Background Uganda remains one of the countries with the highest burden of TB/HIV. Drug-resistant TB remains a substantial challenge to TB control globally and requires new strategic effective control approaches. Drug resistance usually develops due to inadequate management of TB patients including improper treatment regimens and failure to complete the treatment course which may be due to an unstable supply or a lack of access to treatment, as well as patient noncompliance. Methods Two sputa samples were collected from Xpert MTB/RIF® assay-diagnosed multi-drug resistant tuberculosis (MDR-TB) patient at Lira regional referral hospital in northern Uganda between 2020 and 2021 for comprehensive routine mycobacterial species identification and drug susceptibility testing using culture-based methods. Detection of drug resistance-conferring genes was subsequently performed using whole-genome sequencing with Illumina MiSeq platform at the TB Supranational Reference Laboratory in Uganda. Results In both isolates, extensively drug-resistant TB (XDR-TB) was identified including resistance to Isoniazid (katG p.Ser315Thr), Rifampicin (rpoB p.Ser450Leu), Moxifloxacin (gyrA p.Asp94Gly), Bedaquiline (Rv0678 Glu49fs), Clofazimine (Rv0678 Glu49fs), Linezolid (rplC Cys154Arg), and Ethionamide (ethA c.477del). Further analysis of these two high quality genomes revealed that this 32 years-old patient was infected with the Latin American Mediterranean TB strain (LAM). Conclusions This is the first identification of extensively drug-resistant Mycobacterium tuberculosis clinical isolates with bedaquiline, linezolid and clofazimine resistance from Uganda. These acquired resistances were because of non-adherence as seen in the patient’s clinical history. Our study also strongly highlights the importance of combating DR-TB in Africa through implementing next generation sequencing that can test resistance to all drugs while providing a faster turnaround time. This can facilitate timely clinical decisions in managing MDR-TB patients with non-adherence or lost to follow-up.

Background: In January 2020, a previously unknown coronavirus strain was identified as the cause of a severe acute respiratory syndrome (SARS-CoV-2). The first viral whole-genome was sequenced using high-throughput sequencing from a sample collected in Wuhan, China. Whole-genome sequencing (WGS) is imperative in investigating disease outbreak transmission dynamics and guiding decision-making in public health. Methods: We retrieved archived SARS-CoV-2 samples at the Integrated Biorepository of H3Africa Uganda, Makerere University (IBRH3AU). These samples were collected previously from individuals diagnosed with coronavirus disease 2019 (COVID-19) using real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR). 30 samples with cycle thresholds (Cts) values <25 were selected for WGS using SARS-CoV-2 ARTIC protocol at Makerere University Molecular Diagnostics Laboratory. Results: 28 out of 30 (93.3%) samples generated analyzable genomic sequence reads. We detected SARS-CoV-2 and lineages A (22/28) and B (6/28) from the samples. We further show phylogenetic relatedness of these isolates alongside other 328 Uganda (lineage A = 222, lineage B = 106) SARS-CoV-2 genomes available in GISAID by April 22, 2021 and submitted by the Uganda Virus Research Institute. Conclusions: Our study demonstrated adoption and optimization of the low-cost ARTIC SARS-CoV-2 WGS protocol in a resource limited laboratory setting. This work has set a foundation to enable rapid expansion of SARS-CoV-2 WGS in Uganda as part of the Presidential Scientific Initiative on Epidemics (PRESIDE) CoV-bank project and IBRH3AU.

Background Mycobacterium tuberculosis presents several lineages each with distinct characteristics of evolutionary status, transmissibility, drug resistance, host interaction, latency, and vaccine efficacy. Whole genome sequencing (WGS) has emerged as a new diagnostic tool to reliably inform the occurrence of phylogenetic lineages of Mycobacterium tuberculosis and examine their relationship with patient demographic characteristics and multidrug-resistance development. Methods 191 Mycobacterium tuberculosis isolates obtained from a 2017/2018 Tanzanian drug resistance survey were sequenced on the Illumina Miseq platform at Supranational Tuberculosis Reference Laboratory in Uganda. Obtained fast-q files were imported into tools for resistance profiling and lineage inference (Kvarq v0.12.2, Mykrobe v0.8.1 and TBprofiler v3.0.5). Additionally for phylogenetic tree construction, RaxML-NG v1.0.3(25) was used to generate a maximum likelihood phylogeny with 800 bootstrap replicates. The resulting trees were plotted, annotated and visualized using ggtree v2.0.4 Results Most [172(90.0%)] of the isolates were from newly treated Pulmonary TB patients. Coinfection with HIV was observed in 33(17.3%) TB patients. Of the 191 isolates, 22(11.5%) were resistant to one or more commonly used first line anti-TB drugs (FLD), 9(4.7%) isolates were MDR-TB while 3(1.6%) were resistant to all the drugs. Of the 24 isolates with any resistance conferring mutations, 13(54.2%) and 10(41.6%) had mutations in genes associated with resistance to INH and RIF respectively. The findings also show four major lineages i.e. Lineage 3[81 (42.4%)], followed by Lineage 4 [74 (38.7%)], the Lineage 1 [23 (12.0%)] and Lineages 2 [13 (6.8%)] circulaing in Tanzania. Conclusion The findings in this study show that Lineage 3 is the most prevalent lineage in Tanzania whereas drug resistant mutations were more frequent among isolates that belonged to Lineage 4.

Antimicrobial resistance (AMR) in Neisseria gonorrhoeae (NG), compromising gonorrhea treatment, is a global public health concern. Improved, quality-assured NG AMR monitoring at the global level is essential. This mini-review examined NG AMR susceptibility surveillance and AMR data from the African continent from 2001 to 2020. Eligible peer-reviewed publications (n = 30) containing NG AMR data for antimicrobials currently recommended for gonorrhea treatment were included. Overall, very limited NG surveillance and AMR data was available. Furthermore, the NG AMR surveillance studies varied greatly regarding surveillance protocols (e.g., populations and samples tested, sample size, antimicrobials examined), methodologies (e.g., antimicrobial susceptibility testing method [agar dilution, minimum inhibitory concentration (MIC) gradient strip test, disc diffusion test] and interpretative criteria), and quality assurance (internal quality controls, external quality assessments [EQA], and verification of AMR detected). Moreover, most studies examined a suboptimal number of NG isolates, i.e., less than the WHO Global Gonococcal Antimicrobial Surveillance Program (GASP) and WHO Enhanced GASP (EGASP) recommendations of ≥100 isolates per setting and year. The notable inter-study variability and frequently small sample sizes make appropriate inter-study and inter-country comparisons of AMR data difficult. In conclusion, it is imperative to establish an enhanced, standardized and quality-assured NG AMR surveillance, ideally including patient metadata and genome sequencing as in WHO EGASP, in Africa, the region with the highest gonorrhea incidence globally. This will enable the monitoring of AMR trends, detection of emerging AMR, and timely refinements of national and international gonorrhea treatment guidelines. To achieve this aim, national and international leadership, political and financial commitments are imperative.

Background: The emergence and spread of antiretroviral drug resistant HIV-1 variants is one of the major factors associated with therapeutic failure in persons living with HIV (PLWH) as it jeopardizes the efforts to reduce the progression to AIDS. Whereas Sanger sequencing is the most appropriate conventional method for HIV drug resistance testing, it has limited capacity to detect low-abundance variants. This study assessed the suitability of next generation sequencing (NGS) to reveal low-abundance HIV-1 drug resistance mutations amongst patients experiencing virological failure at the time of therapy switching in Uganda. Methods: Archived blood samples previously collected from 60 PLWH were used in this study. Briefly HIV viral RNA was extracted and performed targeted NGS of portions of both the HIV protease and reverse transcriptase genes on the illumina MiSeq. For performance comparison, Sanger sequencing was also performed for all the samples targeting the highlighted genes. The sequence data generated was analyzed using HyDRA bioinformatics pipeline, accompanied by the Stanford HIV drug resistance database, to annotate and report drug resistance mutations/variants. Results: Out of the 60 samples, 58 passed preliminary quality control and were considered for subsequent analysis—of which 38/58 (65.5%) registered low-abundance HIV drug resistance variants. Overall, 757 variants from the NGS data and 90 variants from the Sanger data were identified. The most prevalent minority variants included; K65R (65.5%), K14R (63.8%), K45R (63.8%), L63P (63.8%), I15V (63.8%), K70R (60.3%), V77I (60.3%), L283I (60.3%), G16E (58.6%) and L282C (58.6%). Conclusion: An estimated 65.5% of the sampled population harbors low-abundance HIV-1 variants, most of which are associated with virological failure, and consequently antiviral drug resistance. NGS suitably detects drug resistance mutations even at frequencies below 20% of the viral quasi species that are occasionally missed by Sanger sequencing.