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Oluniyi, P.

Publications and source records attributed to Oluniyi, P..

2 recordsLinked to original sources

Genomic sequence analysis of the first mpox virus detected in Kenya

Mpox is a zoonotic disease caused by the Monkeypox virus (MPXV) in the family: Poxviridae, genus: Orthopoxvirus. Historically, the disease was restricted mostly to Africa with cases being reported in Central Africa (mostly caused by clade I) and in West Africa (caused by clade II). However, there has been a recent shift in the virus range with outbreaks being reported in Europe and America, and in countries where the virus was initially not endemic. This multi-country outbreak was driven mostly by clade IIb lineage of MPXV. Since December 2023, there has been an ongoing mpox outbreak in the Democratic Republic of Congo (DRC), driven by a new clade I lineage of the virus, designated clade Ib. The DRC outbreak has persisted, with an increase in cases being reported over the past few months. Spillover of these outbreak-related cases to the neighbouring countries have also been reported in multiple countries including Uganda and Rwanda. Here, we report the rapid application of unbiased metagenomic next generation sequencing (mNGS) to reconstruct the genome sequence of the first reported case of MPXV in Kenya. Our findings show that the Kenyan case clusters together with clade Ib MPXV strains, associated with the sustained outbreak in the DRC. Clade Ib lineage has been associated with continuing geographical expansion of the virus to previously unaffected areas, high incidence of the disease as well as high case fatality (CFR 4.9-6.7%). Similar to other clade Ib strains, the Kenyan strain carries predominant APOBEC3-type mutations which is characteristic feature of human-to-human transmission, highlighting the need for surveillance to curtail any potential expansion of this MPXV strain. The lack of information on genomes associated with cases reported in different East African countries, is a gap that urgently needs to be addressed to aid in the monitoring of this MPXV strain. This case investigation, therefore, underscores the need for sequencing efforts to be enhanced across the continent to help improve our understanding of the geographical range and diversity of the MPXV strains, especially those belonging to clade I which is currently under-represented.

genomics↗

hAMRonization: Enhancing antimicrobial resistance prediction using the PHA4GE AMR detection specification and tooling

The detection of antimicrobial resistance (AMR) markers directly from genomic or metagenomic data is becoming a standard clinical and public health procedure. This has resulted in the development of a number of different bioinformatic AMR prediction tools. Although many may implement similar principles, these tools differ significantly in their supported inputs, search algorithms, parameterisation, and underlying reference databases. Each of these tools generates a report of detected AMR genes or variants in a distinct, non-standard, format. This presents a huge barrier to the comparison of results and to the modularity of tools for AMR gene prediction within bioinformatic workflows. In collaboration with 17 public health laboratories across 10 countries, the Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) data structures working group has developed and piloted a standardized output specification for the bioinformatic detection of AMR from microbial genomes. In this report, we discuss hAMRonization, a python package and command-line utility, which implements PHA4GEs AMR specification to combine the outputs of disparate antimicrobial resistance gene detection tools into a single unified format. hAMRonization can be easily extended and currently supports 18 different tools (both species-agnostic and species-specific) for the detection of genes and/or variants conferring AMR. The harmonized reports are available in tabular form, JSON format or through an interactive HTML file (e.g., https://maguire-lab.github.io/assets/interactive_report_demo.html) that can be opened within the browser for navigable data exploration. As of 2024-03-07 hAMRonization has been downloaded [~]12,500 times, incorporated into >9 public bioinformatic tools and workflows, and been internally adopted by several national and international public health groups. The hAMRonization tool and underlying specification are open-source and freely available through PyPI, conda and GitHub (https://github.com/pha4ge/hAMRonization).

bioinformatics↗