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DNA sequence analysis is undertaken in many biological research laboratories. The workflow consists of several steps involving the bioinformatic processing of biological data. We have developed a suite of web-based online bioinformatic tools to assist with processing, analysis and curation of DNA sequence data. Most of these tools are genome-agnostic, with two tools specifically designed for hepatitis B virus sequence data. Tools in the suite are able to process sequence data from Sanger sequencing, ultra-deep amplicon resequencing (pyrosequencing) and chromatograph (trace files), as appropriate. The tools are available online at no cost and are aimed at researchers without specialist technical computer knowledge. The tools can be accessed at http://hvdr.bioinf.wits.ac.za/SmallGenomeTools, and the source code is available online at https://github.com/DrTrevorBell/SmallGenomeTools. [ABSTRACT FROM AUTHOR]

Before COVID-19, digital divide research among college students was scarce, reinforcing the idea that technology access was nearly universal, with few demographic differences. Pandemic-era research found some technical challenges, but most studies were conducted nationally or at research-intensive (R1) universities, indicating a paucity in research among underrepresented populations, notably at Hispanic-Serving Institutions (HSI). This mixed-methods study aimed to assess digital inequities and pandemic-related technological challenges at an HSI, with high percentages of low-income and first-generation students. This study also sought to determine if findings were consistent with national and R1 research. We surveyed a representative sample of 2188 undergraduates and conducted semi-structured interviews with 26 students. Results showed many students had inadequate technology. Just 79% had the optimal combination of smartphone plus laptop or desktop, with first-generation, low-income, Black, and older students significantly less likely to have this combination and often having to share devices within their households. Internet quality significantly affected all coursework-related challenges, as almost half of students with unstable internet reported trouble completing assignments compared to 20% with stable internet. Finally, results suggest the digital divide may be more prevalent at HSIs than at previously studied institutions, while also offering insight into how these challenges affect similar universities. [ABSTRACT FROM AUTHOR]

While PCR amplicons extend to a few thousand bases, the length of sequences from direct Sanger sequencing is limited to 500-800 nucleotides. Therefore, several fragments may be required to cover an amplicon, a gene or an entire genome. These fragments are typically sequenced in an overlapping fashion and assembled by manually sliding and aligning the sequences visually. This is time-consuming, repetitive and error-prone, and further complicated by circular genomes. An online tool merging two to twelve long overlapping sequence fragments was developed. Either chromatograms or FASTA files are submitted to the tool, which trims poor quality ends of chromatograms according to user-specified parameters. Fragments are assembled into a single sequence by repeatedly calling the EMBOSS merger tool in a consecutive manner. Output includes the number of trimmed nucleotides, details of each merge, and an optional alignment to a reference sequence. The final merge sequence is displayed and can be downloaded in FASTA format. All output files can be downloaded as a ZIP archive. This tool allows for easy and automated assembly of overlapping sequences and is aimed at researchers without specialist computer skills. The tool is genome- and organism-agnostic and has been developed using hepatitis B virus sequence data. [ABSTRACT FROM AUTHOR]

Hepatitis B virus (HBV) is the primary cause of liver-related malignancies worldwide, and there is no effective cure for chronic HBV infection (CHB) currently. Strong immunological responses induced by T cells are associated with HBV clearance during acute infection; however, the repertoire of epitopes (epi) presented by major histocompatibility complexes (MHCs) to elicit these responses in various African populations is not well understood. In silico approaches were used to map and investigate 15-mers HBV peptides restricted to 9 HLA class II alleles with high population coverage in Botswana. Sequences from 44 HBV genotype A and 48 genotype D surface genes (PreS/S) from Botswana were used. Of the 1819 epi bindings predicted, 20.2% were strong binders (SB), and none of the putative epi bind to all the 9 alleles suggesting that multi-epitope, genotype-based, population-based vaccines will be more effective against HBV infections as opposed to previously proposed broad potency epitope-vaccines which were assumed to work for all alleles. In total, there were 297 unique epi predicted from the 3 proteins and amongst, S regions had the highest number of epi (n = 186). Epitope-densities (Depi) between genotypes A and D were similar. A number of mutations that hindered HLA-peptide binding were observed. We also identified antigenic and genotype-specific peptides with characteristics that are well suited for the development of sensitive diagnostic kits. This study identified candidate peptides that can be used for developing multi-epitope vaccines and highly sensitive diagnostic kits against HBV infection in an African population. Our results suggest that viral variability may hinder HBV peptide-MHC binding, required to initiate a cascade of immunological responses against infection. [ABSTRACT FROM AUTHOR]

Seabed sediment composition is an important component of benthic habitat and there are many approaches for producing maps that convey sediment information to marine managers. Random Forest is a popular statistical method for thematic seabed sediment mapping using both categorical and quantitative supervised modelling approaches. This study compares the performance and qualities of these Random Forest approaches to predict the distribution of fine-grained sediments from grab samples as one component of a multi-model map of sediment classes in Frobisher Bay, Nunavut, Canada. The second component predicts the presence of coarse substrates from underwater video. Spatial and non-spatial cross-validations were conducted to evaluate the performance of categorical and quantitative Random Forest models and maps were compared to determine differences in predictions. While both approaches seemed highly accurate, the non-spatial cross-validation suggested greater accuracy using the categorical approach. Using a spatial cross-validation, there was little difference between approaches—both showed poor extrapolative performance. Spatial cross-validation methods also suggested evidence of overfitting in the coarse sediment model caused by the spatial dependence of transect samples. The quantitative modelling approach was able to predict rare and unsampled sediment classes but the flexibility of probabilistic predictions from the categorical approach allowed for tuning to maximize extrapolative performance. Results demonstrate that the apparent accuracies of these models failed to convey important differences between map predictions and that spatially explicit evaluation strategies may be necessary for evaluating extrapolative performance. Differentiating extrapolative from interpolative prediction can aid in selecting appropriate modelling methods. [ABSTRACT FROM AUTHOR]

The World Health Organization plans to eliminate hepatitis B and C Infections by 2030. Therefore, there is a need to study and understand hepatitis B virus (HBV) epidemiology and viral evolution further, including evaluating occult (HBsAg-negative) HBV infection (OBI), given that such infections are frequently undiagnosed and rarely treated. We aimed to molecularly characterize HBV genomes from 108 individuals co-infected with human immunodeficiency virus (HIV) and chronic hepatitis B (CHB) or OBI identified from previous HIV studies conducted in Botswana from 2009 to 2012. Full-length (3.2 kb) and nearly full-length (~3 kb) genomes were amplified by nested polymerase chain reaction (PCR). Sequences from OBI participants were compared to sequences from CHB participants and GenBank references to identify OBI-unique mutations. HBV genomes from 50 (25 CHB and 25 OBI) individuals were successfully genotyped. Among OBI participants, subgenotype A1 was identified in 12 (48%), D3 in 12 (48%), and E in 1 (4%). A similar genotype distribution was observed in CHB participants. Whole HBV genome sequences from Botswana, representing OBI and CHB, were compared for the first time. There were 43 OBI-unique mutations, of which 26 were novel. Future studies using larger sample sizes and functional analysis of OBI-unique mutations are warranted. [ABSTRACT FROM AUTHOR]

Occult hepatitis B infections (OBI) represent a reservoir of undiagnosed and untreated hepatitis B virus (HBV), hence the need to identify mutations that lead to this phenotype. Functionally characterizing these mutations by in vitro studies is time-consuming and expensive. To bridge this gap, in silico approaches, which predict the effect of amino acid (aa) variants on HBV protein function, are necessary. We developed an algorithm for determining the relevance of OBI-associated mutations using in silico approaches. A 3 kb fragment of subgenotypes A1 and D3 from 24 chronic HBV-infected (CHB) and 24 OBI participants was analyzed. To develop and validate the algorithm, the effects of 68 previously characterized occult-associated mutations were determined using three computational tools: PolyPhen2, SNAP2, and PROVEAN. The percentage of deleterious mutations (with impact on protein function) predicted were 52 (76.5%) by PolyPhen2, 55 (80.9%) by SNAP2, and 65 (95.6%) by PROVEAN. At least two tools correctly predicted 59 (86.8%) mutations as deleterious. To identify OBI-associated mutations exclusive to Botswana, study sequences were compared to CHB sequences from GenBank. Of the 43 OBI-associated mutations identified, 26 (60.5%) were predicted by at least two tools to have an impact on protein function. To our knowledge, this is the first study to use in silico approaches to determine the impact of OBI-associated mutations, thereby identifying potential candidates for functional analysis to facilitate mechanistic studies of the OBI phenotype. [ABSTRACT FROM AUTHOR]

The World Health Organization plans to eliminate hepatitis B and C Infections by 2030. Therefore, there is a need to study and understand hepatitis B virus (HBV) epidemiology and viral evolution further, including evaluating occult (HBsAg-negative) HBV infection (OBI), given that such infections are frequently undiagnosed and rarely treated. We aimed to molecularly characterize HBV genomes from 108 individuals co-infected with human immunodeficiency virus (HIV) and chronic hepatitis B (CHB) or OBI identified from previous HIV studies conducted in Botswana from 2009 to 2012. Full-length (3.2 kb) and nearly full-length (~3 kb) genomes were amplified by nested polymerase chain reaction (PCR). Sequences from OBI participants were compared to sequences from CHB participants and GenBank references to identify OBI-unique mutations. HBV genomes from 50 (25 CHB and 25 OBI) individuals were successfully genotyped. Among OBI participants, subgenotype A1 was identified in 12 (48%), D3 in 12 (48%), and E in 1 (4%). A similar genotype distribution was observed in CHB participants. Whole HBV genome sequences from Botswana, representing OBI and CHB, were compared for the first time. There were 43 OBI-unique mutations, of which 26 were novel. Future studies using larger sample sizes and functional analysis of OBI-unique mutations are warranted.

Occult hepatitis B infections (OBI) represent a reservoir of undiagnosed and untreated hepatitis B virus (HBV), hence the need to identify mutations that lead to this phenotype. Functionally characterizing these mutations by in vitro studies is time-consuming and expensive. To bridge this gap, in silico approaches, which predict the effect of amino acid (aa) variants on HBV protein function, are necessary. We developed an algorithm for determining the relevance of OBI-associated mutations using in silico approaches. A 3 kb fragment of subgenotypes A1 and D3 from 24 chronic HBV-infected (CHB) and 24 OBI participants was analyzed. To develop and validate the algorithm, the effects of 68 previously characterized occult-associated mutations were determined using three computational tools: PolyPhen2, SNAP2, and PROVEAN. The percentage of deleterious mutations (with impact on protein function) predicted were 52 (76.5%) by PolyPhen2, 55 (80.9%) by SNAP2, and 65 (95.6%) by PROVEAN. At least two tools correctly predicted 59 (86.8%) mutations as deleterious. To identify OBI-associated mutations exclusive to Botswana, study sequences were compared to CHB sequences from GenBank. Of the 43 OBI-associated mutations identified, 26 (60.5%) were predicted by at least two tools to have an impact on protein function. To our knowledge, this is the first study to use in silico approaches to determine the impact of OBI-associated mutations, thereby identifying potential candidates for functional analysis to facilitate mechanistic studies of the OBI phenotype.