DNA structural features and variability of complete MHC locus sequences.

The major histocompatibility (MHC) locus, also known as the Human Leukocyte Antigen (HLA) genes, is located on the short arm of chromosome 6, and contains three regions (Class I, Class II and Class III). This 5 Mbp locus is one of the most variable regions of the human genome, yet it also encodes a set of highly conserved and important proteins related to immunological response. Genetic variations in this region are responsible for more diseases than in the entire rest of the human genome. However, information on local structural features of the DNA is largely ignored. With recent advances in long-read sequencing technology, it is now becoming possible to sequence the entire 5 Mbp MHC locus, producing complete diploid haplotypes of the whole region. Here, we describe structural maps based on the complete sequences from six different homozygous HLA cell lines. We find long-range structural variability in the different sequences for DNA stacking energy, position preference and curvature, variation in repeats, as well as more local changes in regions forming open chromatin structures, likely to influence gene expression levels. These structural maps can be useful in visualizing large scale structural variation across HLA types, in particular when this can be complemented with epigenetic signals.

Genomic surveillance of SARS-CoV-2 using long-range PCR primers.

Introduction: Whole Genome Sequencing (WGS) of the SARS-CoV-2 virus is crucial in the surveillance of the COVID-19 pandemic. Several primer schemes have been developed to sequence nearly all of the ~30,000 nucleotide SARS-CoV-2 genome, using a multiplex PCR approach to amplify cDNA copies of the viral genomic RNA. Midnight primers and ARTIC V4.1 primers are the most popular primer schemes that can amplify segments of SARS-CoV-2 (400 bp and 1200 bp, respectively) tiled across the viral RNA genome. Mutations within primer binding sites and primer-primer interactions can result in amplicon dropouts and coverage bias, yielding low-quality genomes with 'Ns' inserted in the missing amplicon regions, causing inaccurate lineage assignments, and making it challenging to monitor lineage-specific mutations in Variants of Concern (VoCs). Methods: In this study we used a set of seven long-range PCR primer pairs to sequence clinical isolates of SARS-CoV-2 on Oxford Nanopore sequencer. These long-range primers generate seven amplicons approximately 4500 bp that covered whole genome of SARS-CoV-2. One of these regions includes the full-length S-gene by using a set of flanking primers. We also evaluated the performance of these long-range primers with Midnight primers by sequencing 94 clinical isolates in a Nanopore flow cell. Results and discussion: Using a small set of long-range primers to sequence SARS-CoV-2 genomes reduces the possibility of amplicon dropout and coverage bias. The key finding of this study is that long range primers can be used in single-molecule sequencing of RNA viruses in surveillance of emerging variants. We also show that by designing primers flanking the S-gene, we can obtain reliable identification of SARS-CoV-2 variants.

Genomic Surveillance of SARS-CoV-2 Using Long-Range PCR Primers.

Whole Genome Sequencing (WGS) of the SARS-CoV-2 virus is crucial in the surveillance of the COVID-19 pandemic. Several primer schemes have been developed to sequence the ~30,000 nucleotide SARS-CoV-2 genome that use a multiplex PCR approach to amplify cDNA copies of the viral genomic RNA. Midnight primers and ARTIC V4.1 primers are the most popular primer schemes that can amplify segments of SARS-CoV-2 (400 bp and 1200 bp, respectively) tiled across the viral RNA genome. Mutations within primer binding sites and primer-primer interactions can result in amplicon dropouts and coverage bias, yielding low-quality genomes with 'Ns' inserted in the missing amplicon regions, causing inaccurate lineage assignments, and making it challenging to monitor lineage-specific mutations in Variants of Concern (VoCs). This study uses seven long-range PCR primers with an amplicon size of ~4500 bp to tile across the complete SARS-CoV-2 genome. One of these regions includes the full-length S-gene by using a set of flanking primers. Using a small set of long-range primers to sequence SARS-CoV-2 genomes reduces the possibility of amplicon dropout and coverage bias.

Severe Acute Respiratory Syndrome Coronavirus-2 Lambda Variant Collected from a Child from Arkansas and Sequenced.

An eleven-year-old tested positive for SARS-CoV-2 Lambda variant. Sequencing was performed on the Oxford Nanopore and the Illumina NextSeq 500. Both platforms identified all 7 of the synonymous mutations in the sample, while all 28 nonsynonymous mutations were identified from Oxford Nanopore and 20 nonsynonymous mutations were identified from Illumina.

Big data in genomic research for big questions with examples from covid-19 and other zoonoses.

Omics research inevitably involves the collection and analysis of big data, which can only be handled by automated approaches. Here we point out that the analysis of big data in the field of genomics dictates certain requirements, such as specialized software, quality control of input data, and simplification for visualization of the results. The latter results in a loss of information, as is exemplified for phylogenetic trees. Clear communication of big data analyses can be enhanced by novel visualization strategies. The interpretation of findings is sometimes hampered when dedicated analytical tools are not fully understood by microbiologists, while the researchers performing these analyses may not have a full overview of the biology of the microbes under study. These issues are illustrated here, using SARS-Cov-2 and Salmonella enterica as zoonotic examples. Whereas in scientific communications jargon should be avoided or explained, nomenclature to group similar organisms and distinguish these from more distant relatives is not only essential, but also influences the interpretation of results. Unfortunately, changes in taxonomically accepted names are now so frequent that they hamper rather than assist research, as is illustrated with difficulties of microbiome studies. Nomenclature to group viral isolates, as is done for SARS-Cov2, is also not without difficulties. Some weaknesses in current omics research stem from poor quality of data or biased databases, and problems can be magnified by machine learning approaches. Moreover, the overall opus of scientific publications can now be considered "big data", as is illustrated by the avalanche of COVID-19-related publications. The peer-review model of scientific publishing is only barely coping with this novel situation, resulting in retractions and the publication of bogus works. The avalanche of scientific publications that originated from the current pandemic can obstruct literature searches, and this will unfortunately continue over time.

Comparison of Monkeypox virus genomes from the 2017 Nigeria outbreak and the 2022 outbreak.

AIMS: The current Monkeypox virus (MPX) outbreak is not only the largest known outbreak to date caused by a strain belonging to the West-African clade, but also results in remarkably different clinical and epidemiological features compared to previous outbreaks of this virus. Here, we consider the possibility that mutations in the viral genome may be responsible for its changed characteristics. METHODS AND RESULTS: Six genome sequences of isolates from the current outbreak were compared to five genomes of isolates from the 2017 outbreak in Nigeria and to two historic genomes, all belonging to the West-African clade. We report differences that are consistently present in the 2022 isolates but not in the others. Although some variation in repeat units was observed, only two were consistently found in the 2022 genomes only, and these were located in intergenic regions. A total of 55 single nucleotide polymorphisms were consistently present in the 2022 isolates compared to the 2017 isolates. Of these, 25 caused an amino acid substitution in a predicted protein. CONCLUSIONS: The nature of the substitution and the annotation of the affected protein identified potential candidates that might affect the virulence of the virus. These included the viral DNA helicase and transcription factors. SIGNIFICANCE: This bioinformatic analysis provides guidance for wet-lab research to identify changed properties of the MPX.

The first three waves of the Covid-19 pandemic hint at a limited genetic repertoire for SARS-CoV-2.

The genomic diversity of SARS-CoV-2 is the result of a relatively low level of spontaneous mutations introduced during viral replication. With millions of SARS-CoV-2 genome sequences now available, we can begin to assess the overall genetic repertoire of this virus. We find that during 2020, there was a global wave of one variant that went largely unnoticed, possibly because its members were divided over several sublineages (B.1.177 and sublineages B.1.177.XX). We collectively call this Janus, and it was eventually replaced by the Alpha (B.1.1.7) variant of concern (VoC), next replaced by Delta (B.1.617.2), which itself might soon be replaced by a fourth pandemic wave consisting of Omicron (B.1.1.529). We observe that splitting up and redefining variant lineages over time, as was the case with Janus and is now happening with Alpha, Delta and Omicron, is not helpful to describe the epidemic waves spreading globally. Only ∼5% of the 30 000 nucleotides of the SARS-CoV-2 genome are found to be variable. We conclude that a fourth wave of the pandemic with the Omicron variant might not be that different from other VoCs, and that we may already have the tools in hand to effectively deal with this new VoC.

Is amplification bias consequential in transposon sequencing (TnSeq) assays? A case study with a Staphylococcus aureus TnSeq library subjected to PCR-based and amplification-free enrichment methods.

As transposon sequencing (TnSeq) assays have become prolific in the microbiology field, it is of interest to scrutinize their potential drawbacks. TnSeq data consist of millions of nucleotide sequence reads that are generated by PCR amplification of transposon-genomic junctions. Reads mapping to the junctions are enumerated thus providing information on the number of transposon insertion mutations in each individual gene. Here we explore the possibility that PCR amplification of transposon insertions in a TnSeq library skews the results by introducing bias into the detection and/or enumeration of insertions. We compared the detection and frequency of mapped insertions when altering the number of PCR cycles, and when including a nested PCR, in the enrichment step. Additionally, we present nCATRAs - a novel, amplification-free TnSeq method where the insertions are enriched via CRISPR/Cas9-targeted transposon cleavage and subsequent Oxford Nanopore MinION sequencing. nCATRAs achieved 54 and 23% enrichment of the transposons and transposon-genomic junctions, respectively, over background genomic DNA. These PCR-based and PCR-free experiments demonstrate that, overall, PCR amplification does not significantly bias the results of TnSeq insofar as insertions in the majority of genes represented in our library were similarly detected regardless of PCR cycle number and whether or not PCR amplification was employed. However, the detection of a small subset of genes which had been previously described as essential is sensitive to the number of PCR cycles. We conclude that PCR-based enrichment of transposon insertions in a TnSeq assay is reliable, but researchers interested in profiling putative essential genes should carefully weigh the number of amplification cycles employed in their library preparation protocols. In addition, nCATRAs is comparable to traditional PCR-based methods (Kendall's correlation=0.896-0.897) although the latter remain superior owing to their accessibility and high sequencing depth.

Mash-based analyses of Escherichia coli genomes reveal 14 distinct phylogroups.

In this study, more than one hundred thousand Escherichia coli and Shigella genomes were examined and classified. This is, to our knowledge, the largest E. coli genome dataset analyzed to date. A Mash-based analysis of a cleaned set of 10,667 E. coli genomes from GenBank revealed 14 distinct phylogroups. A representative genome or medoid identified for each phylogroup was used as a proxy to classify 95,525 unassembled genomes from the Sequence Read Archive (SRA). We find that most of the sequenced E. coli genomes belong to four phylogroups (A, C, B1 and E2(O157)). Authenticity of the 14 phylogroups is supported by several different lines of evidence: phylogroup-specific core genes, a phylogenetic tree constructed with 2613 single copy core genes, and differences in the rates of gene gain/loss/duplication. The methodology used in this work is able to reproduce known phylogroups, as well as to identify previously uncharacterized phylogroups in E. coli species.

Decoding the epitranscriptional landscape from native RNA sequences.

Traditional epitranscriptomics relies on capturing a single RNA modification by antibody or chemical treatment, combined with short-read sequencing to identify its transcriptomic location. This approach is labor-intensive and may introduce experimental artifacts. Direct sequencing of native RNA using Oxford Nanopore Technologies (ONT) can allow for directly detecting the RNA base modifications, although these modifications might appear as sequencing errors. The percent Error of Specific Bases (%ESB) was higher for native RNA than unmodified RNA, which enabled the detection of ribonucleotide modification sites. Based on the %ESB differences, we developed a bioinformatic tool, epitranscriptional landscape inferring from glitches of ONT signals (ELIGOS), that is based on various types of synthetic modified RNA and applied to rRNA and mRNA. ELIGOS is able to accurately predict known classes of RNA methylation sites (AUC > 0.93) in rRNAs from Escherichiacoli, yeast, and human cells, using either unmodified in vitro transcription RNA or a background error model, which mimics the systematic error of direct RNA sequencing as the reference. The well-known DRACH/RRACH motif was localized and identified, consistent with previous studies, using differential analysis of ELIGOS to study the impact of RNA m6A methyltransferase by comparing wild type and knockouts in yeast and mouse cells. Lastly, the DRACH motif could also be identified in the mRNA of three human cell lines. The mRNA modification identified by ELIGOS is at the level of individual base resolution. In summary, we have developed a bioinformatic software package to uncover native RNA modifications.

Two SARS-CoV-2 Genome Sequences of Isolates from Rural U.S. Patients Harboring the D614G Mutation, Obtained Using Nanopore Sequencing.

Two coding-complete sequences of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were obtained from samples from two patients in Arkansas, in the southeastern corner of the United States. The viral genome was obtained using the ARTIC Network protocol and Oxford Nanopore Technologies sequencing.

ProdMX: Rapid query and analysis of protein functional domain based on compressed sparse matrices.

Large-scale protein analysis has been used to characterize large numbers of proteins across numerous species. One of the applications is to use as a high-throughput screening method for pathogenicity of genomes. Unlike sequence homology methods, protein comparison at a functional level provides us with a unique opportunity to classify proteins, based on their functional structures without dealing with sequence complexity of distantly related species. Protein functions can be abstractly described by a set of protein functional domains, such as PfamA domains; a set of genomes can then be mapped to a matrix, with each row representing a genome, and the columns representing the presence or absence of a given functional domain. However, a powerful tool is needed to analyze the large sparse matrices generated by millions of genomes that will become available in the near future. The ProdMX is a tool with user-friendly utilities developed to facilitate high-throughput analysis of proteins with an ability to be included as an effective module in the high-throughput pipeline. The ProdMX employs a compressed sparse matrix algorithm to reduce computational resources and time used to perform the matrix manipulation during functional domain analysis. The ProdMX is a free and publicly available Python package which can be installed with popular package mangers such as PyPI and Conda, or with a standard installer from source code available on the ProdMX GitHub repository at https://github.com/visanuwan/prodmx.

Machine Learning Methods in Drug Discovery.

The advancements of information technology and related processing techniques have created a fertile base for progress in many scientific fields and industries. In the fields of drug discovery and development, machine learning techniques have been used for the development of novel drug candidates. The methods for designing drug targets and novel drug discovery now routinely combine machine learning and deep learning algorithms to enhance the efficiency, efficacy, and quality of developed outputs. The generation and incorporation of big data, through technologies such as high-throughput screening and high through-put computational analysis of databases used for both lead and target discovery, has increased the reliability of the machine learning and deep learning incorporated techniques. The use of these virtual screening and encompassing online information has also been highlighted in developing lead synthesis pathways. In this review, machine learning and deep learning algorithms utilized in drug discovery and associated techniques will be discussed. The applications that produce promising results and methods will be reviewed.

Two Cases of Vancomycin-Resistant Enterococcus faecium Bacteremia With Development of Daptomycin-Resistant Phenotype and its Detection Using Oxford Nanopore Sequencing.

In this work, we report 2 cases of vancomycin-resistant Enterococcus faecium bacteremia with development of daptomycin resistance in 2 patients with acute myeloid leukemia and myelodysplastic syndrome. Mutations related to daptomycin-nonsusceptible phenotype in liaSR genes were found in all strains of the study, including those with a minimum inhibitory concentration <1 µg/mL collected before daptomycin therapy. Epidemiological investigation using core genome single nucleotide polymorphism and core genome multilocus sequence typing revealed clonality of all the isolates. In this study, we conclude that real-time genome sequencing of clinical isolates can provide rapid access to timely information on daptomycin-resistant genotypes that would help clinicians speed up and optimize the selection of the antibiotic for treatment.

16S rRNA Gene Amplicon Profiling of Baby and Adult Captive Elephants in Thailand.

Here, we present a 16S rRNA gene amplicon sequence data set and profiles demonstrating the bacterial diversity of baby and adult elephants from four different geographical locations in Thailand. The dominant phyla among baby and adult elephants were Bacteroidetes, Firmicutes, Proteobacteria, Kiritimatiellaeota, Euryarchaeota, and Tenericutes.

A novel Cas9-targeted long-read assay for simultaneous detection of IDH1/2 mutations and clinically relevant MGMT methylation in fresh biopsies of diffuse glioma.

Molecular biomarkers provide both diagnostic and prognostic results for patients with diffuse glioma, the most common primary brain tumor in adults. Here, we used a long-read nanopore-based sequencing technique to simultaneously assess IDH mutation status and MGMT methylation level in 4 human cell lines and 8 fresh human brain tumor biopsies. Currently, these biomarkers are assayed separately, and results can take days to weeks. We demonstrated the use of nanopore Cas9-targeted sequencing (nCATS) to identify IDH1 and IDH2 mutations within 36 h and compared this approach against currently used clinical methods. nCATS was also able to simultaneously provide high-resolution evaluation of MGMT methylation levels not only at the promoter region, as with currently used methods, but also at CpGs across the proximal promoter region, the entirety of exon 1, and a portion of intron 1. We compared the methylation levels of all CpGs to MGMT expression in all cell lines and tumors and observed a positive correlation between intron 1 methylation and MGMT expression. Finally, we identified single nucleotide variants in 3 target loci. This pilot study demonstrates the feasibility of using nCATS as a clinical tool for cancer precision medicine.

Report of the 2019 NIST-FDA workshop on standards for next generation sequencing detection of viral adventitious agents in biologics and biomanufacturing.

Adventitious virus testing assures product safety by demonstrating the absence of viruses that could be unintentionally introduced during the manufacturing process. The capabilities of next-generation sequencing (NGS) for broad virus detection in biologics have been demonstrated by the detection of known and novel viruses that were previously missed using the recommended routine assays for adventitious agent testing. A meeting was co-organized by the National Institute of Standards and Technology and the U.S. Food and Drug Administration on September 18-19, 2019 in Gaithersburg, Maryland, USA, to facilitate standardization of NGS technologies for applications of adventitious virus testing in biologics. The goal was to assess the currently used standards for virus detection by NGS and their public availability, and to identify additional needs for different types of reference materials and standards (natural and synthetic). The meeting focused on the NGS processes from sample preparation through sequencing but did not thoroughly cover bioinformatics, since this was considered to be the topic of a separate meeting.

Complete Genome Sequences of Four Isolates of Vancomycin-Resistant Enterococcus faecium with the vanA Gene and Two Daptomycin Resistance Mutations, Obtained from Two Inpatients with Prolonged Bacteremia.

Here, we present complete genome sequences of four Enterococcus faecium isolates, obtained from two patients with apparent vancomycin-resistant Enterococcus faecium bacteremia; these isolates also carried two mutations known to be associated with daptomycin resistance. Sequences were obtained using de novo and hybrid assembly of Oxford Nanopore and Illumina sequence data.

Comparative genomics of hepatitis A virus, hepatitis C virus, and hepatitis E virus provides insights into the evolutionary history of Hepatovirus species.

The intraspecies genomic diversity of the single-strand RNA (+) virus species hepatitis A virus (Hepatovirus), hepatitis C virus (Hepacivirus), and hepatitis E virus (Orthohepevirus) was compared. These viral species all can cause liver inflammation (hepatitis), but share no gene similarity. The codon usage of human hepatitis A virus (HAV) is suboptimal for replication in its host, a characteristic it shares with taxonomically related rodent, simian, and bat hepatitis A virus species. We found this codon usage to be strikingly similar to that of Triatoma virus that infects blood-sucking kissing bugs. The codon usage of that virus is well adapted to its insect host. The codon usage of HAV is also similar to other invertebrate viruses of various taxonomic families. An evolutionary ancestor of HAV and related virus species is hypothesized to be an insect virus that underwent a host jump to infect mammals. The similarity between HAV and invertebrate viruses goes beyond codon usage, as they also share amino acid composition characteristics, while not sharing direct sequence homology. In contrast, hepatitis C virus and hepatitis E virus are highly similar in codon usage preference, nucleotide composition, and amino acid composition, and share these characteristics with Human pegivirus A, West Nile virus, and Zika virus. We present evidence that these observations are only partly explained by differences in nucleotide composition of the complete viral codon regions. We consider the combination of nucleotide composition, amino acid composition, and codon usage preference suitable to provide information on possible evolutionary similarities between distant virus species that cannot be investigated by phylogeny.

An assessment of Oxford Nanopore sequencing for human gut metagenome profiling: A pilot study of head and neck cancer patients.

Gut metagenome profiling using the Oxford Nanopore Technologies (ONT) sequencer was assessed in a pilot-sized study of 10 subjects. The taxonomic abundance of gut microbiota derived from ONT was comparable with Illumina Technology (IT) for the high-abundance species. IT better detected low-abundance species through amplification, when material was limited.