Amogelang R. Raphenya

Bio: Amogelang R. Raphenya is an academic researcher from McMaster University. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 10, co-authored 18 publications receiving 2123 citations. Previous affiliations of Amogelang R. Raphenya include BC Cancer Research Centre.

CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database

Abstract: The Comprehensive Antibiotic Resistance Database (CARD; http://arpcardmcmasterca) is a manually curated resource containing high quality reference data on the molecular basis of antimicrobial resistance (AMR), with an emphasis on the genes, proteins and mutations involved in AMR CARD is ontologically structured, model centric, and spans the breadth of AMR drug classes and resistance mechanisms, including intrinsic, mutation-driven and acquired resistance It is built upon the Antibiotic Resistance Ontology (ARO), a custom built, interconnected and hierarchical controlled vocabulary allowing advanced data sharing and organization Its design allows the development of novel genome analysis tools, such as the Resistance Gene Identifier (RGI) for resistome prediction from raw genome sequence Recent improvements include extensive curation of additional reference sequences and mutations, development of a unique Model Ontology and accompanying AMR detection models to power sequence analysis, new visualization tools, and expansion of the RGI for detection of emergent AMR threats CARD curation is updated monthly based on an interplay of manual literature curation, computational text mining, and genome analysis

CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database

Abstract: The Comprehensive Antibiotic Resistance Database (CARD; https://card.mcmaster.ca) is a curated resource providing reference DNA and protein sequences, detection models and bioinformatics tools on the molecular basis of bacterial antimicrobial resistance (AMR). CARD focuses on providing high-quality reference data and molecular sequences within a controlled vocabulary, the Antibiotic Resistance Ontology (ARO), designed by the CARD biocuration team to integrate with software development efforts for resistome analysis and prediction, such as CARD's Resistance Gene Identifier (RGI) software. Since 2017, CARD has expanded through extensive curation of reference sequences, revision of the ontological structure, curation of over 500 new AMR detection models, development of a new classification paradigm and expansion of analytical tools. Most notably, a new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes. By adding these resistance variants to CARD, we are able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants. Here, we describe updates and recent expansions to CARD and its biocuration process, including new resources for community biocuration of AMR molecular reference data.

Metformin-induced increases in GDF15 are important for suppressing appetite and promoting weight loss

Abstract: Metformin is the most commonly prescribed medication for type 2 diabetes, owing to its glucose-lowering effects, which are mediated through the suppression of hepatic glucose production (reviewed in refs. 1-3). However, in addition to its effects on the liver, metformin reduces appetite and in preclinical models exerts beneficial effects on ageing and a number of diverse diseases (for example, cognitive disorders, cancer, cardiovascular disease) through mechanisms that are not fully understood1-3. Given the high concentration of metformin in the liver and its many beneficial effects beyond glycemic control, we reasoned that metformin may increase the secretion of a hepatocyte-derived endocrine factor that communicates with the central nervous system4. Here we show, using unbiased transcriptomics of mouse hepatocytes and analysis of proteins in human serum, that metformin induces expression and secretion of growth differentiating factor 15 (GDF15). In primary mouse hepatocytes, metformin stimulates the secretion of GDF15 by increasing the expression of activating transcription factor 4 (ATF4) and C/EBP homologous protein (CHOP; also known as DDIT3). In wild-type mice fed a high-fat diet, oral administration of metformin increases serum GDF15 and reduces food intake, body mass, fasting insulin and glucose intolerance; these effects are eliminated in GDF15 null mice. An increase in serum GDF15 is also associated with weight loss in patients with type 2 diabetes who take metformin. Although further studies will be required to determine the tissue source(s) of GDF15 produced in response to metformin in vivo, our data indicate that the therapeutic benefits of metformin on appetite, body mass and serum insulin depend on GDF15.

Isolation, Sequence, Infectivity, and Replication Kinetics of Severe Acute Respiratory Syndrome Coronavirus 2.

Abstract: Since its emergence in Wuhan, China, in December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected ≈6 million persons worldwide As SARS-CoV-2 spreads across the planet, we explored the range of human cells that can be infected by this virus We isolated SARS-CoV-2 from 2 infected patients in Toronto, Canada; determined the genomic sequences; and identified single-nucleotide changes in representative populations of our virus stocks We also tested a wide range of human immune cells for productive infection with SARS-CoV-2 We confirm that human primary peripheral blood mononuclear cells are not permissive for SARS-CoV-2 As SARS-CoV-2 continues to spread globally, it is essential to monitor single-nucleotide polymorphisms in the virus and to continue to isolate circulating viruses to determine viral genotype and phenotype by using in vitro and in vivo infection models

Failed Recovery of Glycemic Control and Myofibrillar Protein Synthesis With 2 wk of Physical Inactivity in Overweight, Prediabetic Older Adults.

Abstract: Background Physical inactivity impairs insulin sensitivity, which is exacerbated with aging. We examined the impact of 2 wk of acute inactivity and recovery on glycemic control, and integrated rates of muscle protein synthesis in older men and women. Methods Twenty-two overweight, prediabetic older adults (12 men, 10 women, 69 ± 4 y) undertook 7 d of habitual activity (baseline; BL), step reduction (SR; <1,000 steps.d-1 for 14 d), followed by 14 d of recovery (RC). An oral glucose tolerance test was used to assess glycemic control and deuterated water ingestion to measure integrated rates of muscle protein synthesis. Results Daily step count was reduced (all p < .05) from BL at SR (7362 ± 3294 to 991 ± 97) and returned to BL levels at RC (7117 ± 3819). Homeostasis model assessment-insulin resistance increased from BL to SR and Matsuda insulin sensitivity index decreased and did not return to BL in RC. Glucose and insulin area under the curve were elevated from BL to SR and did not recover in RC. Integrated muscle protein synthesis was reduced during SR and did not return to BL in RC. Conclusions Our findings demonstrate that 2 wk of SR leads to lowered rates of muscle protein synthesis and a worsening of glycemic control that unlike younger adults is not recovered during return to normal activity in overweight, prediabetic elderly humans. Clinical Trials Registration ClinicalTrials.gov identifier: NCT03039556.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database

Abstract: The Comprehensive Antibiotic Resistance Database (CARD; https://card.mcmaster.ca) is a curated resource providing reference DNA and protein sequences, detection models and bioinformatics tools on the molecular basis of bacterial antimicrobial resistance (AMR). CARD focuses on providing high-quality reference data and molecular sequences within a controlled vocabulary, the Antibiotic Resistance Ontology (ARO), designed by the CARD biocuration team to integrate with software development efforts for resistome analysis and prediction, such as CARD's Resistance Gene Identifier (RGI) software. Since 2017, CARD has expanded through extensive curation of reference sequences, revision of the ontological structure, curation of over 500 new AMR detection models, development of a new classification paradigm and expansion of analytical tools. Most notably, a new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes. By adding these resistance variants to CARD, we are able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants. Here, we describe updates and recent expansions to CARD and its biocuration process, including new resources for community biocuration of AMR molecular reference data.

IslandViewer 4: expanded prediction of genomic islands for larger-scale datasets.

Abstract: IslandViewer (http://www.pathogenomics.sfu.ca/islandviewer/) is a widely-used webserver for the prediction and interactive visualization of genomic islands (GIs, regions of probable horizontal origin) in bacterial and archaeal genomes. GIs disproportionately encode factors that enhance the adaptability and competitiveness of the microbe within a niche, including virulence factors and other medically or environmentally important adaptations. We report here the release of IslandViewer 4, with novel features to accommodate the needs of larger-scale microbial genomics analysis, while expanding GI predictions and improving its flexible visualization interface. A user management web interface as well as an HTTP API for batch analyses are now provided with a secured authentication to facilitate the submission of larger numbers of genomes and the retrieval of results. In addition, IslandViewer's integrated GI predictions from multiple methods have been improved and expanded by integrating the precise Islander method for pre-computed genomes, as well as an updated IslandPath-DIMOB for both pre-computed and user-supplied custom genome analysis. Finally, pre-computed predictions including virulence factors and antimicrobial resistance are now available for 6193 complete bacterial and archaeal strains publicly available in RefSeq. IslandViewer 4 provides key enhancements to facilitate the analysis of GIs and better understand their role in the evolution of successful environmental microbes and pathogens.

Genetic compensation induced by deleterious mutations but not gene knockdowns

Abstract: Cells sense their environment and adapt to it by fine-tuning their transcriptome. Wired into this network of gene expression control are mechanisms to compensate for gene dosage. The increasing use of reverse genetics in zebrafish, and other model systems, has revealed profound differences between the phenotypes caused by genetic mutations and those caused by gene knockdowns at many loci, an observation previously reported in mouse and Arabidopsis. To identify the reasons underlying the phenotypic differences between mutants and knockdowns, we generated mutations in zebrafish egfl7, an endothelial extracellular matrix gene of therapeutic interest, as well as in vegfaa. Here we show that egfl7 mutants do not show any obvious phenotypes while animals injected with egfl7 morpholino (morphants) exhibit severe vascular defects. We further observe that egfl7 mutants are less sensitive than their wild-type siblings to Egfl7 knockdown, arguing against residual protein function in the mutants or significant off-target effects of the morpholinos when used at a moderate dose. Comparing egfl7 mutant and morphant proteomes and transcriptomes, we identify a set of proteins and genes that are upregulated in mutants but not in morphants. Among them are extracellular matrix genes that can rescue egfl7 morphants, indicating that they could be compensating for the loss of Egfl7 function in the phenotypically wild-type egfl7 mutants. Moreover, egfl7 CRISPR interference, which obstructs transcript elongation and causes severe vascular defects, does not cause the upregulation of these genes. Similarly, vegfaa mutants but not morphants show an upregulation of vegfab. Taken together, these data reveal the activation of a compensatory network to buffer against deleterious mutations, which was not observed after translational or transcriptional knockdown.