DNA Reads Research Articles

Fungal and fungal-like diversity present in ornithogenically influenced maritime Antarctic soils assessed using metabarcoding.

We assessed soil fungal and fungal-like diversity using metabarcoding in ornithogenically influenced soils around nests of the bird species Phalacrocorax atriceps, Macronectes giganteus, Pygoscelis antarcticus, and Pygoscelis adelie on the South Shetland Islands, maritime Antarctic. A total of 1,392,784 fungal DNA reads was obtained and assigned to 186 amplicon sequence variants (ASVs). The dominant fungal phylum was Ascomycota, followed by Basidiomycota, Chytridiomycota, Blastocladiomycota, Rozellomycota, Mortierellomycota, Monoblepharomycota, Aphelidiomycota, Basidiobolomycota, Mucoromycota, and the fungal-like Oomycota (Stramenopila), in rank order. Antarctomyces sp., Blastocladiomycota sp., Pseudogymnoascus pannorum, Microascaceae sp., Mortierella sp., Lobulomycetales sp., Sordariomycetes sp., Fungal sp., Rhizophydiales sp., Pseudeurotiaceae sp., Chytridiomycota sp. 1, Filobasidiella sp., Tausonia pullulans, Betamyces sp., and Leucosporidium sp. were the most abundant assigned taxa. The fungal assemblages present in the different ornithogenically influenced soils displayed different diversity indices. However, in general, we detected high fungal diversity and few taxa shared between the samples. Despite the polyextreme environmental conditions experienced in these Antarctic soils, the metabarcoding approach detected a rich and complex fungal community dominated by saprophytes, but with some pathogenic taxa also present. The community was dominated by psychrophilic and psychrotolerant taxa, some apparently endemic to Antarctica, and those identified only at higher taxonomic levels, which may represent currently undescribed fungi. The mycobiome detected included taxa characterized by different ecological roles, including saprotrophic, human- and animal-associated, phytopathogenic, mutualistic, and cosmopolitan. These fungi may potentially be dispersed by birds or in the air column over great distances, including between different regions within Antarctica and from South America, Africa, and Oceania.

A Revised Molecular Model of Ovarian Cancer Biomarker CA125 (MUC16) Enabled by Long-read Sequencing.

Despite its crucial role in clinical management of ovarian cancer, the exact molecular sequence and structure of the biomarker, CA125, are not defined. Here, we combine long-read sequencing, mass spectrometry, and in silico modeling to provide the foundational dataset for a more complete characterization of the CA125 epitope.

Unraveling Zooplankton Diversity in a Pre-Alpine Lake: A Comparative Analysis of ZooScan and DNA Metabarcoding Methods

Zooplankton, integral to aquatic ecosystems, face diverse environmental influences. To comprehend their dynamics, critical for ecological insights and fisheries management, traditional morphological analysis proves laborious. Recent advances include automated systems like ZooScan and DNA metabarcoding. This study examines two methods on the same samples to identify similarities and dependencies between them, potentially reducing the required workload and enhancing the quality of the results. Ten Lake Starnberg vertical tows in September 2021 provided zooplankton samples preserved in ethanol. Subsamples underwent ZooScan morphological identification and subsequent DNA metabarcoding. High concordance between ZooScan counts and DNA reads (86.8%) was observed, while biomass calculations from body length (major axis) and equivalent spherical diameter (ESD) showed slightly lower agreement (78.1% and 79.6%, respectively). Linear regression analysis revealed a correlation between counts and DNA reads (r2 = 0.59). This study underscores the complementary strengths and limitations of ZooScan and DNA metabarcoding for zooplankton analysis. ZooScan aids biomass estimation and morphological differentiation, whereas DNA metabarcoding offers superior taxonomic resolution and low-abundance taxon detection. Combining both methods on the same sample enhances understanding and facilitates future advanced analyses.

Long-Read Sequencing Genome Assembly of Ceratocystis fimbriata Enables Development of Molecular Diagnostics for Sweetpotato Black Rot.

Ceratocystis fimbriata is a destructive fungal pathogen of sweetpotato (Ipomoea batatas) that leads to losses at all stages of sweetpotato production. Accurate detection of C. fimbriata would allow for more efficient deployment of management tactics in sweetpotato production. To develop a diagnostic assay, a hybrid genome assembly of C. fimbriata isolate AS236 was generated. The resulting 31.7-MB assembly was near-chromosome level, with 18 contigs, 6,481 predicted genes, and a BUSCO completion score of 98.4% when compared with the fungus-specific lineage database. Additional Illumina DNA reads from C. manginecans, C. platani, and a second C. fimbriata isolate (C1421) were then mapped to the assembled genome using BOWTIE2 and counted using HTSeq, which identified 148 genes present only within C. fimbriata as molecular diagnostic candidates; 6 single-copy and 35 highly multi-copy (>40 BLAST hits), as determined through a self-BLAST-P alignment. Primers for PCR were designed in the 200-bp flanking region of the first exon for each candidate, and the candidates were validated against a diverse DNA panel containing Ceratocystis species, sweetpotato pathogens, and plants. After validation, two diagnostic candidates amplified only C. fimbriata DNA and were considered to be highly specific to the species. These genetic markers will serve as valuable diagnostic tools with multiple applications including the detection of C. fimbriata in seed, soil, and wash water in sweetpotato production.

Community structure and association network of prokaryotic community in surface sediments from the Bering-Chukchi shelf and adjacent sea areas.

The Bering-Chukchi shelf is one of the world's most productive areas and characterized by high benthic biomass. Sedimentary microbial communities play a crucial role in the remineralization of organic matter and associated biogeochemical cycles, reflecting both short-term changes in the environment and more consistent long-term environmental characteristics in a given habitat. In order to get a better understanding of the community structure of sediment-associated prokaryotes, surface sediments were collected from 26 stations in the Bering-Chukchi shelf and adjacent northern deep seas in this study. Prokaryote community structures were analyzed by metabarcoding of the 16S rRNA gene, and potential interactions among prokaryotic groups were analyzed by co-occurrence networks. Relationships between the prokaryote community and environmental factors were assessed. Gammaproteobacteria, Alphaproteobacteria, and Flavobacteriia were the dominant bacterial classes, contributing 35.0, 18.9, and 17.3% of the bacterial reads, respectively. The phototrophic cyanobacteria accounted for 2.7% of the DNA reads and occurred more abundantly in the Bering-Chukchi shelf. Prokaryotic community assemblages were different in the northern deep seas compared to the Bering-Chukchi shelf, represented by the lowered diversity and the increased abundant operational Taxonomic Units (OTU), suggesting that the abundant taxa may play more important roles in the northern deep seas. Correlation analysis showed that latitude, water depth, and nutrients were important factors affecting the prokaryote community structure. Abundant OTUs were distributed widely in the study area. The complex association networks indicated a stable microbial community structure in the study area. The high positive interactions (81.8-97.7%) in this study suggested that symbiotic and/or cooperative relationships accounted for a dominant proportion of the microbial networks. However, the dominant taxa were generally located at the edge of the co-occurrence networks rather than in the major modules. Most of the keystone OTUs were intermediately abundant OTUs with relative reads between 0.01 and 1%, suggesting that taxa with moderate biomass might have considerable impacts on the structure and function of the microbial community. This study enriched the understanding of prokaryotic community in surface sediments from the Bering-Chukchi shelf and adjacent sea areas.

Efficient Memory Layout for Pre-Alignment Filtering of Long DNA Reads Using Racetrack Memory

Efficient Memory Layout for Pre-Alignment Filtering of Long DNA Reads Using Racetrack Memory

Approaches for the Analysis and Interpretation of Whole-Genome Bisulfite Sequencing Data.

DNA methylation is a covalent modification of DNA that plays important roles in processes such as the regulation of gene expression, transcription factor binding, and suppression of transposable elements. The use of whole-genome bisulfite sequencing (WGBS) enables the genome-wide identification and quantification of DNA methylation patterns at single-base resolution and is the gold standard for the analysis of DNA methylation. However, the computational analysis of WGBS data can be particularly challenging, as many computationally intensive steps are required. Here, we outline step-by-step an approach for the analysis and interpretation of WGBS data. First, sequencing reads must be trimmed, quality-checked, and aligned to the genome. Second, DNA methylation levels are estimated at each cytosine position using the aligned sequence reads of the bisulfite-treated DNA. Third, regions of differential cytosine methylation between samples can be identified. Finally, these data need to be visualized and interpreted in the context of the biological question at hand.

GCOC: A Genome Classifier-On-Chip based on Similarity Search Content Addressable Memory.

GCOC is a genome classification system-on-chip (SoC) that classifies genomes by k-mer matching, an approach that divides a DNA query sequence into a set of short DNA fragments of size k, which are searched in a reference genome database, with the underlying assumption that sequenced DNA reads of the same organism (or its close variants) share most of such k-mers. At the core of GCOC is a similarity, or approximate search-capable Content Addressable Memory (SAS-CAM), which in addition to exact match, also supports approximate, or Hamming distance tolerant search. Classification operation is controlled by an embedded RISC-V processor. GCOC classification platform was designed and manufactured in a commercial 65nm process. We conduct a thorough analysis of GCOC classification efficiency as well as its performance, silicon area, and power consumption using silicon measurements. GCOC classifies 769.2K short DNA reads/sec. The silicon area of GCOC SoC is 3.12mm2 and its power consumption is 1.27mW. We envision GCOC deployed as a field (for example at points of care) portable classifier where the classification is required to be real-time, easy to operate and energy efficient.

A full-length SSU rRNA-based workflow for high-resolution monitoring of nematode communities reveals direct and indirect responses to plant-based manipulations

Agricultural intensification has resulted in a decline in soil biodiversity, and concerns about the deterioration of the biological condition of soils prompted the development of measures to restore soil life. Due to the overwhelming biodiversity of soils, evaluation of such measures is not straightforward, and proxies are used to assess soil health. Because of their trophic diversity, high abundance, and relatively well-characterized ecologies, nematodes are often used as soil health indicators. However, the scarcity of informative morphological characters hampers the upscaling of this proxy. Here we present a community analysis approach that uses nanopore sequencing to generate full-length sequences of small subunit ribosomal DNAs (SSU rDNA). Cover cropping is a common agricultural practice that stimulates soil life, and we mapped the effects of ten cover crop treatments on nematode communities in a field experiment. These analyses included the monitoring of a high-impact plant-parasite, Meloidogyne chitwoodi. In total, 132 nematode samples were analyzed, and 65 nematode taxa were detected, mostly at the species level, including representatives of all trophic groups. As a validation, all samples were analyzed microscopically for M. chitwoodi, and a comparison of count and DNA read data revealed highly similar results. Treatments did not only affect plant-parasitic nematodes but also free-living nematodes in a cover crop-specific manner. Free-living nematodes from the same trophic group, and even congeneric species, responded differentially to plant-mediated manipulations of the soil microbiome. Hence, nanopore-based SSU rDNA sequencing could facilitate a substantial refinement of the use of nematodes as indicators for soil health.

Performance of environmental DNA metabarcoding to identify and quantify benthic organisms in river ecosystems

Our lack of fundamental knowledge about species occurrence, abundance, distribution, threats, and habitat requirements makes it challenging to conserve biodiversity in the face of rising human pressure. To obtain this information, practical and sensitive methods are required to identify and quantify the occurrence and diversity of rare, cryptic, and elusive species. Environmental DNA (eDNA) is a new technology that can help to discover and quantify biodiversity by addressing some of the limitations of conventional surveys. This study aimed to evaluate the biodiversity and composition of benthic species in the Lower Ciliwung River, Jakarta, Indonesia. The investigation was conducted from upstream to downstream of the river at the three sites during the dry season (July 2022). The DNA read sequences were used to examine the composition, relative abundance, and diversity of the samples. In this study, 1,492,975 initial reads were filtered down to 1,265,307 reads belonging to 27 species of benthic organisms. The taxa identified from the eDNA samples revealed that the most frequently detected species belonged to the family Siboglinidae, order Sabellida, and class Polychaeta. The composition of benthic species discovered in the eDNA water samples varied substantially (p ≤ 0.05). Osedax sp. (class Polychaeta) was the most prevalent species across all locations. The diversity index (H) ranged from low to moderate. eDNA offers potential advantages, but is hampered by DNA degradation, primer sensitivity, and the inability to distinguish between dead and living organisms.

BIOM-12. ULTRA-DEEP WHOLE GENOME SEQUENCING UNCOVERS A HIGH PREVALENCE OF GLIOBLASTOMA-DERIVED CELL-FREE DNA IN PLASMA

Abstract The detection of glioblastoma-derived circulating cell-free DNA (ccfDNA) has proven formidable because tumor-specific mutations are hidden among the abundance of ccfDNA from healthy cells. While capture-enrichment panels provide the necessary read depth to detect low-frequency variants, searches are constrained to a narrow range of targets and largely limited to single nucleotide variants (SNVs). Here, we use ultra-deep whole genome sequencing (WGS) to broaden the search for somatic mutations across the entire genome. In addition, a kmer-based reference-free variant caller, which mitigates the bias and errors that accrue during alignment, is used to extend the mutation search beyond SNVs to include insertions/deletions (INDELS) and structural variants (SVs) such as large INDELS ( >20 bp) and tandem duplications. In tumor DNA and ccfDNA, we achieve a WGS (GRCh38) mean read depth of 263X and 225X, respectively. WGS of matched buffy coat DNA and sequencing reads from the 1000 Genome Database were used to eliminate germline polymorphisms, sequencing artifacts, and common variants. We detected 20,488 somatic mutations in tumor DNA of which 17.3% affected a coding sequence, 31.9% were INDELS, 91 were large INDELs, and 18 were tandem duplications. A tumor-informed search identified 489 of these somatic mutations in ccfDNA which included a large INDEL and a similar portion of mutations affecting a coding sequence. Using an unguided search for glioblastoma-derived ccfDNA uncovered an additional 8,794 somatic mutations of which 16.6% involved a coding sequence, 60.7% were INDELS, 30 were large INDELS, and 3 were tandem duplications. The high prevalence of somatic mutations discovered in ccfDNA using an unbiased approach highlights the low yield of tumor-informed searches in spatially genetically heterogeneous cancers like glioblastoma. Our findings demonstrate that ultra-deep WGS detects glioblastoma-derived ccfDNA by broadening the search for variants across the entire genome and through the inclusion of INDELS and SVs.

A Deep Insight into the Diversity of Microfungal Communities in Arctic and Antarctic Lakes.

We assessed fungal diversity in water and sediment samples obtained from five Arctic lakes in Ny-Ålesund (Svalbard Islands, High Arctic) and five Antarctic lakes on Livingston and Deception Islands (South Shetland Islands), using DNA metabarcoding. A total of 1,639,074 fungal DNA reads were detected and assigned to 5980 ASVs amplicon sequence variants (ASVs), with only 102 (1.7%) that were shared between the two Polar regions. For Arctic lakes, unknown fungal taxa dominated the sequence assemblages, suggesting the dominance of possibly undescribed fungi. The phylum Chytridiomycota was the most represented in the majority of Arctic and Antarctic samples, followed by Rozellomycota, Ascomycota, Basidiomycota, and the less frequent Monoblepharomycota, Aphelidiomycota, Mortierellomycota, Mucoromycota, and Neocallimastigomycota. At the genus level, the most abundant genera included psychrotolerant and cosmopolitan cold-adapted fungi including Alternaria, Cladosporium, Cadophora, Ulvella (Ascomycota), Leucosporidium, Vishniacozyma (Basidiomycota), and Betamyces (Chytridiomycota). The assemblages displayed high diversity and richness. The assigned diversity was composed mainly of taxa recognized as saprophytic fungi, followed by pathogenic and symbiotic fungi.

Retrieval of long DNA reads from herbarium specimens.

High-throughput sequencing of herbarium specimens' DNA with short-read platforms has helped explore many biological questions. Here, for the first time, we investigate the potential of using herbarium specimens as a resource for long-read DNA sequencing technologies. We use target capture of 48 low-copy nuclear loci in 12 herbarium specimens of Silene as a basis for long-read sequencing using SMRT PacBio Sequel. The samples were collected between 1932 and 2019. A simple optimization of size selection protocol enabled the retrieval of both long DNA fragments (>1 kb) and long on-target reads for nine of them. The limited sampling size does not enable statistical evaluation of the influence of specimen age to the DNA fragmentation, but our results confirm that younger samples, that is, collected after 1990, are less fragmented and have better sequencing success than specimens collected before this date. Specimens collected between 1990 and 2019 yield between 167 and 3403 on-target reads > 1 kb. They enabled recovering between 34 loci and 48 (i.e. all loci recovered). Three samples from specimens collected before 1990 did not yield on-target reads > 1 kb. The four other samples collected before this date yielded up to 144 reads and recovered up to 25 loci. Young herbarium specimens seem promising for long-read sequencing. However, older ones have partly failed. Further exploration would be necessary to statistically test and understand the potential of older material in the quest for long reads. We would encourage greatly expanding the sampling size and comparing different taxonomic groups.

Complete Mitochondrial DNA Genome Variation in the Swedish Population.

The development of complete mitochondrial genome (mitogenome) reference data for inclusion in publicly available population databases is currently underway, and the generation of more high-quality mitogenomes will only enhance the statistical power of this forensically useful locus. To characterize mitogenome variation in Sweden, the mitochondrial DNA (mtDNA) reads from the SweGen whole genome sequencing (WGS) dataset were analyzed. To overcome the interference from low-frequency nuclear mtDNA segments (NUMTs), a 10% variant frequency threshold was applied for the analysis. In total, 934 forensic-quality mitogenome haplotypes were characterized. Almost 45% of the SweGen haplotypes belonged to haplogroup H. Nearly all mitogenome haplotypes (99.1%) were assigned to European haplogroups, which was expected based on previous mtDNA studies of the Swedish population. There were signature northern Swedish and Finnish haplogroups observed in the dataset (e.g., U5b1, W1a), consistent with the nuclear DNA analyses of the SweGen data. The complete mitogenome analysis resulted in high haplotype diversity (0.9996) with a random match probability of 0.15%. Overall, the SweGen mitogenomes provide a large mtDNA reference dataset for the Swedish population and also contribute to the effort to estimate global mitogenome haplotype frequencies.

Metabarcoding of microeukaryotes in surface sediments from the Pacific Arctic and adjacent sea areas: The role of diatoms in the biological pump

To better understand the importance of diatoms in carbon burial and biological pumps in the Pacific Arctic, we analyzed the microeukaryotic assemblages in twenty-six surface sediments from the northern Bering and Chukchi Seas and adjacent sea areas by metabarcoding the V4 region of the 18S rRNA gene. Biogenic elements were measured, and the contributions of diatoms to sediment carbon are discussed. A total of 618 operational taxonomic units (OTUs) of microeukaryotes were identified. Microalgae accounted for a majority of the DNA reads. Diatoms predominated in the microeukaryotic sequences, and Chaetoceros socialis was the most dominant species, especially in the Bering and Chukchi Seas. The microeukaryotic community was different in the northern deep sea, as represented by the decrease in algal and diatom reads. Organic carbon mainly originated from marine sources in the Chukchi Sea, while the Bering Sea and northern deep seas had relatively more terrestrial inputs based on the TOC/TN data. High BSi concentrations (average > 5% with a maximum of 12.87%) and BSi/TOC ratios (average > 2%) in the Bering and Chukchi Seas indicated the high diatom productivity and efficiency of the silicate pump. Diatom DNA reads were positively correlated with all biogenic elements, indicating that diatoms play an important role in organic matter burial, especially for the dominant diatom species C. socialis due to its fast growth rate and bloom- and spore-forming abilities.

Time-calibrated phylogeny and full mitogenome sequence of the Galapagos sea lion (Zalophus wollebaeki) from scat DNA.

The Galapagos sea lion, Zalophus wollebaeki, is an endemic and endangered otariid, which is considered as a sentinel species of ecosystem dynamics in the Galapagos archipelago. Mitochondrial DNA is an important tool in phylogenetic and population genetic inference. In this work we use Illumina sequencing to complement the mitogenomic resources for Zalophus genus-the other two species employed Sanger sequencing-by a complete mitochondrial genome and a molecular clock of this species, which is not present in any case. We used DNA obtained from a fresh scat sample of a Galapagos sea lion and shotgun-sequenced it on the Illumina NextSeq platform. The obtained raw reads were processed using the GetOrganelle software to filter the mitochondrial Zalophus DNA reads (∼16% survive the filtration), assemble them, and set up a molecular clock. From the obtained 3,511,116 raw reads, we were able to assemble a full mitogenome of a length of 16,676 bp, consisting of 13 protein-coding genes (PCGs), 22 transfer RNAs (tRNA), and two ribosomal RNAs (rRNA). A time-calibrated phylogeny confirmed the phylogenetic position of Z. wollebaeki in a clade with Z. californianus, and Z. japonicus, and sister to Z. californianus; as well as establishing the divergence time for Z. wollebaeki 0.65 million years ago. Our study illustrates the possibility of seamlessly sequencing full mitochondrial genomes from fresh scat samples of marine mammals.

HQAlign: aligning nanopore reads for SV detection using current-level modeling.

Detection of structural variants (SVs) from the alignment of sample DNA reads to the reference genome is an important problem in understanding human diseases. Long reads that can span repeat regions, along with an accurate alignment of these long reads play an important role in identifying novel SVs. Long-read sequencers, such as nanopore sequencing, can address this problem by providing very long reads but with high error rates, making accurate alignment challenging. Many errors induced by nanopore sequencing have a bias because of the physics of the sequencing process and proper utilization of these error characteristics can play an important role in designing a robust aligner for SV detection problems. In this article, we design and evaluate HQAlign, an aligner for SV detection using nanopore sequenced reads. The key ideas of HQAlign include (i) using base-called nanopore reads along with the nanopore physics to improve alignments for SVs, (ii) incorporating SV-specific changes to the alignment pipeline, and (iii) adapting these into existing state-of-the-art long-read aligner pipeline, minimap2 (v2.24), for efficient alignments. We show that HQAlign captures about 4%-6% complementary SVs across different datasets, which are missed by minimap2 alignments while having a standalone performance at par with minimap2 for real nanopore reads data. For the common SV calls between HQAlign and minimap2, HQAlign improves the start and the end breakpoint accuracy by about 10%-50% for SVs across different datasets. Moreover, HQAlign improves the alignment rate to 89.35% from minimap2 85.64% for nanopore reads alignment to recent telomere-to-telomere CHM13 assembly, and it improves to 86.65% from 83.48% for nanopore reads alignment to GRCh37 human genome. https://github.com/joshidhaivat/HQAlign.git.

DNA metabarcoding of mock communities highlights potential biases when assessing Neotropical fish diversity

AbstractDespite the increasing popularity of DNA metabarcoding in the assessment of aquatic ecosystems using fish eDNA or ichthyoplankton, challenges have hampered its broader application in the Neotropical freshwaters. Using five mock communities composed of fish species from two Neotropical River basins, we evaluated the influence of DNA concentration and choice of mitochondrial 12S molecular markers (MiFish, NeoFish, and Teleo) on species detection and relative read abundance (RRA) using DNA metabarcoding. Of the three 12S markers analyzed, only MiFish detected all species from all mock communities. The performance of a taxonomy‐free approach using ASV/MOTUs was not as precise as assigning DNA reads to species using a curated 12S library that includes approximately 100 fish species since more than one ASV/MOTU was observed for the same specimen. Thus, here we showcase the importance of a custom reference database to allow precise assignment of Neotropical fish species in metabarcoding studies and that the RRA is dependent on community composition, marker, and DNA concentration. We highlight the importance of controlled experiments using known species communities before large investments are made in assessing biodiversity using non‐invasive methods that apply DNA metabarcoding.

Estimated Nucleotide Reconstruction Quality Symbols of Basecalling Tools for Oxford Nanopore Sequencing.

Currently, one of the fastest-growing DNA sequencing technologies is nanopore sequencing. One of the key stages involved in processing sequencer data is the basecalling process, where the input sequence of currents measured on the nanopores of the sequencer reproduces the DNA sequences, called DNA reads. Many of the applications dedicated to basecalling, together with the DNA sequence, provide the estimated quality of the reconstruction of a given nucleotide (quality symbols are contained on every fourth line of the FASTQ file; each nucleotide in the FASTQ file corresponds to exactly one estimated nucleotide reconstruction quality symbol). Herein, we compare the estimated nucleotide reconstruction quality symbols (signs from every fourth line of the FASTQ file) reported by other basecallers. The conducted experiments consisted of basecalling the same raw datasets from the nanopore device by other basecallers and comparing the provided quality symbols, denoting the estimated quality of the nucleotide reconstruction. The results show that the estimated quality reported by different basecallers may vary, depending on the tool used, particularly in terms of range and distribution. Moreover, we mapped basecalled DNA reads to reference genomes and calculated matched and mismatched rates for groups of nucleotides with the same quality symbol. Finally, the presented paper shows that the estimated nucleotide reconstruction quality reported in the basecalling process is not used in any investigated tool for processing nanopore DNA reads.

A Snapshot of the Influent and Effluent Bacterial Populations in a Wastewater Treatment Plant in the North-West Province, South Africa

Wastewater treatment plants receive influent wastewater that is contaminated with bacterial pathogens which may be released into the environment if the plant effluent is inadequately treated. In this study, next-generation sequencing was used to perform a 16S rDNA-based survey of bacterial populations in the influent and effluent from a treatment facility in the North-West Province (SA). In total, 3638 and 3872 effective DNA reads were obtained for the influent and effluent, respectively. Sequence analysis revealed the detection of a diverse bacterial constituency in both the influent and effluent samples. The phyla: Proteobacteria (49.82% and 52.04%), Firmicutes (14.06% and 13.14%) and Actinobacteria (5.00% and 9.99%) were found to be taxonomically abundant in the influent and effluent, respectively. This translated to the detection of biological treatment-, fecal coliform-, and disease-associated bacterial groups that are classified under the following genera: Escherichia spp., Serratia spp., Aeromonas spp., Legionella spp., Pseudomonas spp., Mycobacterium spp., Clostridium spp., Staphylococcus spp. and Streptococcus spp., Comamonas spp., Nitrosomonas spp., Acinetobacter spp., Rhodobacter spp., Paracoccus spp., Hyphomicrobium spp., and Desulfovibrio spp.