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

Combining Short- and Long-Read Sequencing Technologies to Identify SARS-CoV-2 Variants in Wastewater

During the COVID-19 pandemic, the monitoring of SARS-CoV-2 RNA in wastewater was used to track the evolution and emergence of variant lineages and gauge infection levels in the community, informing appropriate public health responses without relying solely on clinical testing. As more sublineages were discovered, it increased the difficulty in identifying distinct variants in a mixed population sample, particularly those without a known lineage. Here, we compare the sequencing technology from Illumina and from Oxford Nanopore Technologies, in order to determine their efficacy at detecting variants of differing abundance, using 248 wastewater samples from various Quebec and Ontario cities. Our study used two analytical approaches to identify the main variants in the samples: the presence of signature and marker mutations and the co-occurrence of signature mutations within the same amplicon. We observed that each sequencing method detected certain variants at different frequencies as each method preferentially detects mutations of distinct variants. Illumina sequencing detected more mutations with a predominant lineage that is in low abundance across the population or unknown for that time period, while Nanopore sequencing had a higher detection rate of mutations that are predominantly found in the high abundance B.1.1.7 (Alpha) lineage as well as a higher sequencing rate of co-occurring mutations in the same amplicon. We present a workflow that integrates short-read and long-read sequencing to improve the detection of SARS-CoV-2 variant lineages in mixed population samples, such as wastewater.

Spectral Algal Fingerprinting and Long Sequencing in Synthetic Algal-Microbial Communities

Synthetic biology has advanced in creating artificial microbial and algal communities, but technical and evolutionary complexities still pose significant challenges. Traditional methods, like microscopy and pigment analysis, are limited in throughput and resolution. In contrast, advancements in full-spectrum cytometry enabled high-throughput, multidimensional analysis of single cells based on size, complexity, and spectral fingerprints, offering more precision and flexibility than conventional flow cytometry. This study uses full-spectrum cytometry to analyze synthetic algal-microbial communities, enabling rapid species identification and enumeration. The workflow involves recording individual spectral signatures from monocultures, using autofluorescence to capture populations of interest, and creating a spectral library for further analysis. This spectral library was used for the analysis of the synthetic phytoplankton communities, revealing differences in spectral signatures. Moreover, the synthetic consortium experiment monitored algal growth, comparing results from different instruments, highlighting the advantages of the spectral virtual filter system for precise population separation and abundance tracking. By capturing the entire emission spectrum of each cell, this method enhances understanding of algal-microbial community dynamics and responses to environmental stressors. The development of standardized spectral libraries would improve the characterization of algal communities, further advancing synthetic biology and phytoplankton ecology research.

What's on the menu? A novel molecular gut content analysis to investigate the feeding behavior of phytophagous insects

The relationship between phytophagous insects and plants is a central aspect of food webs and ecosystem functioning. The introduction of new species into an environment can have significant impacts on the food web of a native ecosystem. In many cases, there is a lack of knowledge on the biology and feeding behavior of invasive species prior their introduction and in the invaded regions. Gut content analyses of insects have provided valuable information on the host spectrum of insects. However, current approaches are time-consuming and costly. Here, we describe a new molecular gut content analysis (GCA) approach using the Oxford Nanopore (ONT) Flongle sequencing platform to characterize the plant DNA present in the gut of the highly polyphagous insect species Halyomorpha halys. We demonstrate that this technique efficiently amplifies and correctly identifies plant DNA in a mock community. We performed a feeding experiment to determine the sensitivity of this approach and to assess how long the plant DNA can be detected. All plants used in the feeding experiment were correctly identified and detected after 56 days. Surprisingly, we also detected various plant genera that were not included in the feeding experiment and thus were likely ingested months before the experiment. Our study suggests that the GCA using the ONT Flongle sequencing platform represents a rapid and cost-efficient diagnosis of the dietary preferences, host range, and the diversity of consumed plant species of pest insects with high precision.

Insights into mycobacteriome composition in Mycobacterium bovis-infected African buffalo (Syncerus caffer) tissue samples

Animal tuberculosis significantly challenges global health, agriculture, and wildlife conservation efforts. Mycobacterial cultures are resource-intensive, time-consuming, and challenged by heterogeneous populations. In this study, we employed a culture-independent approach, using targeted long-read-based next-generation sequencing (tNGS), to investigate the mycobacterial composition in 60 DNA samples extracted from Mycobacterium bovis infected culture-confirmed African buffalo tissue. We detected mycobacterial DNA in 93.3% of the samples and the sensitivity for detecting Mycobacterium tuberculosis complex (MTBC) was 91.7%, demonstrating a high concordance of our culture-independent tNGS approach with mycobacterial culture results. In five samples, we identified heterogenous mycobacterial populations with various non-tuberculous mycobacteria, including members of the Mycobacterium avium complex (MAC), M. smegmatis, and M. komaniense. The latter Mycobacterium species was described in South Africa from bovine nasal swabs and environmental samples from the Hluhluwe-iMfolozi Park, which was the origin of the buffalo samples in the present study. This finding suggests that exposure to environmental mycobacteria may confound detection of MTBC in wildlife. In conclusion, our approach represents a promising alternative to conventional methods for detecting mycobacterial DNA. This high-throughput technique enables rapid differentiation of heterogeneous mycobacterial populations, which will contribute valuable insights into the epidemiology, pathogenesis, and microbial synergy during mycobacterial infections.

EnsembleSeq: a workflow towards real-time, rapid, and simultaneous multi-kingdom-amplicon sequencing for holistic and resource-effective microbiome research at scale

Bacterial communities are often concomitantly present with numerous microorganisms in the human body and other natural environments. Amplicon-based microbiome studies have generally paid skewed attention, that too at a rather shallow genus level resolution, to the highly abundant bacteriome, with interest now forking toward the other microorganisms, particularly fungi. Given the generally sparse abundance of other microbes in the total microbiome, simultaneous sequencing of amplicons targeting multiple microbial kingdoms could be possible even with full multiplexing. Guiding studies are currently needed for performing and monitoring multi-kingdom-amplicon sequencing and data capture at scale. Aiming to address these gaps, amplification of full-length bacterial 16S rRNA gene and entire fungal internal-transcribed spacer (ITS) region was performed for human saliva samples (n = 96, including negative and positive controls). Combined amplicon DNA libraries were prepared for nanopore sequencing using a major fraction of 16S molecules and a minor fraction of ITS amplicons. Sequencing was performed in a single run of an R10.4.1 flow cell employing the latest V14 chemistry. An approach for real-time monitoring of the species saturation using dynamic rarefaction was designed as a guiding determinant of optimal run time. Real-time saturation monitoring for both bacterial and fungal species enabled the completion of sequencing within 30 hours, utilizing less than 60% of the total nanopores. Approximately 5 million high quality (HQ) taxonomically assigned reads were generated (~4.2 million bacterial and 0.7 million fungal), providing a wider (beyond bacteriome) snapshot of human oral microbiota at species-level resolution. Among the more than 400 bacterial and 240 fungal species identified in the studied samples, the species of Streptococcus (e.g., Streptococcus mitis and Streptococcus oralis) and Candida (e.g., Candida albicans and Candida tropicalis) were observed to be the dominating microbes in the oral cavity, respectively. This conformed well with the previous reports of the human oral microbiota. EnsembleSeq provides a proof-of-concept toward the identification of both fungal and bacterial species simultaneously in a single fully multiplexed nanopore sequencing run in a time- and resource-effective manner. Details of this workflow, along with the associated codebase, are provided to enable large-scale application for a holistic species-level microbiome study.

IMPORTANCE

Human microbiome is a sum total of a variety of microbial genomes (including bacteria, fungi, protists, viruses, etc.) present in and on the human body. Yet, a majority of amplicon-based microbiome studies have largely remained skewed toward bacteriome as an assumed proxy of the total microbiome, primarily at a shallow genus level. Cost, time, effort, data quality/management, and importantly lack of guiding studies often limit progress in the direction of moving beyond bacteriome. Here, EnsembleSeq presents a proof-of-concept toward concomitantly capturing multiple-kingdoms of microorganisms (bacteriome and mycobiome) in a fully multiplexed (96-sample) single run of long-read amplicon sequencing. In addition, the workflow captures dynamic tracking of species-level saturation in a time- and resource-effective manner.

Using short-read 16S rRNA sequencing of multiple variable regions to generate high-quality results to a species level

Introduction

Short-read amplicon sequencing studies have typically focused on 1-2 variable regions of the 16S rRNA gene. Species-level resolution is limited in these studies, as each variable region enables the characterisation of a different subsection of the microbiome. Although long-read sequencing techniques take advantage of all 9 variable regions by sequencing the entire 16S rRNA gene, they are substantially more expensive. This work assessed the feasibility of accurate species-level resolution and reproducibility using a relatively new sequencing kit and bioinformatics pipeline developed for short-read sequencing of multiple variable regions of the 16S rRNA gene. In addition, we evaluated the potential impact of different sample collection methods on our outcomes.

Methods

Using xGen™ 16S Amplicon Panel v2 kits, sequencing of all 9 variable regions of the 16S rRNA gene was carried out on an Illumina MiSeq platform. Mock cells and mock DNA for 8 bacterial species were included as extraction and sequencing controls respectively. Within-run and between-run replicate samples, and pairs of stool and rectal swabs collected at 0-5 weeks from the same participants, were incorporated. Observed relative abundances of each species were compared to theoretical abundances provided by ZymoBIOMICS. Paired Wilcoxon rank sum tests and distance-based intraclass correlation coefficients were used to statistically compare alpha and beta diversity measures, respectively, for pairs of replicates and stool/rectal swab sample pairs.

Results

Using multiple variable regions of the 16S ribosomal Ribonucleic Acid (rRNA) gene, we found that we could accurately identify taxa to a species level and obtain highly reproducible results at a species level. Yet, the microbial profiles of stool and rectal swab sample pairs differed substantially despite being collected concurrently from the same infants.

Conclusion

This protocol provides an effective means for studying infant gut microbial samples at a species level. However, sample collection approaches need to be accounted for in any downstream analysis.

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.

Differential microbiota shift on whole romaine lettuce subjected to source or forward processing and on fresh-cut products during cold storage

Romaine lettuce in the U.S. is primarily grown in California or Arizona and either processed near the growing regions (source processing) or transported long distance for processing in facilities serving distant markets (forward processing). Recurring outbreaks of Escherichia coli O157:H7 implicating romaine lettuce in recent years, which sometimes exhibited patterns of case clustering in Northeast and Midwest, have raised industry concerns over the potential impact of forward processing on romaine lettuce food safety and quality. In this study, freshly harvested romaine lettuce from a commercial field destined for both forward and source processing channels was tracked from farm to processing facility in two separate trials. Whole-head romaine lettuce and packaged fresh-cut products were collected from both forward and source facilities for microbiological and product quality analyses. High-throughput amplicon sequencing targeting16S rRNA gene was performed to describe shifts in lettuce microbiota. Total aerobic bacteria and coliform counts on whole-head lettuce and on fresh-cut lettuce at different storage times were significantly (p < 0.05) higher for those from the forward processing facility than those from the source processing facility. Microbiota on whole-head lettuce and on fresh-cut lettuce showed differential shifting after lettuce being subjected to source or forward processing, and after product storage. Consistent with the length of pre-processing delays between harvest and processing, the lettuce quality scores of source-processed romaine lettuce, especially at late stages of 2-week storage, was significantly higher than of forward-processed product (p < 0.05).

Impact of Equine Ocular Surface Squamous Neoplasia on Interactions between Ocular Transcriptome and Microbiome

Ocular surface squamous neoplasia (OSSN) represents the most common conjunctival tumor in horses and frequently results in vision loss and surgical removal of the affected globe. Multiple etiologic factors have been identified as contributing to OSSN progression, including solar radiation exposure, genetic mutations, and a lack of periocular pigmentation. Response to conventional treatments has been highly variable, though our recent work indicates that these tumors are highly responsive to local immunotherapy. In the present study, we extended our investigation of OSSN in horses to better understand how the ocular transcriptome responds to the presence of the tumor and how the ocular surface microbiome may also be altered by the presence of cancer. Therefore, we collected swabs from the ventral conjunctival fornix from 22 eyes in this study (11 with cytologically or histologically confirmed OSSN and 11 healthy eyes from the same horses) and performed RNA sequencing and 16S microbial sequencing using the same samples. Microbial 16s DNA sequencing and bulk RNA sequencing were both conducted using an Illumina-based platform. In eyes with OSSN, we observed significantly upregulated expression of genes and pathways associated with inflammation, particularly interferon. Microbial diversity was significantly reduced in conjunctival swabs from horses with OSSN. We also performed interactome analysis and found that three bacterial taxa (Actinobacillus, Helcococcus and Parvimona) had significant correlations with more than 100 upregulated genes in samples from animals with OSSN. These findings highlight the inflammatory nature of OSSN in horses and provide important new insights into how the host ocular surface interacts with certain microbial populations. These findings suggest new strategies for the management of OSSN in horses, which may entail immunotherapy in combination with ocular surface probiotics or prebiotics to help normalize ocular cell and microbe interactions.

Microbiome diversity and zoonotic bacterial pathogen prevalence in Peromyscus mice from agricultural landscapes and synanthropic habitat

Rodents are key reservoirs of zoonotic pathogens and play an important role in disease transmission to humans. Importantly, anthropogenic land-use change has been found to increase the abundance of rodents that thrive in human-built environments (synanthropic rodents), particularly rodent reservoirs of zoonotic disease. Anthropogenic environments also affect the microbiome of synanthropic wildlife, influencing wildlife health and potentially introducing novel pathogens. Our objective was to examine the effect of agricultural development and synanthropic habitat on microbiome diversity and the prevalence of zoonotic bacterial pathogens in wild Peromyscus mice to better understand the role of these rodents in pathogen maintenance and transmission. We conducted 16S amplicon sequencing on faecal samples using long-read nanopore sequencing technology to characterize the rodent microbiome. We compared microbiome diversity and composition between forest and synanthropic habitats in agricultural and undeveloped landscapes and screened for putative pathogenic bacteria. Microbiome richness, diversity, and evenness were higher in the agricultural landscape and synanthropic habitat compared to undeveloped-forest habitat. Microbiome composition also differed significantly between agricultural and undeveloped landscapes and forest and synanthropic habitats. We detected overall low diversity and abundance of putative pathogenic bacteria, though putative pathogens were more likely to be found in mice from the agricultural landscape. Our findings show that landscape- and habitat-level anthropogenic factors affect Peromyscus microbiomes and suggest that landscape-level agricultural development may be important to predict zoonotic pathogen prevalence. Ultimately, understanding how anthropogenic land-use change and synanthropy affect rodent microbiomes and pathogen prevalence is important to managing transmission of rodent-borne zoonotic diseases to humans.

Full-length 16S rRNA gene sequencing by PacBio improves taxonomic resolution in human microbiome samples

BACKGROUND

Sequencing variable regions of the 16S rRNA gene (≃300 bp) with Illumina technology is commonly used to study the composition of human microbiota. Unfortunately, short reads are unable to differentiate between highly similar species. Considering that species from the same genus can be associated with health or disease it is important to identify them at the lowest possible taxonomic rank. Third-generation sequencing platforms such as PacBio SMRT, increase read lengths allowing to sequence the whole gene with the maximum taxonomic resolution. Despite its potential, full length 16S rRNA gene sequencing is not widely used yet. The aim of the current study was to compare the sequencing output and taxonomic annotation performance of the two approaches (Illumina short read sequencing and PacBio long read sequencing of 16S rRNA gene) in different human microbiome samples. DNA from saliva, oral biofilms (subgingival plaque) and faeces of 9 volunteers was isolated. Regions V3-V4 and V1-V9 were amplified and sequenced by Illumina Miseq and by PacBio Sequel II sequencers, respectively.

RESULTS

With both platforms, a similar percentage of reads was assigned to the genus level (94.79% and 95.06% respectively) but with PacBio a higher proportion of reads were further assigned to the species level (55.23% vs 74.14%). Regarding overall bacterial composition, samples clustered by niche and not by sequencing platform. In addition, all genera with > 0.1% abundance were detected in both platforms for all types of samples. Although some genera such as Streptococcus tended to be observed at higher frequency in PacBio than in Illumina (20.14% vs 14.12% in saliva, 10.63% vs 6.59% in subgingival plaque biofilm samples) none of the differences were statistically significant when correcting for multiple testing.

CONCLUSIONS

The results presented in the current manuscript suggest that samples sequenced using Illumina and PacBio are mostly comparable. Considering that PacBio reads were assigned at the species level with higher accuracy than Illumina, our data support the use of PacBio technology for future microbiome studies, although a higher cost is currently required to obtain an equivalent number of reads per sample.

Techniques, procedures, and applications in microbiome analysis

Microbiota is a complex community of microorganisms living in a defined environment. Until the 20th century, knowledge of microbiota was partial, as the techniques available for their characterization were primarily based on bacteriological culture. In the last twenty years, the development of DNA sequencing technologies, multi-omics, and bioinformatics has expanded our understanding of microorganisms. We have moved from mainly considering them isolated disease-causing agents to recognizing the microbiota as an essential component of host biology. These techniques have shown that the microbiome plays essential roles in various host phenotypes, influencing development, physiology, reproduction, and evolution. This chapter provides researchers with a summary of the primary concepts, sample collection, experimental techniques, and bioinformatics analysis commonly used in microbiome research. The main features, applications in microbiome studies, and their advantages and limitations are included in each section.

16S rRNA Gene Amplicon Analysis of Human Gut Microbiota

The intestinal microbiota is associated with a variety of diseases, and there are a growing number of research reports on the gut microbiota. In addition, a new technique such as Nanopore sequencing has recently become available, making it easier to conduct research related to the gut microbiota. In this chapter, we introduce a technique used in gut microbiota analysis, from stool collection to sequencing with MinION.

Long-read MinION™ sequencing of 16S and 16S-ITS-23S rRNA genes provides species-level resolution of Lactobacillaceae in mixed communities

The Lactobacillaceae are lactic acid bacteria harnessed to deliver important outcomes across numerous industries, and their unambiguous, species-level identification from mixed community environments is an important endeavor. Amplicon-based metataxonomics using short-read sequencing of partial 16S rRNA gene regions is widely used to support this, however, the high genetic similarity among Lactobacillaceae species restricts our ability to confidently describe these communities even at genus level. Long-read sequencing (LRS) of the whole 16S rRNA gene or the near complete rRNA operon (16S-ITS-23S) has the potential to improve this. We explored species ambiguity amongst Lactobacillaceae using in-silico tool RibDif2, which identified allele overlap when various partial and complete 16S rRNA gene and 16S-ITS-23S rRNA regions were amplified. We subsequently implemented LRS by MinION™ to compare the capacity of V3-V4, 16S and 16S-ITS-23S rRNA amplicons to accurately describe the diversity of a 20-species Lactobacillaceae mock community in practice. In-silico analysis identified more instances of allele/species overlap with V3-V4 amplicons (n = 43) compared to the 16S rRNA gene (n = 11) and partial (n = up to 15) or complete (n = 0) 16S-ITS-23S rRNA amplicons. With subsequent LRS of a DNA mock community, 80% of target species were identified using V3-V4 amplicons whilst the 16S rRNA gene and 16S-ITS-23S rRNA region amplicons resulted in 95 and 100% of target species being identified. A considerable reduction in false-positive identifications was also seen with 16S rRNA gene (n = 3) and 16S-ITS-23S rRNA region (n = 9) amplicons compared with V3-V4 amplicons (n = 43). Whilst the target species affected by allele overlap in V3-V4 and 16S rRNA gene sequenced mock communities were predicted by RibDif2, unpredicted species ambiguity was observed in 16S-ITS-23S rRNA sequenced communities. Considering the average nucleotide identity (ANI) between ambiguous species (~97%) and the basecall accuracy of our MinION™ sequencing protocol (96.4%), the misassignment of reads between closely related taxa is to be expected. With basecall accuracy exceeding 99% for recent MinION™ releases, the increased species-level differentiating power promised by longer amplicons like the 16S-ITS-23S rRNA region, may soon be fully realized.

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.

Nanopore sequencing technology and its applications

Since the development of Sanger sequencing in 1977, sequencing technology has played a pivotal role in molecular biology research by enabling the interpretation of biological genetic codes. Today, nanopore sequencing is one of the leading third-generation sequencing technologies. With its long reads, portability, and low cost, nanopore sequencing is widely used in various scientific fields including epidemic prevention and control, disease diagnosis, and animal and plant breeding. Despite initial concerns about high error rates, continuous innovation in sequencing platforms and algorithm analysis technology has effectively addressed its accuracy. During the coronavirus disease (COVID-19) pandemic, nanopore sequencing played a critical role in detecting the severe acute respiratory syndrome coronavirus-2 virus genome and containing the pandemic. However, a lack of understanding of this technology may limit its popularization and application. Nanopore sequencing is poised to become the mainstream choice for preventing and controlling COVID-19 and future epidemics while creating value in other fields such as oncology and botany. This work introduces the contributions of nanopore sequencing during the COVID-19 pandemic to promote public understanding and its use in emerging outbreaks worldwide. We discuss its application in microbial detection, cancer genomes, and plant genomes and summarize strategies to improve its accuracy.

Comparative analysis of full-length 16s ribosomal RNA genome sequencing in human fecal samples using primer sets with different degrees of degeneracy

Next-generation sequencing has revolutionized the field of microbiology research and greatly expanded our knowledge of complex bacterial communities. Nanopore sequencing provides distinct advantages, combining cost-effectiveness, ease of use, high throughput, and high taxonomic resolution through its ability to process long amplicons, such as the entire 16s rRNA genome. We examine the performance of the conventional 27F primer (27F-I) included in the 16S Barcoding Kit distributed by Oxford Nanopore Technologies (ONT) and that of a more degenerate 27F primer (27F-II) in the context of highly complex bacterial communities in 73 human fecal samples. The results show striking differences in both taxonomic diversity and relative abundance of a substantial number of taxa between the two primer sets. Primer 27F-I reveals a significantly lower biodiversity and, for example, at the taxonomic level of the phyla, a dominance of Firmicutes and Proteobacteria as determined by relative abundances, as well as an unusually high ratio of Firmicutes/Bacteriodetes when compared to the more degenerate primer set (27F-II). Considering the findings in the context of the gut microbiomes common in Western industrial societies, as reported in the American Gut Project, the more degenerate primer set (27F-II) reflects the composition and diversity of the fecal microbiome significantly better than the 27F-I primer. This study provides a fundamentally relevant comparative analysis of the in situ performance of two primer sets designed for sequencing of the entire 16s rRNA genome and suggests that the more degenerate primer set (27F-II) should be preferred for nanopore sequencing-based analyses of the human fecal microbiome.