Identification of consensus head and neck cancer-associated microbiota signatures: a systematic review and meta-analysis of 16S rRNA and The Cancer Microbiome Atlas datasets

Yeo, Kenny; Li, Runhao; Wu, Fangmeinuo; Bouras, George; Mai, Linh T.H.; Smith, Eric; Wormald, Peter-John; Valentine, Rowan; Psaltis, Alkis James; Vreugde, Sarah; Fenix, Kevin

doi:10.1099/jmm.0.001799

Cited by 3 publications

References 109 publications

(218 reference statements)

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

Yeo,

Connell,

Bouras

et al. 2024

Arch Microbiol

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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.

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

Yeo,

Connell,

Bouras

et al. 2024

Arch Microbiol

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

Yeo,

Connell,

Bouras

et al. 2024

Preprint

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Introduction: 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 ribosomal RNA (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). To date, this is the largest study using HNC tissues samples to perform FL-ONT of the 16S rRNA using ONT. Methods: Sequencing of the full-length and the V3-V4 16S rRNA region was conducted on tumour samples from 26 HNC patients, using ONT and Illumina technologies respectively. Paired sample analysis was applied to compare differences in diversities and abundance of microbial communities. Further validation was also performed using culture-based methods in 16 bacterial isolates obtained from 4 patients using MALDI-TOF MS. Results: We observed similar alpha diversity indexes between FL-ONT and V3V4-Illumina technologies. However, beta-diversity was significantly different between techniques (PERMANOVA - R2 = 0.083, 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 microbial 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 (81.3% v.s. 62.5%). Conclusions: FL-ONT was able to identify lower taxonomic levels at a better resolution as compared to V3V4-Illumina 16S rRNA sequencing. Depending on application purposes, both methods are suitable for identification of microbial communities, with FL-ONT being more superior at species level.

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Is Short-Read 16S rRNA Sequencing of Oral Microbiome Sampling a Suitable Diagnostic Tool for Head and Neck Cancer?

Yeo,

Wu,

et al. 2024

Pathogens

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The oral microbiome, studied by sampling the saliva or by oral rinse, has been long thought to have diagnostic capacity for head and neck cancers (HNC). However, previous reports on the HNC oral microbiome provide inconsistent results. The aim of this study is to consolidate these datasets and determine the oral microbial composition between HNC patients to healthy and premalignant individuals. We analyzed 16 published head and neck cancer (HNC) short-read 16S rRNA sequencing datasets, specifically targeting the V3V4, V4 and V4V5 regions. These datasets included saliva and oral rinse samples from donors with HNC, as well as from healthy and premalignant donors. Differences in diversities and microbial abundance were determined. HNC saliva displayed lower alpha diversity than healthy donors. In contrast, the opposite trend was observed for oral rinse samples. Beta diversity scores were largely similar across different patient types. Similar oral phyla were detected for all samples, but proportions were largely dependent on sample type (i.e., saliva or oral rinse) and primer set utilized for 16S rRNA sequencing. Neisseria, Leptotrichia and Megasphaera were elevated in healthy saliva, while Mycoplasma was elevated in HNC saliva. Oral rinse and saliva displayed similar enrichment for Fusobacterium, while Veillonella, Alloprevotella, and Campylobacter showed conflicting results. The sparse partial least squares discriminant analysis model performed effectively in discriminating HNC from healthy or premalignant patients using V3V4 saliva (AUC = 0.888) and V3V4 oral rinse (AUC = 0.928), while poor discriminative capacity was observed for V4 saliva (AUC = 0.688). In conclusion, our meta-analysis highlighted the limitations of 16S rRNA sequencing, particularly due to variations across study batches, primer sets (i.e., V3V4, V4), and sample types. Hence, caution should be exercised when interpreting 16S rRNA sequencing results across studies, especially when different primer sets and sample types are used.

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Identification of consensus head and neck cancer-associated microbiota signatures: a systematic review and meta-analysis of 16S rRNA and The Cancer Microbiome Atlas datasets

Cited by 3 publications

References 109 publications

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

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

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

Is Short-Read 16S rRNA Sequencing of Oral Microbiome Sampling a Suitable Diagnostic Tool for Head and Neck Cancer?

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