RESCUE: a validated Nanopore pipeline to classify bacteria through long-read, 16S-ITS-23S rRNA sequencing

Application of nanopore long-read sequencing and metabolomics in an in vitro dynamic intestinal digestion model: A genome-centric metatranscriptomic approach to investigating microbial TMA and SCFA metabolism

The gut microbiota plays a relevant role in human health by metabolizing dietary components into bioactive molecules, including short-chain fatty acids and trimethylamine. Understanding how dietary interventions modulate microbial metabolism is key to developing strategies for reducing harmful metabolites such as TMA, a precursor of the pro-atherogenic trimethylamine-N-oxide. In this study, we integrated a dynamic in vitro gastrointestinal model (simgi®) with nanopore sequencing technology and metabolomics to investigate the impact of red thyme extract on microbial trimethylamine metabolism from L-carnitine. Metabarcoding, metagenomic, and metatranscriptomic analyses were performed alongside targeted metabolite quantification. Our results showed that microbial trimethylamine production primarily occurred in the transverse and descending colon compartments, coinciding with increased transcriptional activity of taxa harboring gbu cluster, associated with trimethylamine production. The administration of red thyme extract transiently reduced L-carnitine utilization but had a limited effect on overall trimethylamine levels. In parallel, short-chain fatty acids analysis revealed a shift in microbial fermentation patterns, with Acidaminococcus emerging as a dominant butyrate producer. Carbohydrate-active enzyme profiling identified Bacteroides and Parabacteroides genera as key mucin utilizers under the simulation conditions. These findings highlight the metabolic plasticity of the gut microbiota in response to the presence of L-carnitine and reduced complex carbohydrates availability, and provide new insights into microbial functional responses to dietary interventions targeting trimethylamine metabolism. Additionally, this study represents the first integration of nanopore-based metagenomics and genome-centric metatranscriptomics with targeted metabolomics in a dynamic in vitro gastrointestinal model. This multi-omics approach enabled a detailed reconstruction of the microbial metabolic network involved in L-carnitine utilization and trimethylamine formation, offering a powerful tool for mechanistic studies of gut microbiota-diet interactions.

Cas9-based enrichment for targeted long-read metabarcoding

Metabarcoding is a valuable tool for characterizing the communities that underpin the functioning of ecosystems. However, current methods often rely on polymerase chain reaction (PCR) amplification for enrichment of marker genes. PCR can introduce significant biases that affect quantification and is typically restricted to one target loci at a time, limiting the diversity that can be captured in a single reaction. Here, we address these issues by using Cas9 to enrich marker genes for long-read nanopore sequencing directly from a DNA sample, removing the need for PCR. We show that this approach can effectively isolate a 4.5 kb region covering partial 18S and 28S rRNA genes and the ITS region in a mixed nematode community, and further adapt our approach for characterizing a diverse microbial community. We demonstrate the ability for Cas9-based enrichment to support multiplexed targeting of several different DNA regions simultaneously, enabling optimal marker gene selection for different clades of interest within a sample. We also find a strong correlation between input DNA concentrations and output read proportions for mixed-species samples, demonstrating the ability for quantification of relative species abundance. This study lays a foundation for targeted long-read sequencing to more fully capture the diversity of organisms present in complex environments.

PRONAME: a user-friendly pipeline to process long-read nanopore metabarcoding data by generating high-quality consensus sequences

Background

The study of sample taxonomic composition has evolved from direct observations and labor-intensive morphological studies to different DNA sequencing methodologies. Most of these studies leverage the metabarcoding approach, which involves the amplification of a small taxonomically-informative portion of the genome and its subsequent high-throughput sequencing. Recent advances in sequencing technology brought by Oxford Nanopore Technologies have revolutionized the field, enabling portability, affordable cost and long-read sequencing, therefore leading to a significant increase in taxonomic resolution. However, Nanopore sequencing data exhibit a particular profile, with a higher error rate compared with Illumina sequencing, and existing bioinformatics pipelines for the analysis of such data are scarce and often insufficient, requiring specialized tools to accurately process long-read sequences.

Results

We present PRONAME (PROcessing NAnopore MEtabarcoding data), an open-source, user-friendly pipeline optimized for processing raw Nanopore sequencing data. PRONAME includes precompiled databases for complete 16S sequences (Silva138 and Greengenes2) and a newly developed and curated database dedicated to bacterial 16S-ITS-23S operon sequences. The user can also provide a custom database if desired, therefore enabling the analysis of metabarcoding data for any domain of life. The pipeline significantly improves sequence accuracy, implementing innovative error-correction strategies and taking advantage of the new sequencing chemistry to produce high-quality duplex reads. Evaluations using a mock community have shown that PRONAME delivers consensus sequences demonstrating at least 99.5% accuracy with standard settings (and up to 99.7%), making it a robust tool for genomic analysis of complex multi-species communities.

Conclusion

PRONAME meets the challenges of long-read Nanopore data processing, offering greater accuracy and versatility than existing pipelines. By integrating Nanopore-specific quality filtering, clustering and error correction, PRONAME produces high-precision consensus sequences. This brings the accuracy of Nanopore sequencing close to that of Illumina sequencing, while taking advantage of the benefits of long-read technologies.

Moving Beyond Oxford Nanopore Standard Procedures: New Insights from Water and Multiple Fish Microbiomes

Oxford Nanopore Technology (ONT) allows for the rapid profiling of aquaculture microbiomes. However, not all the experimental and downstream methodological possibilities have been benchmarked. Here, we aimed to offer novel insights into the use of different library preparation methods (standard-RAP and native barcoding-LIG), primers (V3-V4, V1-V3, and V1-V9), and basecalling models (fast-FAST, high-HAC, and super-accuracy-SUP) implemented in ONT to elucidate the microbiota associated with the aquatic environment and farmed fish, including faeces, skin, and intestinal mucus. Microbial DNA from water and faeces samples could be amplified regardless of the library-primer strategy, but only with LIG and V1-V3/V1-V9 primers in the case of skin and intestine mucus. Low taxonomic assignment levels were favoured by the use of full-length V1-V9 primers, though in silico hybridisation revealed a lower number of potential matching sequences in the SILVA database, especially evident with the increase in Actinobacteriota in real datasets. SUP execution allowed for a higher median Phred quality (24) than FAST (11) and HAC (17), but its execution time (6-8 h) was higher in comparison to the other models (0.6-7 h). Altogether, we optimised the use of ONT for water- and fish-related microbial analyses, validating, for the first time, the use of the LIG strategy. We consider that LIG-V1-V9-HAC is the optimal time/cost-effective option to amplify the microbial DNA from environmental samples. However, the use of V1-V3 could help to maximise the dataset microbiome diversity, representing an alternative when long amplicon sequences become compromised by microbial DNA quality and/or high host DNA loads interfere with the PCR amplification/sequencing procedures, especially in the case of gut mucus.

Interplay of human ABCC11 transporter gene variants with axillary skin microbiome functional genomics

The human armpit microbiome is metabolically entangled with skin cell physiology. This "meta-organism" symbiotic mutualism results in sweat either with or without odor (osmidrosis), depending on host ABCC11 gene haplotypes. Apocrine metabolism produces odorless S-glutathione conjugate that is transferred by ABCC11 transporters into secretory vesicles, deglutamylated to S-Cys-Gly-3M3SH thiol, and exuded to skin surface. An anthropogenic clade of skin bacteria then takes up the thiol and bioconverts it to malodorous 3-methyl-3-sulfanylhexan-1-ol (3M3SH). We hypothesized a familial meta-organism association of human ABCC11 gene non-synonymous SNP rs17822931 interplaying with skin microbiome 3M3SH biosynthesis. Subjects were genotyped for ABCC11 SNPs, and their haplotypes were correlated with axilla microbiome DNA sequencing profiles and predicted metagenome functions. A multigeneration family pedigree revealed a Mendelian autosomal recessive pattern: the C allele of ABCC11 correlated with bacterial Cys-S-conjugate β-lyase (PatB) gene known for Staphylococcus hominis biosynthesis of 3M3SH from human precursor; PatB was rescinded in hosts with homozygous TT alleles encoding ABCC11 loss-of-function mutation. We posit that a C allele encoding functional ABCC11 is key to delivering host conjugate precursors that shape heritable skin niche conditions favorable to harboring Staphylococcus having genomics of odor thiol production. This provides existential insights into human evolution and global regional population ancestries.

Complete pipeline for Oxford Nanopore Technology amplicon sequencing (ONT-AmpSeq): from pre-processing to creating an operational taxonomic unit table

Amplicon sequencing has long served as a robust method for characterising microbial communities, and despite inherent resolution limitations, it remains a preferred technique, offering cost- and time-effective insights into bacterial compositions. Here, we introduce ONT-AmpSeq, a user-friendly pipeline designed for processing amplicon sequencing data generated from Oxford Nanopore Technology (ONT) devices. Our pipeline enables efficient creation of taxonomically annotated operational taxonomic unit (OTU) tables from ONT sequencing data, with the flexibility to multiplex amplicons on the same barcode. The pipeline encompasses six main steps-statistics, quality filtering, alignment, clustering, polishing, and taxonomic classification-integrating various state-of-the-art software tools. We provide a detailed description of each step, along with performance tests and robustness evaluations using both test data and a ZymoBIOMICS® Microbial Community Standard mock community dataset. Our results demonstrate the ability of ONT-AmpSeq to effectively process ONT amplicon data, offering valuable insights into microbial community composition. Additionally, we discuss the influence of polishing tools on taxonomic insight and the impact of taxonomic annotation methods on the derived microbial composition. Overall, ONT-AmpSeq represents a comprehensive solution for analysing ONT amplicon sequencing data, facilitating streamlined and reliable microbial community analysis. The pipeline, along with test data, is freely available for public use.

Short-read full-length 16S rRNA amplicon sequencing for characterisation of the respiratory bacteriome of captive and free-ranging African elephants (Loxodonta africana)

Hypervariable region sequencing of the 16S ribosomal RNA (rRNA) gene plays a critical role in microbial ecology by offering insights into bacterial communities within specific niches. While providing valuable genus-level information, its reliance on data from targeted genetic regions limits its overall utility. Recent advances in sequencing technologies have enabled characterisation of the full-length 16S rRNA gene, enhancing species-level classification. Although current short-read platforms are cost-effective and precise, they lack full-length 16S rRNA amplicon sequencing capability. This study aimed to evaluate the feasibility of a modified 150 bp paired-end full-length 16S rRNA amplicon short-read sequencing technique on the Illumina iSeq 100 and 16S rRNA amplicon assembly workflow by utilising a standard mock microbial community and subsequently performing exploratory characterisation of captive (zoo) and free-ranging African elephant (Loxodonta africana) respiratory microbiota. Our findings demonstrate that, despite generating assembled amplicons averaging 869 bp in length, this sequencing technique provides taxonomic assignments consistent with the theoretical composition of the mock community and respiratory microbiota of other mammals. Tentative bacterial signatures, potentially representing distinct respiratory tract compartments (trunk and lower respiratory tract) were visually identified, necessitating further investigation to gain deeper insights into their implication for elephant physiology and health.

GROND: a quality-checked and publicly available database of full-length 16S-ITS-23S rRNA operon sequences

Sequence comparison of 16S rRNA PCR amplicons is an established approach to taxonomically identify bacterial isolates and profile complex microbial communities. One potential application of recent advances in long-read sequencing technologies is to sequence entire rRNA operons and capture significantly more phylogenetic information compared to sequencing of the 16S rRNA (or regions thereof) alone, with the potential to increase the proportion of amplicons that can be reliably classified to lower taxonomic ranks. Here we describe GROND (Genome-derived Ribosomal Operon Database), a publicly available database of quality-checked 16S-ITS-23S rRNA operons, accompanied by multiple taxonomic classifications. GROND will aid researchers in analysis of their data and act as a standardised database to allow comparison of results between studies.

Microbial Community Profiling Protocol with Full-length 16S rRNA Sequences and Emu

16S rRNA targeted amplicon sequencing is an established standard for elucidating microbial community composition. While high-throughput short-read sequencing can elicit only a portion of the 16S rRNA gene due to their limited read length, third generation sequencing can read the 16S rRNA gene in its entirety and thus provide more precise taxonomic classification. Here, we present a protocol for generating full-length 16S rRNA sequences with Oxford Nanopore Technologies (ONT) and a microbial community profile with Emu. We select Emu for analyzing ONT sequences as it leverages information from the entire community to overcome errors due to incomplete reference databases and hardware limitations to ultimately obtain species-level resolution. This pipeline provides a low-cost solution for characterizing microbiome composition by exploiting real-time, long-read ONT sequencing and tailored software for accurate characterization of microbial communities. © 2024 Wiley Periodicals LLC. Basic Protocol: Microbial community profiling with Emu Support Protocol 1: Full-length 16S rRNA microbial sequences with Oxford Nanopore Technologies sequencing platform Support Protocol 2: Building a custom reference database for Emu.