Nationwide USA re-analysis of amplicon metabarcoding targeting β-tubulin isoform-1 reveals absence of benzimidazole resistant SNPs in Ancylostoma braziliense, Ancylostoma tubaeforme and Uncinaria stenocephala

Nationwide sampling by Venkatesan and colleagues (2023) described the resistance status of the canine hookworm, Ancylostoma caninum, to benzimidazoles across the USA via β-tubulin isotype-1 amplicon metabarcoding. In this study, we aimed to use the existing public amplicon metabarcoding data and mine it for the presence of β-tubulin isotype-1 sequences that belong to hookworm species other than A. caninum. Through bioinformatics analysis we assigned species to A. caninum, Ancylostoma braziliense, Ancylostoma tubaeforme and Uncinaria stenocephala. All non-A. caninum sequences contained only the benzimidazole susceptible residues of β-tubulin isotype-1. Using two β-tubulin isotype-1 metabarcoding sequence data (assay targeting 134 and 167 codons, and assay targeting 198 and 200 codons), 2.0% (6/307) and 2.9% (9/310) individual samples had hookworms other than A. caninum (A. braziliense n = 5, A. tubaeforme n = 4 and U. stenocephala n = 2), respectively. We identified one sample containing A. braziliense in each of the Northeastern region and Midwestern region, and in three samples from the Southern region. Presence of A. tubaeforme in dog faeces is considered as pseudoparasitism. There were no statistically significant regional differences for the distribution of each species, for either of the two assays independently or combined (χ2 tests, P > 0.05). Our work demonstrates the utility of the amplicon metabarcoding for the identification of species through antemortem assays, thus resolving the dilemma of assigning hookworm species based on either post-mortem or egg sizes for the identification of hookworms.

Estuarine microbial networks and relationships vary between environmentally distinct communities

Microbial interactions have profound impacts on biodiversity, biogeochemistry, and ecosystem functioning, and yet, they remain poorly understood in the ocean and with respect to changing environmental conditions. We applied hierarchical clustering of an annual 16S and 18S amplicon dataset in the Skidaway River Estuary, which revealed two similar clusters for prokaryotes (Bacteria and Archaea) and protists: Cluster 1 (March-May and November-February) and Cluster 2 (June-October). We constructed co-occurrence networks from each cluster to explore how microbial networks and relationships vary between environmentally distinct periods in the estuary. Cluster 1 communities were exposed to significantly lower temperature, sunlight, NO₃, and SiO₄; only NH₄ was higher at this time. Several network properties (e.g., edge number, degree, and centrality) were elevated for networks constructed with Cluster 1 vs. 2 samples. There was also evidence that microbial nodes in Cluster 1 were more connected (e.g., higher edge density and lower path length) compared to Cluster 2, though opposite trends were observed when networks considered Prokaryote-Protist edges only. The number of Prokaryote-Prokaryote and Prokaryote-Protist edges increased by >100% in the Cluster 1 network, mainly involving Flavobacteriales, Rhodobacterales, Peridiniales, and Cryptomonadales associated with each other and other microbial groups (e.g., SAR11, Bacillariophyta, and Strombidiida). Several Protist-Protist associations, including Bacillariophyta correlated with Syndiniales (Dino-Groups I and II) and an Unassigned Dinophyceae group, were more prevalent in Cluster 2. Based on the type and sign of associations that increased in Cluster 1, our findings indicate that mutualistic, competitive, or predatory relationships may have been more representative among microbes when conditions were less favorable in the estuary; however, such relationships require further exploration and validation in the field and lab. Coastal networks may also be driven by shifts in the abundance of certain taxonomic or functional groups. Sustained monitoring of microbial communities over environmental gradients, both spatial and temporal, is critical to predict microbial dynamics and biogeochemistry in future marine ecosystems.

Microbial profiles of Greek PDO cheeses assessed with amplicon metabarcoding

Greece is a country possessing many cheese products granted with a PDO (Protected Designation of Origin) certificate, with high exporting activities. In this study, we analyzed six popular cheese PDO products purchased from different industries to assess their microbial communities using amplicon metabarcoding analysis. To this end, using Next Generation Sequencing technology, we sequenced the 16S rRNA gene and the ITS spacer for prokaryotes and fungi, respectively. Alpha diversity indices revealed higher bacterial species richness for some cheeses (Kopanisti, Batzos) and poor for others (Feta, Galotiri). Kopanisti, together with Kalathaki and Anevato, also presented increased species diversity concerning fungal populations. Results showed that lactic acid bacteria (LAB) prevailed the bacterial populations in all samples (Lactococcus, Lactobacillus, Streptococcus, Leuconostoc), whereas for fungi, members of the Saccharomycetaceae, Dipodascaceae and Debaryomycetaceae families prevailed the fungal populations. Several other genera were identified that make up each product's microbiome leading to the creation of the unique organoleptic attributes of Greek PDO cheeses. However, the identified species could not be directly linked to certain cheese types, assuming that starter and adjunct cultures, combined with the raw material used during production greatly impact the microbial communities in cheeses. Our data, produced for the first time for six Greek PDO cheeses, can be exploited in the process of creating a core microbial signature within each cheese type, supporting the Greek brand name and valorizing cheese products.