MinION Sequencing of Yeast Mock Communities To Assess the Effect of Databases and ITS-LSU Markers on the Reliability of Metabarcoding Analysis

The bacterial and yeast microbiota in livestock forages in Hungary

BACKGROUND

Along bacteria, yeasts are common in forages and forage fermentations as spoilage microbes or as additives, yet few studies exist with species-level data on these fungi's occurrence in feedstuff. Active dry yeast and other yeast-based products are also common feed additives in animal husbandry. Here, we aimed to characterize both fermented and non-fermented milking cow feedstuff samples from Hungary to assess their microbial diversity in the first such study from Central Europe.

RESULTS

We applied long-read bacterial metabarcoding to 10 fermented and 25 non-fermented types of samples to assess bacterial communities and their characteristics, surveyed culturable mold and yeast abundance, and identified culturable yeast species. Fermented forages showed the abundance of Aerococcaceae, Bacillaceae, Brucellaceae, Lactobacillaceae, Staphylococcaceae, and Thermoactinomycetaceae, non-fermented ones had Cyanothecaceae, Enterobacteriaceae, Erwiniaceae, Gomontiellaceae, Oxalobacteraceae, Rhodobiaceae, Rickettsiaceae, and Staphylococcaceae. Abundances of bacterial families showed mostly weak correlation with yeast CFU numbers, only Microcoleaceae (positive) and Enterococcaceae and Alcaligenaceae (negative correlation) showed moderate correlation. We identified 14 yeast species, most commonly Diutina rugosa, Pichia fermentans, P. kudriavzevii, and Wickerhahomyces anomalus. We recorded S. cerevisiae isolates only from animal feed mixes with added active dry yeast, while the species was completely absent from fermented forages. The S. cerevisiae isolates showed high genetic uniformity.

CONCLUSION

Our results show that both fermented and non-fermented forages harbor diverse bacterial microbiota, with higher alpha diversity in the latter. The bacterial microbiome had an overall weak correlation with yeast abundance, but yeasts were present in the majority of the samples, including four new records for forages as a habitat for yeasts. Yeasts in forages mostly represented common species including opportunistic pathogens, along with a single strain of Saccharomyces used as a feed mix additive.

Primed and ready: nanopore metabarcoding can now recover highly accurate consensus barcodes that are generally indel-free

BACKGROUND

DNA metabarcoding applies high-throughput sequencing approaches to generate numerous DNA barcodes from mixed sample pools for mass species identification and community characterisation. To date, however, most metabarcoding studies employ second-generation sequencing platforms like Illumina, which are limited by short read lengths and longer turnaround times. While third-generation platforms such as the MinION (Oxford Nanopore Technologies) can sequence longer reads and even in real-time, application of these platforms for metabarcoding has remained limited possibly due to the relatively high read error rates as well as the paucity of specialised software for processing such reads.

RESULTS

We show that this is no longer the case by performing nanopore-based, cytochrome c oxidase subunit I (COI) metabarcoding on 34 zooplankton bulk samples, and benchmarking the results against conventional Illumina MiSeq sequencing. Nanopore R10.3 sequencing chemistry and super accurate (SUP) basecalling model reduced raw read error rates to ~ 4%, and consensus calling with amplicon_sorter (without further error correction) generated metabarcodes that were ≤ 1% erroneous. Although Illumina recovered a higher number of molecular operational taxonomic units (MOTUs) than nanopore sequencing (589 vs. 471), we found no significant differences in the zooplankton communities inferred between the sequencing platforms. Importantly, 406 of 444 (91.4%) shared MOTUs between Illumina and nanopore were also found to be free of indel errors, and 85% of the zooplankton richness could be recovered after just 12-15 h of sequencing.

CONCLUSION

Our results demonstrate that nanopore sequencing can generate metabarcodes with Illumina-like accuracy, and we are the first study to show that nanopore metabarcodes are almost always indel-free. We also show that nanopore metabarcoding is viable for characterising species-rich communities rapidly, and that the same ecological conclusions can be obtained regardless of the sequencing platform used. Collectively, our study inspires confidence in nanopore sequencing and paves the way for greater utilisation of nanopore technology in various metabarcoding applications.

Role of socioeconomic factors and interkingdom crosstalk in the dental plaque microbiome in early childhood caries

Early childhood caries (ECC) is influenced by microbial and host factors, including social, behavioral, and oral health. In this cross-sectional study, we analyze interkingdom dynamics in the dental plaque microbiome and its association with host variables. We use 16S rRNA and ITS1 amplicon sequencing on samples collected from preschool children and analyze questionnaire data to examine the social determinants of oral health. The results indicate a significant enrichment of Streptococcus mutans and Candida dubliniensis in ECC samples, in contrast to Neisseria oralis in caries-free children. Our interkingdom correlation analysis reveals that Candida dubliniensis is strongly correlated with both Neisseria bacilliformis and Prevotella veroralis in ECC. Additionally, ECC shows significant associations with host variables, including oral health status, age, place of residence, and mode of childbirth. This study provides empirical evidence associating the oral microbiome with socioeconomic and behavioral factors in relation to ECC, offering insights for developing targeted prevention strategies.

A comparison of microbiota isolation methods reveals habitat preferences for fermentative yeasts and plant pathogenic fungi in the grape berry

The methodologies for profiling the grape berry microbiota have exponentially evolved in the past 25 years. Recently, concerns arose regarding the homogeneity in the protocols of grape harvesting, sequencing and bioinformatic analyses, but the bias introduced by the microbiota isolation method is still unexplored. This study followed a simple approach of comparing two most used methods of microbiota collection from grape berries (washing vs crushing), hypothesizing a significant impact in the outcome of the microbiota profiles analyzed by NGS metabarcoding. Experiments conducted in fruits of three cultivars of the Douro wine region showed that only 52 % of OTUs were common to both surface and juice microbiota, suggesting specific microbial niches. Thirteen fungal genera were abundantly detected in the fruit surface, including Alternaria, Aureobasidium, Cladosporium, Didymella and Bipolaris. Fermentative yeasts including Meyerozyma and Saccharomyces cerevisiae were exclusively detected in the juice, together with several Penicillium species. Distinct habitat preferences of species within the genera Alternaria, Sporobolomyces and Rhodotorula were also revealed. The study showed that the microbiota isolation method is crucial in the detection of certain plant pathogenic/saprophytic fungi and yeasts with biotechnological and oenological interest, adding novelty to the globally accepted assumption that S. cerevisiae in musts originates primarily from the cellar.