BACKGROUND
Two sub variants (BA.4 and BA.5) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant are concerning as they are spreading rapidly worldwide; however, no published data concerning these variants are available in Cameroon. We report the early detection of these new sub variants that are associated with the onset of the fifth wave of coronavirus 2019 (COVID-19) in Cameroon.
METHODS
Positive samples were selected for next-generation sequencing (NGS). BA.4 and BA.5 complete genome sequences underwent sequence data analysis, epidemiology analysis of COVID-19’s resurgence and wave, recombination and pairwise matrix analysis, and phylogenetic analysis. We selected the first nine SARS-CoV-2 Omicron BA.4 and BA.5 sub variants detected in Cameroon using local whole genome sequencing for the NGS analysis.
RESULTS
During the fifth wave of resurgence of COVID-19 cases in Cameroon, it was found that the Northwest and Littoral regions were the most affected areas, while the Center and Littoral regions recorded the highest number of new deaths. The study identified evidence of recombination between the BA.2 sub variant and BA.4 and BA.5 Cameroonian strains. This result highlights the dynamic nature of SARS-CoV-2 evolution. The BA.5 strain (entitled hCoV-19/Cameroon/23850/2022) showed the highest sequence similarity to the first reported genome of the Omicron strain with 497 mutations. Phylogenetic analysis revealed that these nine Omicron sub variants were grouped into a distinct and highly distant cluster separate from the first Omicron variant detected in Botswana and were intermixed with sequences from other countries (the United States, Denmark, Scotland, and England), thus implying multiple introductions of the BA.4 and BA.5 sub variants in Cameroon.
CONCLUSIONS
Omicron BA.4 and BA.5 sub-lineages are associated with the onset of the fifth wave of COVID-19 in Cameroon. In addition to providing early warning of COVID-19 resurgence, continuous local genome sequencing of emerging variants is essential for detecting variants of concern, thereby guiding the country's response. This study emphasizes the value of real-time surveillance.
BACKGROUND
Nipah virus (NiV), a highly lethal virus in humans, circulates in Pteropus bats throughout South and Southeast Asia. Difficulty in obtaining viral genomes from bats means we have a poor understanding of NiV diversity.
METHODS
We develop phylogenetic approaches applied to the most comprehensive collection of genomes to date (N = 257, 175 from bats, 73 from humans) from 6 countries over 22 years (1999–2020). We divide the 4 major NiV sublineages into 15 genetic clusters. Using Approximate Bayesian Computation fit to a spatial signature of viral diversity, we estimate the presence and the average size of genetic clusters per area.
RESULTS
We find that, within any bat roost, there are an average of 2.4 co-circulating genetic clusters, rising to 5.5 clusters at areas of 1500–2000 km2. We estimate that each genetic cluster occupies an average area of 1.3 million km2 (95% confidence interval [CI], .6–2.3 million km2), with 14 clusters in an area of 100 000 km2 (95% CI, 6–24 km2). In the few sites in Bangladesh and Cambodia where genomic surveillance has been concentrated, we estimate that most clusters have been identified, but only approximately 15% of overall NiV diversity has been uncovered.
CONCLUSIONS
Our findings are consistent with entrenched co-circulation of distinct lineages, even within roosts, coupled with slow migration over larger spatial scales.
Malaria genetic diversity is an important indicator of malaria transmission. Pfmsp1 and pfmsp2 are a frequent molecular epidemiology tool to assess the genetic diversity. This study aims to assess the genetic diversity and the description of multiplicity of infection (MOI) of P. falciparum in Yambio County, South Sudan. Additionally, it assesses the association of specific alleles or multiplicity of infection with antimalarial drugs resistance haplotypes and severity of infection, major challenges in malaria control strategies.
METHODS
There were collected 446 malaria samples from patients in Yambio county. After P. falciparum confirmation, pfmsp1 and pfmsp2 allelic families were genotyped. Frequencies of each alleles were described and multiplicity of infection was calculated. The association between MOI and complicated malaria was assessed using U-Mann Whitney test. The Kruskal-Wallis test was used to compare MOI between collection sites, age groups and antimalarial resistance haplotypes.
RESULTS
For pfmsp1, monomorphic K1 allele infection was predominant (37.0%) in every location and for pfmsp2 locus, monomorphic 3D7 was predominant (44.8%). 71.9% of samples were polyclonal infections (overall MOI = 1.96). The high diversity and polyclonal infections are associated with molecular markers of resistance, and high MOI has been related with a lower risk of severity of infections. There was not find evidence of association between a specific allele and an infection trait.
CONCLUSION
High genetic diversity and high level of polyclonal infections have been found in this study, confirming the general high transmission, and highlighting the need for control measures to be intensified in Yambio county, South Sudan.
Children with severe acute malnutrition are treated with antibiotics as outpatients. We aimed to determine the effect of 7 days of amoxicillin on acute and long-term changes to the gut microbiome and antibiotic resistome in children treated for severe acute malnutrition.
METHODS
We conducted a secondary analysis of a randomised, double-blinded, placebo-controlled trial (NCT01613547) of amoxicillin in children (aged 6-59 months) with severe acute malnutrition treated as outpatients in Madarounfa, Niger. We randomly selected 161 children from the overall cohort (n=2399) for initial 12-week follow-up from Sept 23, 2013 to Feb 3, 2014. We selected a convenience sample of those 161 children, on the basis of anthropometric measures, for follow-up 2 years later (Sept 28 to Oct 27, 2015). Children provided faecal samples at baseline, week 1, week 4, week 8, week 12, and, for those in the 2-year follow-up cohort, week 104. We conducted metagenomic sequencing followed by microbiome and resistome profiling of faecal samples. 38 children without severe acute malnutrition and six children with severe acute malnutrition matching the baseline ages of the original cohort were used as reference controls.
FINDINGS
In the 12-week follow-up group, amoxicillin led to an immediate decrease in gut microbiome richness from 37·6 species (95% CI 32·6-42·7) and Shannon diversity index (SDI) 2·18 (95% CI 1·97-2·39) at baseline to 27·7 species (95% CI 22·9-32·6) species and SDI 1·55 (95% CI 1·35-1·75) at week 1. Amoxicillin increased gut antibiotic resistance gene abundance to 6044 reads per kilobase million (95% CI 4704-7384) at week 1, up from 4800 (3391-6208) at baseline, which returned to baseline 3 weeks later. 35 children were included in the 2-year follow-up; the amoxicillin-treated children (n=22) had increased number of species in the gut microbiome compared with placebo-treated children (n=13; 60·7 [95% CI 54·7-66·6] vs 36·9 [29·4-44·3]). Amoxicillin-treated children had increased Prevotella spp and decreased Bifidobacterium spp relative to age-matched placebo-treated children, indicating a more mature, adult-like microbiome.
INTERPRETATION
Amoxicillin treatment led to acute but not sustained increases in antimicrobial resistance genes and improved gut microbiome maturation 2 years after severe acute malnutrition treatment.
Whole genome sequencing (WGS) of extended-spectrum ß-lactamase-producing Escherichia coli (ESBL-E. coli) in developing countries is lacking. Here we describe the population structure and molecular characteristics of ESBL-E. coli faecal isolates in rural Southern Niger.
METHODS
Stools of 383 healthy participants were collected among which 92.4% were ESBL-Enterobacterales carriers. A subset of 90 ESBL-E. coli containing stools (109 ESBL-E. coli isolates) were further analysed by WGS, using short- and long-reads.
RESULTS
Most isolates belonged to the commensalism-adapted phylogroup A (83.5%), with high clonal diversity. The blaCTX-M-15 gene was the major ESBL determinant (98.1%), chromosome-integrated in approximately 50% of cases, in multiple integration sites. When plasmid-borne, blaCTX-M-15 was found in IncF (57.4%) and IncY plasmids (26.2%). Closely related plasmids were found in different genetic backgrounds. Genomic environment analysis of blaCTX-M-15 in closely related strains argued for mobilisation between plasmids or from plasmid to chromosome.
CONCLUSIONS
Massive prevalence of community faecal carriage of CTX-M-15-producing E. coli was observed in a rural region of Niger due to the spread of highly diverse A phylogroup commensalism-adapted clones, with frequent chromosomal integration of blaCTX-M-15. Plasmid spread was also observed. These data suggest a risk of sustainable implementation of ESBL in community faecal carriage.
Phenotypic drug susceptibility testing (pDST) for Mycobacterium tuberculosis can take up to 8 weeks, while conventional molecular tests identify a limited set of resistance mutations. Targeted next-generation sequencing (tNGS) offers rapid results for predicting comprehensive drug resistance, and this study sought to explore its operational feasibility within a public health laboratory in Mumbai, India.
METHODS
Pulmonary samples from consenting patients testing Xpert MTB-positive were tested for drug resistance by conventional methods and using tNGS. Laboratory operational and logistical implementation experiences from study team members are shared below.
RESULTS
Of the total number of patients tested, 70% (113/161) had no history of previous TB or treatment; however, 88.2% (n = 142) had rifampicin-resistant/multidrug-resistant TB (RR/MDR-TB). There was a high concordance between resistance predictions of tNGS and pDST for most drugs, with tNGS more accurately identifying resistance overall. tNGS was integrated and adapted into the laboratory workflow; however, batching samples caused significantly longer result turnaround time, fastest at 24 days. Manual DNA extraction caused inefficiencies; thus protocol optimisations were performed. Technical expertise was required for analysis of uncharacterised mutations and interpretation of report templates. tNGS cost per sample was US$230, while for pDST this was US$119.
CONCLUSIONS
Implementation of tNGS is feasible in reference laboratories. It can rapidly identify drug resistance and should be considered as a potential alternative to pDST.