicon sequencing to characterize the sinus microbiota pre- and post-ETI. Real-time quantitative PCR (RT-qPCR) was performed to estimate total bacterial abundance. Sinus samples from people with CF (pwCF) clustered into three community types, dependent on the dominant bacterial organism: a Pseudomonas-dominant, Staphylococcus-dominant, and mixed dominance cluster. Shannon's diversity index was low and not significantly altered post-ETI. Total bacterial load was not significantly lowered post-ETI. Pseudomonas spp. abundance was significantly reduced post-ETI, but eradication was not observed. Staphylococcus spp. became the dominant organism in most individuals post-ETI and we showed the presence of methicillin-resistant Staphylococcus aureus (MRSA) in the sinus both pre- and post-ETI. We also demonstrated that the sinus microbiome is predictive of the presence of Pseudomonas spp., Staphylococcus spp., and Serratia spp. in the sputum. Pseudomonas spp. and Staphylococcus spp., including MRSA, persist in the sinuses of pwCF after ETI therapy, indicating that these pathogens will continue to be important in CF airway disease management in the era of highly effective modulator therapies (HEMT).IMPORTANCEHighly effective modulator therapies (HEMT), such as elexacaftor/tezacaftor/ivacaftor (ETI), for cystic fibrosis (CF) have revolutionized patient care and quality of life for most affected individuals. The effects of these therapies on the microbiota of the airways are still unclear, though work has already been published on changes to microbiota in the sputum. Our study presents evidence for reduced relative abundance of Pseudomonas spp. in the sinuses following ETI therapy. We also show that Staphylococcus spp. becomes the dominant organism in the sinus communities of most individuals in this cohort after ETI therapy. We identified methicillin-resistant Staphylococcus aureus (MRSA) in the sinus microbiota both pre- and post-therapy. These findings demonstrate that pathogen monitoring and treatment will remain a vital part of airway disease management for people with cystic fibrosis (pwCF) in the era of HEMT.

Metagenomic evaluation of bacteria in drinking water using full-length 16S rRNA amplicons

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.

Dietary supplementation of mineral nanoparticles for channel catfish (Ictalurus punctatus)

This study evaluated the supplementation of iron and copper nanoparticles in channel catfish diets and their influences on growth and health. A comparative feeding trial was carried out for 9 weeks to evaluate combinations of iron and copper nanoparticles: only iron nanoparticles (IronNP), only copper nanoparticles (CopperNP), CopperNP + IronNP, and a control diet supplemented with inorganic iron and copper (FeSO4 and CuSO4). After a 9-week feeding trial, growth performance, hematological parameters, whole-body proximate composition, and intestinal microbiota were evaluated, and fish were subjected to a bacterial challenge against Edwardsiella ictaluri to evaluate the contribution of the experimental treatments to fish health status. No statistical differences were detected for catfish fed the various diets in terms of production performance or survival after bacterial challenge. The hematocrit and RBC counts from fish fed the diet containing copper nanoparticles were significantly lower than the control group. A higher relative abundance of gram-positive bacteria was found in the digesta of catfish fed diets containing copper nanoparticles. Furthermore, in the context of hematology, iron nanoparticles did not impact the blood parameters of channel catfish; however, reduced hematocrits were observed in fish fed the copper nanoparticle diet, which lacked supplemental dietary iron, thus reinforcing the importance of dietary iron to catfish hematopoiesis. Nonetheless, additional studies are needed to investigate the effects of dietary copper nanoparticle supplementation in catfish diets to better illuminate its effects on the intestinal microbiota.

Diagnosis of external ventricular drainage related infections with real-time 16S PCR and third-generation 16S sequencing

OBJECTIVE

Investigate the performance of real-time 16S PCR and third-generation 16S sequencing in the diagnosis of external ventricular drain related infections (EVDRI).

METHODS

Subjects with suspected EVDRI were prospectively included at Uppsala University Hospital. Subjects were included into three groups: subjects with negative CSF culture with and without antibiotic treatment and subjects with positive CSF culture, respectively. CSF was analysed with real-time 16S PCR and third-generation 16S sequencing. Real-time 16S PCR positivity/negativity and number of 16S sequence reads were compared between groups. For culture positive subjects, species identification in third-generation sequencing and routine culture was compared.

RESULTS

84 subjects were included. There were 18, 44 and 22 subjects in the three groups. Real-time PCR was positive in 17 of 22 subjects in the culture positive group and negative in 61 of the 62 subjects in the two culture negative groups. The sensitivity and specificity for real-time 16S PCR compared to culture was estimated to 77% and 98%, respectively. Species identification in 16S sequencing and culture was concordant in 20 of 22 subjects. The number of 16S sequence reads were significantly higher in the culture positive group than in both culture negative groups (p < 0.001). There was no significant difference in number of 16S sequences between the two culture negative groups.

CONCLUSIONS

Real-time 16S PCR predict culture results with sufficient reliability. Third-generation 16S sequencing could enhance sensitivity and species identification in diagnostics of EVD-related infections. False negative culture results appear to be uncommon in patients with suspected EVDRI.

Phenotypic and genotypic characterization of antimicrobial resistances reveals the effect of the production chain in reducing resistant lactic acid bacteria in an artisanal raw ewe milk PDO cheese

Antimicrobial resistance (AMR) is a significant public health threat, with the food production chain, and, specifically, fermented products, as a potential vehicle for dissemination. However, information about dairy products, especially raw ewe milk cheeses, is limited. The present study analysed, for the first time, the occurrence of AMRs related to lactic acid bacteria (LAB) along a raw ewe milk cheese production chain for the most common antimicrobial agents used on farms (dihydrostreptomycin, benzylpenicillin, amoxicillin and polymyxin B). More than 200 LAB isolates were obtained and identified by Sanger sequencing (V1-V3 16S rRNA regions); these isolates included 8 LAB genera and 21 species. Significant differences in LAB composition were observed throughout the production chain (P ≤ 0.001), with Enterococcus (e.g., E. hirae and E. faecalis) and Bacillus (e.g., B. thuringiensis and B. cereus) predominating in ovine faeces and raw ewe milk, respectively, along with Lactococcus (L. lactis) in whey and fresh cheeses, while Lactobacillus and Lacticaseibacillus species (e.g., Lactobacillus sp. and L. paracasei) prevailed in ripened cheeses. Phenotypically, by broth microdilution, Lactococcus, Enterococcus and Bacillus species presented the greatest resistance rates (on average, 78.2 %, 56.8 % and 53.4 %, respectively), specifically against polymyxin B, and were more susceptible to dihydrostreptomycin. Conversely, Lacticaseibacillus and Lactobacillus were more susceptible to all antimicrobials tested (31.4 % and 39.1 %, respectively). Thus, resistance patterns and multidrug resistance were reduced along the production chain (P ≤ 0.05). Genotypically, through HT-qPCR, 31 antimicrobial resistance genes (ARGs) and 6 mobile genetic elements (MGEs) were detected, predominating Str, StrB and aadA-01, related to aminoglycoside resistance, and the transposons tnpA-02 and tnpA-01. In general, a significant reduction in ARGs and MGEs abundances was also observed throughout the production chain (P ≤ 0.001). The current findings indicate that LAB dynamics throughout the raw ewe milk cheese production chain facilitated a reduction in AMRs, which has not been reported to date.

Comparative evaluation of analytical pipelines for illumina short- and nanopore long-read 16S rRNA gene amplicon sequencing with mock microbial communities

Utility of a recently developed long-read pipeline, Emu, was assessed using an expectation-maximization algorithm for accurate read classification. We compared it to conventional short- and long-read pipelines, using well-characterized mock bacterial samples. Our findings highlight the necessity of appropriate data-processing for taxonomic descriptions, expanding our understanding of the precise microbiome.

A survey of BWT variants for string collections

MOTIVATION

In recent years, the focus of bioinformatics research has moved from individual sequences to collections of sequences. Given the fundamental role of the Burrows-Wheeler Transform (BWT) in string processing, a number of dedicated tools have been developed for computing the BWT of string collections. While the focus has been on improving efficiency, both in space and time, the exact definition of the BWT employed has not been at the center of attention. As we show in this paper, the different tools in use often compute non-equivalent BWT variants: the resulting transforms can differ from each other significantly, including the number r of runs, a central parameter of the BWT. Moreover, with many tools, the transform depends on the input order of the collection. In other words, on the same dataset, the same tool may output different transforms if the dataset is given in a different order.

RESULTS

We studied 18 dedicated tools for computing the BWT of string collections and were able to identify 6 different BWT variants computed by these tools. We review the differences between these BWT variants, both from a theoretical and from a practical point of view, comparing them on 8 real-life biological datasets with different characteristics. We find that the differences can be extensive, depending on the datasets, and are largest on collections of many similar short sequences. The parameter r, the number of runs of the BWT, also shows notable variation between the different BWT variants; on our datasets, it varied by a multiplicative factor of up to 4.2.

AVAILABILITY

Source code and scripts to replicate the results and download the data used in the article are available at https://github.com/davidecenzato/BWT-variants-for-string-collections.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The Third-Generation Sequencing Challenge: Novel Insights for the Omic Sciences

The understanding of the human genome has been greatly improved by the advent of next-generation sequencing technologies (NGS). Despite the undeniable advantages responsible for their widespread diffusion, these methods have some constraints, mainly related to short read length and the need for PCR amplification. As a consequence, long-read sequencers, called third-generation sequencing (TGS), have been developed, promising to overcome NGS. Starting from the first prototype, TGS has progressively ameliorated its chemistries by improving both read length and base-calling accuracy, as well as simultaneously reducing the costs/base. Based on these premises, TGS is showing its potential in many fields, including the analysis of difficult-to-sequence genomic regions, structural variations detection, RNA expression profiling, DNA methylation study, and metagenomic analyses. Protocol standardization and the development of easy-to-use pipelines for data analysis will enhance TGS use, also opening the way for their routine applications in diagnostic contexts.

A comparison between full-length 16S rRNA Oxford nanopore sequencing and Illumina V3-V4 16S rRNA sequencing in head and neck cancer tissues

Describing the microbial community within the tumour has been a key aspect in understanding the pathophysiology of the tumour microenvironment. In head and neck cancer (HNC), most studies on tissue samples have only performed 16S rRNA short-read sequencing (SRS) on V3-V5 region. SRS is mostly limited to genus level identification. In this study, we compared full-length 16S rRNA long-read sequencing (FL-ONT) from Oxford Nanopore Technology (ONT) to V3-V4 Illumina SRS (V3V4-Illumina) in 26 HNC tumour tissues. Further validation was also performed using culture-based methods in 16 bacterial isolates obtained from 4 patients using MALDI-TOF MS. We observed similar alpha diversity indexes between FL-ONT and V3V4-Illumina. However, beta-diversity was significantly different between techniques (PERMANOVA - R2 = 0.131, p < 0.0001). At higher taxonomic levels (Phylum to Family), all metrics were more similar among sequencing techniques, while lower taxonomy displayed more discrepancies. At higher taxonomic levels, correlation in relative abundance from FL-ONT and V3V4-Illumina were higher, while this correlation decreased at lower levels. Finally, FL-ONT was able to identify more isolates at the species level that were identified using MALDI-TOF MS (75% vs. 18.8%). FL-ONT was able to identify lower taxonomic levels at a better resolution as compared to V3V4-Illumina 16S rRNA sequencing.

Improving bacteria identification from digital melt assay via oligonucleotide-based temperature calibration

BACKGROUND

Bacterial infections, especially polymicrobial infections, remain a threat to global health and require advances in diagnostic technologies for timely and accurate identification of all causative species. Digital melt - microfluidic chip-based digital PCR combined with high resolution melt (HRM) - is an emerging method for identification and quantification of polymicrobial bacterial infections. Despite advances in recent years, existing digital melt instrumentation often delivers nonuniform temperatures across digital chips, resulting in nonuniform digital melt curves for individual bacterial species. This nonuniformity can lead to inaccurate species identification and reduce the capacity for differentiating bacterial species with similar digital melt curves.

RESULTS

We introduce herein a new temperature calibration method for digital melt by incorporating an unamplified, synthetic DNA fragment with a known melting temperature as a calibrator. When added at a tuned concentration to an established digital melt assay amplifying the commonly targeted 16S V1 - V6 region, this calibrator produced visible low temperature calibrator melt curves across-chip along with the target bacterial melt curves. This enables alignment of the bacterial melt curves and correction of heating-induced nonuniformities. Using this calibration method, we were able to improve the uniformity of digital melt curves from three causative species of bacteria. Additionally, we assessed calibration's effects on identification accuracy by performing machine learning identification of three polymicrobial mixtures comprised of two bacteria with similar digital melt curves in different ratios. Calibration greatly improved mixture composition prediction.

SIGNIFICANCE

To the best of our knowledge, this work represents the first DNA calibrator-supplemented assay and calibration method for nanoarray digital melt. Our results suggest that this calibration method can be flexibly used to improve identification accuracy and reduce melt curve variabilities across a variety of pathogens and assays. Therefore, this calibration method has the potential to elevate the diagnostic capabilities of digital melt toward polymicrobial bacterial infections and other infectious diseases.

An overview of the bacterial microbiome of public transportation systems-risks, detection, and countermeasures

When we humans travel, our microorganisms come along. These can be harmless but also pathogenic, and are spread by touching surfaces or breathing aerosols in the passenger cabins. As the pandemic with SARS-CoV-2 has shown, those environments display a risk for infection transmission. For a risk reduction, countermeasures such as wearing face masks and distancing were applied in many places, yet had a significant social impact. Nevertheless, the next pandemic will come and additional countermeasures that contribute to the risk reduction are needed to keep commuters safe and reduce the spread of microorganisms and pathogens, but also have as little impact as possible on the daily lives of commuters. This review describes the bacterial microbiome of subways around the world, which is mainly characterized by human-associated genera. We emphasize on healthcare-associated ESKAPE pathogens within public transport, introduce state-of-the art methods to detect common microbes and potential pathogens such as LAMP and next-generation sequencing. Further, we describe and discuss possible countermeasures that could be deployed in public transportation systems, as antimicrobial surfaces or air sterilization using plasma. Commuting in public transport can harbor risks of infection. Improving the safety of travelers can be achieved by effective detection methods, microbial reduction systems, but importantly by hand hygiene and common-sense hygiene guidelines.

Full-length transcriptome profiling of Acanthopanax gracilistylus provides new insight into the kaurenoic acid biosynthesis pathway

Acanthopanax gracilistylus is a deciduous plant in the family Araliaceae, which is commonly used in Chinese herbal medicine, as the root bark has functions of nourishing the liver and kidneys, removing dampness and expelling wind, and strengthening the bones and tendons. Kaurenoic acid (KA) is the main effective substance in the root bark of A. gracilistylus with strong anti-inflammatory effects. To elucidate the KA biosynthesis pathway, second-generation (DNA nanoball) and third-generation (Pacific Biosciences) sequencing were performed to analyze the transcriptomes of the A. gracilistylus leaves, roots, and stems. Among the total 505,880 isoforms, 408,954 were annotated by seven major databases. Sixty isoforms with complete open reading frames encoding 11 key enzymes involved in the KA biosynthesis pathway were identified. Correlation analysis between isoform expression and KA content identified a total of eight key genes. Six key enzyme genes involved in KA biosynthesis were validated by real-time quantitative polymerase chain reaction. Based on the sequence analysis, the spatial structure of ent-kaurene oxidase was modeled, which plays roles in the three continuous oxidations steps of KA biosynthesis. This study greatly enriches the transcriptome data of A. gracilistylus and facilitates further analysis of the function and regulation mechanism of key enzymes in the KA biosynthesis pathway.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-024-01436-7.

Human Papillomavirus Infections and the Role Played by Cervical and Cervico-Vaginal Microbiota-Evidence from Next-Generation Sequencing Studies

This comprehensive review encompasses studies examining changes in the cervical and cervico-vaginal microbiota (CM and CVM) in relation to human papillomavirus (HPV) using next-generation sequencing (NGS) technology. HPV infection remains a prominent global health concern, with a spectrum of manifestations, from benign lesions to life-threatening cervical cancers. The CM and CVM, a unique collection of microorganisms inhabiting the cervix/vagina, has emerged as a critical player in cervical health. Recent research has indicated that disruptions in the CM and CVM, characterized by a decrease in Lactobacillus and the overgrowth of other bacteria, might increase the risk of HPV persistence and the progression of cervical abnormalities. This alteration in the CM or CVM has been linked to a higher likelihood of HPV infection and cervical dysplasia. NGS technology has revolutionized the study of the cervical microbiome, providing insights into microbial diversity, dynamics, and taxonomic classifications. Bacterial 16S rRNA gene sequencing, has proven invaluable in characterizing the cervical microbiome, shedding light on its role in HPV infections and paving the way for more tailored strategies to combat cervical diseases. NGS-based studies offer personalized insights into an individual's cervical microbiome. This knowledge holds promise for the development of novel diagnostic tools, targeted therapies, and preventive interventions for cervix-related conditions, including cervical cancer.

Gut microbiome profiles to exclude the diagnosis of hepatic encephalopathy in patients with cirrhosis

Patients with cirrhosis who have cognitive complaints are presumed to have hepatic encephalopathy (HE), which leads to unwarranted medications while ignoring the underlying disease process causing these complaints. Since neuropsychological testing, the current gold standard for HE diagnosis, is not readily available, an orderable test is needed. We aimed to develop and validate a rapid gut microbiota test to exclude HE and determine stakeholder input on this approach. Stool was collected from two cohorts: a two-center training cohort (n = 305, on/not on HE-related therapy) and a multicenter validation cohort (n = 30, on HE treatment). Stool microbiota was analyzed rapidly using nanopore analysis. Stakeholder (patients and clinicians) needs assessment was evaluated using semi-quantitative questionnaires. In the training cohort, machine learning using neural network identified a 20-species signature that differentiated HE vs no-HE with 84% specificity compared to the gold standard neuropsychological testing. This high specificity persisted regardless of whether patients were on HE-related therapy or not. In the validation cohort, application of this profile led to reevaluation of the HE diagnosis and treatment in > 40% of the patients. This approach was acceptable to patients (Veterans in the validation cohort) and clinician (n = 40 nationwide) stakeholders. We conclude that a machine learning stool signature based on 20 microbial species developed in a training set and validated in a separate multicenter prospective cohort differentiated those with vs. without HE, identified patients misdiagnosed with HE, and was acceptable to patients and clinician stakeholders.

Exploring the impact of oral bacteria remnants on stem cells from the Apical papilla: mineralization potential and inflammatory response

Introduction

Bacterial persistence is considered one of the main causal factors for regenerative endodontic treatment (RET) failure in immature permanent teeth. This interference is claimed to be caused by the interaction of bacteria that reside in the root canal with the stem cells that are one of the essentials for RET. The aim of the study was to investigate whether prolonged exposure of stem cells from the apical papilla (SCAP) to bacterial remnants of Fusobacterium nucleatum, Actinomyces gerensceriae, Slackia exigua, Enterococcus faecalis, Peptostreptococcaceae yurii, commonly found in infected traumatized root canals, and the probiotic bacteria Lactobacillus gasseri and Limosilactobacillus reuteri, can alter SCAP's inflammatory response and mineralization potential.

Methods

To assess the effect of bacterial remnants on SCAP, we used UV-C-inactivated bacteria (as cell wall-associated virulence factors) and bacterial DNA. Histochemical staining using Osteoimage Mineralization Assay and Alizarin Red analysis was performed to study SCAP mineralization, while inflammatory and osteo/odontogenic-related responses of SCAPs were assessed with Multiplex ELISA.

Results

We showed that mineralization promotion was greater with UV C-inactivated bacteria compared to bacterial DNA. Immunofluorescence analysis detected that the early mineralization marker alkaline phosphatase (ALP) was increased by the level of E. coli lipopolysaccharide (LPS) positive control in the case of UV-C-inactivated bacteria; meanwhile, DNA treatment decreased the level of ALP compared to the positive control. SCAP's secretome assessed with Multiplex ELISA showed the upregulation of pro-inflammatory factors IL-6, IL-8, GM-CSF, IL-1b, neurotrophic factor BDNF, and angiogenic factor VEGF, induced by UV-C-killed bacteria.

Discussion

The results suggest that long term stimulation (for 21 days) of SCAP with UV-C-inactivated bacteria stimulate their mineralization and inflammatory response, while DNA influence has no such effect, which opens up new ideas about the nature of RET failure.

Oral microbiome and serological analyses on association of Alzheimer's disease and periodontitis

OBJECTIVE

To investigate the association between Alzheimer's disease (AD) and periodontitis in the aspects of periodontal status, serological markers, and oral microbiome.

MATERIALS AND METHODS

Twenty AD and 20 healthy subjects were enrolled in this age- and gender-matched case-control study. Clinical periodontal parameters and serum biomarkers, including amyloid β42 (Aβ42 ), Tau, phosphorylated Tau (pTau), triglyceride, pro-inflammatory cytokines, and anti-Porphyromonas gingivalis lipopolysaccharide (LPS) antibody were examined. The saliva samples were analyzed for oral microbiome composition.

RESULTS

Alzheimer's disease patients with Clinical Dementia Rating (CDR) ≥1 exhibited significantly more clinical attachment loss (CAL) than those with lower CDR. The levels of serum Tau protein, hsCRP and anti-P. gingivalis LPS antibody were markedly elevated in the AD group compared with the control group. Serum pTau protein level was positively correlated with anti-P. gingivalis LPS antibody titer. Moreover, the increased abundances of Capnocytophaga sp ora clone DZ074, Eubacterium infirmum, Prevotella buccae, and Selenomonas artemidis were detected in the AD group. Interestingly, serum levels of Aβ42, pTau, and anti-P. gingivalis LPS antibody were strongly related to the gene upregulation in human pathogen septicemia.

CONCLUSIONS

Our study suggested the association of periodontal infection and oral microbiome with AD. Further large-scale studies with longitudinal follow-up are warranted.

Antimicrobial Efficacy of Allium cepa and Zingiber officinale Against the Milk-Borne Pathogen Listeria monocytogenes

Listeria monocytogenes is an important food-borne pathogen that causes listeriosis and has a high case fatality rate despite its low incidence. Medicinal plants and their secondary metabolites have been identified as potential antibacterial substances, serving as replacements for synthetic chemical compounds. The present studies emphasize two significant medicinal plants, Allium cepa and Zingiber officinale, and their efficacy against L. monocytogenes. Firstly, a bacterial isolate was obtained from milk and identified through morphology and biochemical reactions. The species of the isolate were further confirmed through 16S rRNA analysis. Furthermore, polar solvents such as methanol and ethanol were used for the extraction of secondary metabolites from A. cepa and Z. officinale. Crude phytochemical components were identified using phytochemical tests, FTIR, and GC-MS. Moreover, the antibacterial activity of the crude extract and its various concentrations were tested against L. monocytogenes. Among all, A. cepa in methanolic extracts showed significant inhibitory activity. Since, the A. cepa for methanolic crude extract was used to perform autography to assess its bactericidal activity. Subsequently, molecular docking was performed to determine the specific compound inhibition. The docking results revealed that four compounds displayed strong binding affinity with the virulence factor Listeriolysin-O of L. monocytogenes. Based on the above results, it can be concluded that the medicinal plant A. cepa has potential antibacterial effects against L. monocytogenes, particularly targeting its virulence.

The newest Oxford Nanopore R10.4.1 full-length 16S rRNA sequencing enables the accurate resolution of species-level microbial community profiling

The long-read amplicon provides a species-level solution for the community. With the improvement of nanopore flowcells, the accuracy of Oxford Nanopore Technologies (ONT) R10.4.1 has been substantially enhanced, with an average of approximately 99%. To evaluate its effectiveness on amplicons, three types of microbiomes were analyzed by 16S ribosomal RNA (hereinafter referred to as "16S") amplicon sequencing using Novaseq, Pacbio sequel II, and Nanopore PromethION platforms (R9.4.1 and R10.4.1) in the current study. We showed the error rate, recall, precision, and bias index in the mock sample. The error rate of ONT R10.4.1 was greatly reduced, with a better recall in the case of the synthetic community. Meanwhile, in different types of environmental samples, ONT R10.4.1 analysis resulted in a composition similar to Pacbio data. We found that classification tools and databases influence ONT data. Based on these results, we conclude that the ONT R10.4.1 16S amplicon can also be used for application in environmental samples. IMPORTANCE The long-read amplicon supplies the community with a species-level solution. Due to the high error rate of nanopore sequencing early on, it has not been frequently used in 16S studies. Oxford Nanopore Technologies (ONT) introduced the R10.4.1 flowcell with Q20+ reagent to achieve more than 99% accuracy as sequencing technology advanced. However, there has been no published study on the performance of commercial PromethION sequencers with R10.4.1 flowcells on 16S sequencing or on the impact of accuracy improvement on taxonomy (R9.4.1 to R10.4.1) using 16S ONT data. In this study, three types of microbiomes were investigated by 16S ribosomal RNA (rRNA) amplicon sequencing using Novaseq, Pacbio sequel II, and Nanopore PromethION platforms (R9.4.1 and R10.4.1). In the mock sample, we displayed the error rate, recall, precision, and bias index. We observed that the error rate in ONT R10.4.1 is significantly lower, especially when deletions are involved. First and foremost, R10.4.1 and Pacific Bioscience platforms reveal a similar microbiome in environmental samples. This study shows that the R10.4.1 full-length 16S rRNA sequences allow for species identification of environmental microbiota.

Fecal bacterial microbiota in constipated patients before and after eight weeks of daily Bifidobacterium infantis 35624 administration

INTRODUCTION AND AIM

In recent years, probiotics have been used in functional gastrointestinal disorders, including chronic constipation (CC). The effect of Bifidobacterium infantis strain 35624 on the gut microbiota of CC patients has not been previously studied. Our aim was to analyze the fecal microbiota of constipated patients, before and after consuming a single-strain probiotic (B. infantis strain 35624).

MATERIALS AND METHODS

We used 16S rRNA gene high-throughput sequencing to analyze the fecal microbiota of female patients (n=13) with CC. Patients were instructed to ingest one capsule of Alflorex® (containing 1×109 CFUs/g B. infantis strain 35624) daily for eight weeks. Fecal samples were obtained at the baseline and end (final) of probiotic administration.

RESULTS

Alpha diversity metrics did not differ between the baseline and final periods. The butyrate producer, Oscillospira, was the taxon most strongly correlated with amplicon sequence variants (R2=0.55, p<0.0001). Except for a few bacterial taxa, there were no significant differences in relative abundance between the baseline and final periods. Beta-diversity measures also showed limited evidence for the differences between the two time periods.

CONCLUSIONS

The results suggest that the fecal bacterial microbiota remains stable in constipated women consuming a single-strain probiotic. Those findings may be helpful in better understanding probiotic functioning in patients with digestive disorders.

Oral and Gut Microbiota Dysbiosis is Associated with Mucositis Severity in Autologous Hematopoietic Stem Cell Transplantation: Evidence from an Asian Population

Mucositis is a debilitating complication of hematopoietic stem cell transplantation (HSCT). It is unclear how changes in the composition of microbiota, which are modulated by geographical location and ethnicity, may influence immune regulation leading to the development of mucositis, and the study of both oral and gut microbiota in a single population of autologous HSCT in the Asian region is lacking. The present study aimed to characterize the oral and gut microbiota changes, and the impact on both oral and lower gastrointestinal (GI) mucositis, with associated temporal changes in a population of adult recipients of autologous HSCT. Autologous HSCT recipients age ≥18 years were recruited from Hospital Ampang, Malaysia, between April 2019 and December 2020. Mucositis assessments were conducted daily, and blood, saliva, and fecal samples were collected prior to conditioning, on day 0, and at 7 days and 6 months post-transplantation. Longitudinal differences in alpha diversity and beta diversity were determined using the Wilcoxon signed-rank test and permutational multivariate analysis of variance, respectively. Changes in relative abundances of bacteria across time points were assessed using the microbiome multivariate analysis by linear models function. The combined longitudinal effects of clinical, inflammatory, and microbiota variables on mucositis severity were measured using the generalized estimating equation. Among the 96 patients analyzed, oral mucositis and diarrhea (representing lower GI mucositis) occurred in 58.3% and 95.8%, respectively. Alpha and beta diversities were significantly different between sample types (P < .001) and across time points, with alpha diversity reaching statistical significance at day 0 in fecal samples (P < .001) and at day +7 in saliva samples (P < .001). Diversities normalized to baseline by 6 months post-transplantation. Significant microbiota, clinical, and immunologic factors were associated with increasing mucositis grades. Increasing relative abundances of saliva Paludibacter, Leuconostoc, and Proteus were associated with higher oral mucositis grades, whereas increasing relative abundances of fecal Rothia and Parabacteroides were associated with higher GI mucositis grades. Meanwhile, increasing relative abundances of saliva Lactococcus and Acidaminococcus and fecal Bifidobacterium were associated with protective effects against worsening oral and GI mucositis grades, respectively. This study provides real-world evidence and insights into the dysbiosis of the microbiota in patients exposed to conditioning regimen during HSCT. Independent of clinical and immunologic factors, we demonstrated significant associations between relative bacteria abundances with the increasing severity of oral and lower GI mucositis. Our findings offer a potential rationale to consider the inclusion of preventive and restorative measures targeting oral and lower GI dysbiosis as interventional strategies to ameliorate mucositis outcome in HSCT recipients.

Expanding success in the isolation of abundant marine bacteria after reduction in grazing and viral pressure and increase in nutrient availability

Isolation of microorganisms is a useful approach to gathering knowledge about their genomic properties, physiology, and ecology, in addition to allowing the characterization of novel taxa. We performed an extensive isolation effort on samples from seawater manipulation experiments that were carried out during the four astronomical seasons in a coastal site of the northwest Mediterranean to evaluate the impact of grazing, viral mortality, resource competition reduction, and light presence/absence on bacterioplankton growth. Isolates were retrieved using two growth media, and their full 16S rRNA gene was sequenced to assess their identity and calculate their culturability across seasons and experimental conditions. A total of 1,643 isolates were obtained, mainly affiliated to the classes Gammaproteobacteria (44%), Alphaproteobacteria (26%), and Bacteroidia (17%). Isolates pertaining to class Gammaproteobacteria were the most abundant in all experiments, while Bacteroidia were preferentially enriched in the treatments with reduced grazing. Sixty-one isolates had a similarity below 97% to cultured taxa and are thus putatively novel. Comparison of isolate sequences with 16S rRNA gene amplicon sequences from the same samples showed that the percentage of reads corresponding to isolates was 21.4% within the whole data set, with dramatic increases in the summer virus-reduced (71%) and diluted (47%) treatments. In fact, we were able to isolate the top 10 abundant taxa in several experiments and from the whole data set. We also show that top-down and bottom-up controls differentially affect taxa in terms of culturability. Our results indicate that culturing marine bacteria using agar plates can be successful in certain ecological situations. IMPORTANCE Bottom-up and top-down controls greatly influence marine microbial community composition and dynamics, which in turn have effects on their culturability. We isolated a high amount of heterotrophic bacterial strains from experiments where seawater environmental conditions had been manipulated and found that decreasing grazing and viral pressure as well as rising nutrient availability are key factors increasing the success in culturing marine bacteria. Our data hint at factors influencing culturability and underpin bacterial cultures as a powerful way to discover new taxa.

Detection of the Microbial Composition of Some Commercial Fermented Liquid Products via Metagenomic Analysis

The fermented liquid sector is developing all over the world due to its contribution to health. Our study has contributed to the debate about whether industrially manufactured fermented liquids live up to their claims by analyzing pathogens and beneficial bacteria using a 16S rRNA sequencing technique called metagenomic analysis. Paenibacillus, Lentibacillus, Bacillus, Enterococcus, Levilactobacillus, and Oenococcus were the most abundant bacterial genera observed as potential probiotics. Pseudomonas stutzeri, Acinetobacter, and Collimonas, which have plant-growth-promoting traits, were also detected. The fact that we encounter biocontroller bacteria that promote plant growth demonstrates that these organisms are widely used in foods and emphasizes the necessity of evaluating them in terms of public health. Their potential applications in agriculture may pose a danger to food hygiene and human health in the long term, so our data suggest that this should be evaluated.

CuReSim-LoRM: A Tool to Simulate Metabarcoding Long Reads

Metabarcoding DNA sequencing has revolutionized the study of microbial communities. Third-generation sequencing producing long reads had opened up new perspectives. Obtaining the full-length ribosomal RNA gene would permit one to reach a better taxonomic resolution at the species or the strain level. However, Oxford Nanopore Technologies (ONT) sequencing produces reads with high error rates, which introduces biases in analysis. Understanding the biases introduced during the analysis allows one to better interpret the biological results and take care of conclusions drawn from metabarcoding experiments. To benchmark an analysis process, the ground truth, i.e., the real composition of the microbial community, has to be known. In addition to artificial mock communities, simulated data are often used to evaluate the biases and performances of the bioinformatics analysis step. Currently, no specific tool has been developed to simulate metabarcoding long reads, mimic the error rate and the length distribution, and allow one to benchmark the analysis process. Here, we introduce CuReSim-LoRM, for the customized read simulator to generate long reads for metabarcoding. We showed that CuReSim-LoRM is able to produce reads with varying error rates and length distributions by mimicking the real data very well.

Concatenated 16S rRNA sequence analysis improves bacterial taxonomy

Background: Microscopic, biochemical, molecular, and computer-based approaches are extensively used to identify and classify bacterial populations. Advances in DNA sequencing and bioinformatics workflows have facilitated sophisticated genome-based methods for microbial taxonomy although sequencing of the 16S rRNA gene is widely employed to identify and classify bacterial communities as a cost-effective and single-gene approach. However, the 16S rRNA sequence-based species identification accuracy is limited because of the occurrence of multiple copies of the 16S rRNA gene and higher sequence identity between closely related species. The availability of the genomes of several bacterial species provided an opportunity to develop comprehensive species-specific 16S rRNA reference libraries. Methods: Sequences of the 16S rRNA genes were retrieved from the whole genomes available in the Genome databases. With defined criteria, four 16S rRNA gene copy variants were concatenated to develop a species-specific reference library. The sequence similarity search was performed with a web-based BLAST program, and MEGA software was used to construct the phylogenetic tree. Results: Using this approach, species-specific 16S rRNA gene libraries were developed for four closely related  Streptococcus species ( S. gordonii,  S. mitis,  S. oralis, and  S. pneumoniae). Sequence similarity and phylogenetic analysis using concatenated 16S rRNA copies yielded better resolution than single gene copy approaches. Conclusions: The approach is very effective in classifying genetically closely related bacterial species and may reduce misclassification of bacterial species and genome assemblies.

Deciphering the functional diversity of the gut microbiota of the black soldier fly (Hermetia illucens): recent advances and future challenges

Bioconversion using insects is a promising strategy to convert organic waste (catering leftovers, harvest waste, food processing byproducts, etc.) into biomass that can be used for multiple applications, turned into high added-value products, and address environmental, societal and economic concerns. Due to its ability to feed on a tremendous variety of organic wastes, the black soldier fly (Hermetia illucens) has recently emerged as a promising insect for bioconversion of organic wastes on an industrial scale. A growing number of studies have highlighted the pivotal role of the gut microbiota in the performance and health of this insect species. This review aims to provide a critical overview of current knowledge regarding the functional diversity of the gut microbiota of H. illucens, highlighting its importance for bioconversion, food safety and the development of new biotechnological tools. After providing an overview of the different strategies that have been used to outline the microbial communities of H. illucens, we discuss the diversity of these gut microbes and the beneficial services they can provide to their insect host. Emphasis is placed on technical strategies and aspects of host biology that require special attention in the near future of research. We also argue that the singular digestive capabilities and complex gut microbiota of H. illucens make this insect species a valuable model for addressing fundamental questions regarding the interactions that insects have evolved with microorganisms. By proposing new avenues of research, this review aims to stimulate research on the microbiota of a promising insect to address the challenges of bioconversion, but also fundamental questions regarding bacterial symbiosis in insects.

Machine learning-based detection of adventitious microbes in T-cell therapy cultures using long-read sequencing

Assuring that cell therapy products are safe before releasing them for use in patients is critical. Currently, compendial sterility testing for bacteria and fungi can take 7-14 days. The goal of this work was to develop a rapid untargeted approach for the sensitive detection of microbial contaminants at low abundance from low volume samples during the manufacturing process of cell therapies. We developed a long-read sequencing methodology using Oxford Nanopore Technologies MinION platform with 16S and 18S amplicon sequencing to detect USP <71> organisms and other microbial species. Reads are classified metagenomically to predict the microbial species. We used an extreme gradient boosting machine learning algorithm (XGBoost) to first assess if a sample is contaminated, and second, determine whether the predicted contaminant is correctly classified or misclassified. The model was used to make a final decision on the sterility status of the input sample. An optimized experimental and bioinformatics pipeline starting from spiked species through to sequenced reads allowed for the detection of microbial samples at 10 colony-forming units (CFU)/mL using metagenomic classification. Machine learning can be coupled with long-read sequencing to detect and identify sample sterility status and microbial species present in T-cell cultures, including the USP <71> organisms to 10 CFU/mL. IMPORTANCE This research presents a novel method for rapidly and accurately detecting microbial contaminants in cell therapy products, which is essential for ensuring patient safety. Traditional testing methods are time-consuming, taking 7-14 days, while our approach can significantly reduce this time. By combining advanced long-read nanopore sequencing techniques and machine learning, we can effectively identify the presence and types of microbial contaminants at low abundance levels. This breakthrough has the potential to improve the safety and efficiency of cell therapy manufacturing, leading to better patient outcomes and a more streamlined production process.

A Review on Microbial Species for Forensic Body Fluid Identification in Healthy and Diseased Humans

Microbial communities present in body fluids can assist in distinguishing between types of body fluids. Metagenomic studies have reported bacterial genera which are core to specific body fluids and are greatly influenced by geographical location and ethnicity. Bacteria in body fluids could also be due to bacterial infection; hence, it would be worthwhile taking into consideration bacterial species associated with diseases. The present review reports bacterial species characteristic of diseased and healthy body fluids across geographical locations, and bacteria described in forensic studies, with the aim of collating a set of bacteria to serve as the core species-specific markers for forensic body fluid identification. The most widely reported saliva-specific bacterial species are Streptococcus salivarius, Prevotella melaninogenica, Neisseria flavescens, with Fusobacterium nucleatum associated with increased diseased state. Lactobacillus crispatus and Lactobacillus iners are frequently dominant in the vaginal microbiome of healthy women. Atopobium vaginae, Prevotella bivia, and Gardnerella vaginalis are more prevalent in women with bacterial vaginosis. Semen and urine-specific bacteria at species level have not been reported, and menstrual blood bacteria are indistinguishable from vaginal fluid. Targeting more than one bacterial species is recommended for accurate body fluid identification. Although metagenomic sequencing provides information of a broad microbial profile, the specific bacterial species could be used to design biosensors for rapid body fluid identification. Validation of microbial typing methods and its application in identifying body fluids in a mixed sample would allow regular use of microbial profiling in a forensic workflow.

Single-cell RNA sequencing for the study of kidney disease

The kidney is an important organ for maintaining normal metabolism and stabilising the internal environment, in which, the heterogeneity of cell types has hindered the progress in understanding the mechanisms underlying kidney disease. In recent years the application of single-cell RNA sequencing (scRNA-seq) in nephrology has developed rapidly. In this review, we summarized the technical platform related to scRNA-seq and the role of this technology in investigating the onset and development of kidney diseases, starting from several common kidney diseases (mainly including lupus nephritis, renal cell carcinoma, diabetic nephropathy and acute kidney injury), and provide a reference for the application of scRNA-seq in the study of kidney disease diagnosis, treatment and prognosis.

Comparison of Oxford Nanopore Technologies and Illumina MiSeq sequencing with mock communities and agricultural soil

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.

Differences in the composition of the bacterial element of the urinary tract microbiome in patients undergoing dialysis and patients after kidney transplantation

Introduction

The development of molecular biology methods and their application in microbial research allowed the detection of many new pathogens that cause urinary tract infections (UTIs). Despite the advances of using new research techniques, the etiopathogenesis of UTIs, especially in patients undergoing dialysis and patients after kidney transplantation, is still not fully understood.

Methods

This study aimed to characterize and compare the composition of the bacterial element of the urinary tract microbiome between the groups of patients undergoing dialysis (n = 50) and patients after kidney transplantation (n = 50), with positive or negative urine culture, compared to healthy individuals (n = 50).

Results

Asymptomatic bacteriuria was observed in 30% of the urine cultures of patients undergoing dialysis and patients after kidney transplantation, with Escherichia coli as the most dominant microorganism (73%) detected with the use of classical microbiology techniques. However, differences in the bacterial composition of the urine samples between the evaluated patient groups were demonstrated using the amplicon sequencing. Finegoldia, Leptotrichia, and Corynebacterium were found to be discriminative bacteria genera in patients after dialysis and kidney transplantation compared to the control group. In addition, in all of urine samples, including those without bacteriuria in classical urine culture, many types of bacteria have been identified using 16S rRNA sequencing.

Discussion

The revealed microbial characteristics may form the basis in searching for new diagnostic markers in treatment of patients undergoing dialysis and patients after kidney transplantation.

The use of different 16S rRNA gene variable regions in biogeographical studies

16S rRNA gene amplicon sequencing is routinely used in environmental surveys to identify microbial diversity and composition of the samples of interest. The dominant sequencing technology of the past decade (Illumina) is based on the sequencing of 16S rRNA hypervariable regions. Online sequence data repositories, which represent an invaluable resource for investigating microbial distributional patterns across spatial, environmental or temporal scales, contain amplicon datasets from diverse 16S rRNA gene variable regions. However, the utility of these sequence datasets is potentially reduced by the use of different 16S rRNA gene amplified regions. By comparing 10 Antarctic soil samples sequenced for five different 16S rRNA amplicons, we explore whether sequence data derived from diverse 16S rRNA variable regions can be validly used as a resource for biogeographical studies. Patterns of shared and unique taxa differed among samples as a result of variable taxonomic resolutions of the assessed 16S rRNA variable regions. However, our analyses also suggest that the use of multi-primer datasets for biogeographical studies of the domain Bacteria is a valid approach to explore bacterial biogeographical patterns due to the preservation of bacterial taxonomic and diversity patterns across different variable region datasets. We deem composite datasets useful for biogeographical studies.

The Role of Gut Microbiota in the Clinical Outcome of Septic Patients: State of the Art and Future Perspectives

Sepsis is a life-threatening multiple-organ dysfunction caused by a dysregulated host response to infection, with high mortality worldwide; 11 million deaths per year are attributable to sepsis in high-income countries. Several research groups have reported that septic patients display a dysbiotic gut microbiota, often related to high mortality. Based on current knowledge, in this narrative review, we revised original articles, clinical trials, and pilot studies to evaluate the beneficial effect of gut microbiota manipulation in clinical practice, starting from an early diagnosis of sepsis and an in-depth analysis of gut microbiota.

Gut microbiome profiling of neonates using Nanopore MinION and Illumina MiSeq sequencing

This study aimed to evaluate the difference in gut microbiomes between preterm and term infants using third-generation long-read sequencing (Oxford Nanopore Technologies, ONT) compared with an established gold standard, Illumina (second-generation short-read sequencing). A total of 69 fecal samples from 51 term (T) and preterm (P) infants were collected at 7 and 28 days of life. Gut colonization profiling was performed by 16S rRNA gene sequencing using ONT. We used Illumina to validate and compare the patterns in 13 neonates. Using bioinformatic analysis, we identified features that differed between P and T. Both T1 and P1 microbiomes were dominated by Firmicutes (Staphylococcus and Enterococcus), whereas sequentially showed dominant transitions to Lactobacillus (p < 0.001) and Streptococcus in T2 (p = 0.001), and pathogenic bacteria (Klebsiella) in P2 (p = 0.001). The abundance of beneficial bacteria (Bifidobacterium and Lactobacillus) increased in T2 (p = 0.026 and p < 0.001, respectively). These assignments were correlated with the abundance at the species-level. Bacterial α-diversity increased in T (p = 0.005) but not in P (p = 0.156), and P2 showed distinct β-diversity clustering than T2 (p = 0.001). The ONT reliably identified pathogenic bacteria at the genus level, and taxonomic profiles were comparable to those identified by Illumina at the genus level. This study shows that ONT and Illumina are highly correlated. P and T had different microbiome profiles, and the α- and β-diversity varied. ONT sequencing has potential for pathogen detection in neonates in clinical settings.

SituSeq: an offline protocol for rapid and remote Nanopore 16S rRNA amplicon sequence analysis

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 Is Preferable over Illumina for 16S Amplicon Sequencing of the Gut Microbiota When Species-Level Taxonomic Classification, Accurate Estimation of Richness, or Focus on Rare Taxa Is Required

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.

Performance evaluation of whole genome metagenomics sequencing with the MinION nanopore sequencer: Microbial community analysis and antimicrobial resistance gene detection

Recently, the human gut microbiota has been implicated in various diseases such as immunological and neuropsychiatric disorders, and comprehensive gut microbiota analysis by metagenomic analysis using next-generation sequencers has been attracting attention. In this study, we compared microbial communities of 16S rDNA metagenome sequencing (16S-meta) and whole genome metagenome sequencing (WG-meta) using the nanopore sequencer MinION and 16S-meta using the Illumina Miseq sequencer with simulated and fecal samples, and evaluated the ability of WG-meta to detect antimicrobial resistance genes. We used the commercial Microbial Community DNA Standard as the DNA standard and a simulated sample comprising 17 strains of 15 bacterial species. In the detection of antimicrobial resistance genes, we used a simulated sample and spiked fecal samples containing Escherichia coli carrying bla_CTX-M-27, Klebsiella pneumoniae carrying bla_OXA-48, and Staphylococcus aureus carrying mecA. WG-meta using MinION was superior to 16S-meta and could accurately analyze the microbial communities at the species level, but it underestimated or misidentified the Bacillus subtilis group, Cryptococcus neoformans, Shigella sonnei, and Campylobacter jejuni. WG-meta using MinION could analyze the microbial communities in 5 min, and antimicrobial resistance gene detection using WG-meta could be performed in >30 min in the simulated sample with fewer bacterial counts.

Identification of microbial community in the urban environment: The concordance between conventional culture and nanopore 16S rRNA sequencing

Introduction

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.

Methods

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.

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.

Discussion

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.

Tool and techniques study to plant microbiome current understanding and future needs: an overview

Microorganisms are present in the universe and they play role in beneficial and harmful to human life, society, and environments. Plant microbiome is a broad term in which microbes are present in the rhizo, phyllo, or endophytic region and play several beneficial and harmful roles with the plant. To know of these microorganisms, it is essential to be able to isolate purification and identify them quickly under laboratory conditions. So, to improve the microbial study, several tools and techniques such as microscopy, rRNA, or rDNA sequencing, fingerprinting, probing, clone libraries, chips, and metagenomics have been developed. The major benefits of these techniques are the identification of microbial community through direct analysis as well as it can apply in situ. Without tools and techniques, we cannot understand the roles of microbiomes. This review explains the tools and their roles in the understanding of microbiomes and their ecological diversity in environments.

The continuing evolution of barcode applications: Functional toxicology to cell lineage

DNA barcoding is a method to identify biological entities, including individual cells, tissues, organs, or species, by unique DNA sequences. With the advent of next generation sequencing (NGS), there has been an exponential increase in data acquisition pertaining to medical diagnosis, genetics, toxicology, ecology, cancer, and developmental biology. While barcoding first gained wide access in identifying species, signature tagged mutagenesis has been useful in elucidating gene function, particularly in microbes. With the advent of CRISPR/CAS9, methodology to profile eukaryotic genes has made a broad impact in toxicology and cancer biology. Designed homing guide RNAs (hgRNAs) that self-target DNA sequences facilitate cell lineage barcoding by introducing stochastic mutations within cell identifiers. While each of these applications has their limitations, the potential of sequence barcoding has yet to be realized. This review will focus on signature-tagged mutagenesis and briefly discuss the history of barcoding, experimental problems, novel detection methods, and future directions.

Nanopore Electrochemistry for Pathogen Detection

Pathogen infections have seriously threatened human health, and there is an urgent demand for rapid and efficient pathogen identification to provide instructions in clinical diagnosis and therapeutic intervention. Recently, nanopore technology, a rapidly maturing technology which delivers ultrasensitive sensing and high throughput in real-time and at low cost, has achieved success in pathogen detection. Furthermore, the remarkable development of nanopore sequencing, for example, the MinION sequencer from Oxford Nanopore Technologies (ONT) as a competitive sequencing technology, has facilitated the rapid analysis of disease-related microbiomes at the whole-genome level and on a large scale. Here, we highlighted recent advances in nanopore approaches for pathogen detection at the single-molecule level. We also overviewed the applications of nanopore sequencing in pathogenic bacteria identification and diagnosis. In the end, we discussed the challenges and future developments of nanopore technology as promising tools for the management of infections, which may be helpful to aid understanding as well as decision-making.

Oral Microbiome in Orthodontic Acrylic Retainer

The oral microbiome can be shifted if the patients wear the acrylic retainers for a lengthy period. It is essential to understand the components of the plaque in order to forestall the development of dental caries and gingivitis. The aim of this study is to report the bacterial communities that adhere to the acrylic retainers by full-length nanopore 16S sequencing. Six healthy participants were allocated into 2 groups (chemical tablet and brushing groups). Plaque samples were collected from the acrylic retainer surfaces before and after cleaning. The bacterial communities were reported using full-length nanopore 16S sequencing. The results showed that 7 distinct phyla were identified by sequencing. The most prevalent of these was the Firmicutes. We found a total of 72 genera. The most common microorganism across all samples was Streptococcus, followed by Neisseria, Rothia, and Gemella. The beta diversity showed a significant difference between before and after cleaning (p < 0.05). This study revealed the novel finding that a combination of chemical and mechanical cleaning methods was the most effective method of eliminating retainer biofilms. Moreover, retainer cleaning tablets did not alter the homeostatic balance of the bacterial communities adhering to the acrylic retainers.

Characteristics of Microbial Distribution in Different Oral Niches of Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma (OSCC), one of the most common malignant tumors of the head and neck, is closely associated with the presence of oral microbes. However, the microbiomes of different oral niches in OSCC patients and their association with OSCC have not been adequately characterized. In this study, 305 samples were collected from 65 OSCC patients, including tumor tissue, adjacent normal tissue (paracancerous tissue), cancer surface tissue, anatomically matched contralateral normal mucosa, saliva, and tongue coat. 16S ribosomal DNA (16S rDNA) sequencing was used to compare the microbial composition, distribution, and co-occurrence network of different oral niches. The association between the microbiome and the clinical features of OSCC was also characterized. The oral microbiome of OSCC patients showed a regular ecological distribution. Tumor and paracancerous tissues were more microbially diverse than other oral niches. Cancer surface, contralateral normal mucosa, saliva, and tongue coat showed similar microbial compositions, especially the contralateral normal mucosa and saliva. Periodontitis-associated bacteria of the genera Fusobacterium, Prevotella, Porphyromonas, Campylobacter, and Aggregatibacter, and anaerobic bacteria were enriched in tumor samples. The microbiome was highly correlated with tumor clinicopathological features, with several genera (Lautropia, Asteroleplasma, Parvimonas, Peptostreptococcus, Pyramidobacter, Roseburia, and Propionibacterium) demonstrating a relatively high diagnostic power for OSCC metastasis, potentially providing an indicator for the development of OSCC.

Ecosystem-specific microbiota and microbiome databases in the era of big data

The rapid development of sequencing methods over the past decades has accelerated both the potential scope and depth of microbiota and microbiome studies. Recent developments in the field have been marked by an expansion away from purely categorical studies towards a greater investigation of community functionality. As in-depth genomic and environmental coverage is often distributed unequally across major taxa and ecosystems, it can be difficult to identify or substantiate relationships within microbial communities. Generic databases containing datasets from diverse ecosystems have opened a new era of data accessibility despite costs in terms of data quality and heterogeneity. This challenge is readily embodied in the integration of meta-omics data alongside habitat-specific standards which help contextualise datasets both in terms of sample processing and background within the ecosystem. A special case of large genomic repositories, ecosystem-specific databases (ES-DB's), have emerged to consolidate and better standardise sample processing and analysis protocols around individual ecosystems under study, allowing independent studies to produce comparable datasets. Here, we provide a comprehensive review of this emerging tool for microbial community analysis in relation to current trends in the field. We focus on the factors leading to the formation of ES-DB's, their comparison to traditional microbial databases, the potential for ES-DB integration with meta-omics platforms, as well as inherent limitations in the applicability of ES-DB's.

Emu: species-level microbial community profiling of full-length 16S rRNA Oxford Nanopore sequencing data

16S ribosomal RNA-based analysis is the established standard for elucidating the composition of microbial communities. While short-read 16S rRNA analyses are largely confined to genus-level resolution at best, given that only a portion of the gene is sequenced, full-length 16S rRNA gene amplicon sequences have the potential to provide species-level accuracy. However, existing taxonomic identification algorithms are not optimized for the increased read length and error rate often observed in long-read data. Here we present Emu, an approach that uses an expectation-maximization algorithm to generate taxonomic abundance profiles from full-length 16S rRNA reads. Results produced from simulated datasets and mock communities show that Emu is capable of accurate microbial community profiling while obtaining fewer false positives and false negatives than alternative methods. Additionally, we illustrate a real-world application of Emu by comparing clinical sample composition estimates generated by an established whole-genome shotgun sequencing workflow with those returned by full-length 16S rRNA gene sequences processed with Emu.

Metagenomics: A Tool for Exploring Key Microbiome With the Potentials for Improving Sustainable Agriculture

Microorganisms are immense in nature and exist in every imaginable ecological niche, performing a wide range of metabolic processes. Unfortunately, using traditional microbiological methods, most microorganisms remain unculturable. The emergence of metagenomics has resolved the challenge of capturing the entire microbial community in an environmental sample by enabling the analysis of whole genomes without requiring culturing. Metagenomics as a non-culture approach encompasses a greater amount of genetic information than traditional approaches. The plant root-associated microbial community is essential for plant growth and development, hence the interactions between microorganisms, soil, and plants is essential to understand and improve crop yields in rural and urban agriculture. Although some of these microorganisms are currently unculturable in the laboratory, metagenomic techniques may nevertheless be used to identify the microorganisms and their functional traits. A detailed understanding of these organisms and their interactions should facilitate an improvement of plant growth and sustainable crop production in soil and soilless agriculture. Therefore, the objective of this review is to provide insights into metagenomic techniques to study plant root-associated microbiota and microbial ecology. In addition, the different DNA-based techniques and their role in elaborating plant microbiomes are discussed. As an understanding of these microorganisms and their biotechnological potentials are unlocked through metagenomics, they can be used to develop new, useful and unique bio-fertilizers and bio-pesticides that are not harmful to the environment.

Phenotypic and molecular characterization of the causative agents of edwardsiellosis causing Nile tilapia (Oreochromis niloticus) summer mortalities

Edwardsiellosis is a serious bacterial disease affecting Nile tilapia (Oreochromis niloticus), causing septicemia and mortalities. Edwardsiella tarda and Edwardsiella anguillarum were isolated from Nile tilapia summer mortality events in Egypt. Diseased fish showed hemorrhagic septicemia, skin erosions, and eye opacity. A total of 24 Edwardsiella spp. isolates were retrieved from the investigated fish specimens. Phenotypic and biochemical characteristics grouped isolates into typical Ed. tarda (n = 14 strains) and atypical Ed. tarda (n = 10 strains). The BLAST analysis of sodB gene sequencing confirmed the conventional identification of typical Ed. tarda strains (n = 14) and reidentified all the atypical strains (n = 10) as Ed. anguillarum. Isolates showed a combination of virulence factors, including biofilm formation (66.6%), hemolysis (100%), chondroitinase (50%), and proteolytic activity (20.8%). The major part of isolates showed high resistance to ampicillin, amoxicillin, gentamycin antibiotics and harbored tetA, bla_CTX-M, and aadA1 resistance genes. Pathogenicity testing of isolates in O. niloticus confirmed their virulence. Challenged fish exhibited septicemic signs similar to naturally diseased fish. Infections in naturally infected tilapia triggered acute and chronic histopathological alterations. Degenerative and necrotic changes were noticed in hematopoietic organs. Granulomas were noticed in between the hepatic parenchyma. The data extracted from the study confirm that accurate identification of the causative agents of edwardsiellosis should be reliant on genetic-based approaches. Analysis of the bacterium virulence properties offers insights into establishing novel therapeutics for edwardsiellosis control. The findings refer to the need for antimicrobial sensitivity testing to minimize antimicrobial resistance and increase therapy efficacy.

16S rRNA nanopore sequencing for the diagnosis of ocular infection: a feasibility study

Objective

We conducted a feasibility study to verify the effectiveness of 16S ribosomal RNA (rRNA) gene analysis using the nanopore sequencer MinION for identifying causative bacteria in several types of ocular infections.

Methods and Analysis

Four cases of corneal ulcers, one case of endophthalmitis and one case of a conjunctival abscess were included in this study. DNA was extracted from corneal scraping, vitreous samples and secretions from the conjunctival abscess. We conducted 16S rRNA gene amplicon sequencing using MinION and metagenomic DNA analysis. The efficacy of bacterial identification was verified by comparing the conventional culture method with smear observations.

Results

16S rRNA gene sequencing analysis with MinION identified the causative organisms promptly with high accuracy in approximately 4 hours, from ophthalmic specimens. The results of the conventional culture method and 16S rRNA gene sequencing were consistent in all cases. In four of the six cases, a greater variety of organisms was found in the 16S rRNA gene analysis than in bacterial culture.

Conclusion

Using our workflow, 16S rRNA gene analysis using MinION enabled rapid and accurate identification possible in various kinds of bacterial ocular infections.

A Potential Predictive Role of the Scalp Microbiome Profiling in Patients with Alopecia Areata: Staphylococcus caprae, Corynebacterium, and Cutibacterium Species

Little is known about the scalp bacterial composition of alopecia areata (AA) patients. The aim of this study was to investigate the differences in the scalp microbiome of AA patients according to their prognosis, in addition to healthy controls. A total of 33 AA patients and 12 healthy controls (HC) were included in this study. The microbiomes were characterized by sequencing 16S rRNA genes on the Illumina MiSeq platform. The scalp microbiome was more diverse in AA patients compared to HC, but not significantly different according to the severity of AA. Nevertheless, the higher proportion of Corynebacterium species and the lower proportion of Staphylococcus caprae among the Staphylococcus species were noticed in severe AA patients compared to HC or mild AA. The higher ratio of Cutibacterium species to S. caprae was noticed in severe AA. We highlight the potential predictive role of scalp microbiome profiling to a worse prognosis of patients with alopecia areata.

Bugs in Bugs: The Role of Probiotics and Prebiotics in Maintenance of Health in Mass-Reared Insects

Interactions between insects and their microbiota affect insect behaviour and evolution. When specific microorganisms are provided as a dietary supplement, insect reproduction, food conversion and growth are enhanced and health is improved in cases of nutritional deficiency or pathogen infection. The purpose of this review is to provide an overview of insect-microbiota interactions, to review the role of probiotics, their general use in insects reared for food and feed, and their interactions with the host microbiota. We review how bacterial strains have been selected for insect species reared for food and feed and discuss methods used to isolate and measure the effectiveness of a probiotic. We outline future perspectives on probiotic applications in mass-reared insects.

A metagenomic analysis of the bacterial microbiome of limestone, and the role of associated biofilms in the biodeterioration of heritage stone surfaces

There is growing concern surrounding the aesthetic and physical effects of microbial biofilms on heritage buildings and monuments. Carboniferous stones, such as limestone and marble, are soluble in weak acid solutions and therefore particularly vulnerable to biocorrosion. This paper aims to determine the differences and commonalities between the microbiome of physically damaged and undamaged Lincolnshire limestone, an area of research which has not been previously studied. A lack of information about the core microbiome has resulted in conflicting claims in the literature regarding the biodeteriorative potential of many microorganisms. To address this, we used metagenomics alongside traditional microbiological techniques to produce an in-depth analysis of differences between the bacterial microbiomes found on deteriorated and undamaged external limestone surfaces. We demonstrate there is a core microbiome on Lincolnshire limestone present on both damaged and undamaged surfaces. In addition to the core microbiome, significant differences were found between species isolated from undamaged compared to damaged surfaces. Isolated species were characterised for biofilm formation and biodeteriorative processes, resulting in the association of species with biodeterioration that had not been previously described. Additionally, we have identified a previously undescribed method of biofilm-associated biomechanical damage. This research adds significant new understanding to the field, aiding decision making in conservation of stone surfaces.