Antimicrobial resistance patterns and characterisation of emerging beta-lactamase-producing Escherichia coli in camels sampled from Northern Kenya

BACKGROUND

Animal husbandry practices in different livestock production systems and increased livestock-wildlife interactions are thought to be primary drivers of antimicrobial resistance (AMR) in Arid and Semi-Arid Lands (ASALs). Despite a tenfold increase in the camel population within the last decade, paired with widespread use of camel products, there is a lack of comprehensive information concerning beta-lactamase-producing Escherichia coli (E. coli) within these production systems.

OBJECTIVES

Our study sought to establish an AMR profile and to identify and characterise emerging beta-lactamase-producing E. coli isolated from faecal samples obtained from camel herds in Northern Kenya.

METHODS

The antimicrobial susceptibility profiles of E. coli isolates were established using the disk diffusion method, with beta-lactamase (bla) gene PCR product sequencing performed for phylogenetic grouping and genetic diversity assessments.

RESULTS

Here we show, among the recovered E. coli isolates (n = 123), the highest level of resistance was observed for cefaclor at 28.5% of isolates, followed by cefotaxime at 16.3% and ampicillin at 9.7%. Moreover, extended-spectrum beta-lactamase (ESBL)-producing E. coli harbouring the bla_CTX-M-15 or bla_CTX-M-27 genes were detected in 3.3% of total samples, and are associated with phylogenetic groups B1, B2 and D. Multiple variants of non-ESBL bla_TEM genes were detected, the majority of which were the bla_TEM-1 and bla_TEM-116 genes.

CONCLUSIONS

Findings from this study shed light on the increased occurrence of ESBL- and non-ESBL-encoding gene variants in E. coli isolates with demonstrated multidrug resistant phenotypes. This study highlights the need for an expanded One Health approach to understanding AMR transmission dynamics, drivers of AMR development, and appropriate practices for antimicrobial stewardship in camel production systems within ASALs.

Net charge and position 22 of the V3 loop are associated with HIV-1 tropism in recently infected female sex workers in Nairobi, Kenya

Human immunodeficiency virus (HIV) infection affects around 37 million people worldwide, and in Kenya, key populations especially female sex workers (FSW), are thought to play a substantial role in the wider, mostly heterosexual HIV-1 transmission structure. Notably, HIV tropism has been found to correlate with HIV-1 transmission and disease progression in HIV-infected patients. In this study, recently infected FSWs from Nairobi, Kenya, were assessed for HIV tropism and the factors related to it. We used a cross-sectional study design to analyze 76 HIV-1 positive plasma samples obtained from FSWs enrolled in sex worker outreach program clinics in Nairobi between November 2020 and April 2021. The effects of clinical, demographic, and viral genetic characteristics were determined using multivariable logistic regression. HIV-1 subtype A1 accounted for 89.5% of all cases, with a prevalence of CXCR4-tropic viruses of 26.3%. WebPSSMR5X4 and Geno2Pheno [G2P:10-15% false positive rate] showed high concordance of 88%. Subjects infected with CXCR4-tropic viruses had statistically significant lower baseline CD4+T-cell counts than those infected with CCR5-tropic viruses (P = .044). Using multivariable logistic regression and adjusting for potential confounders, we found that net charge, the amino acid at position 22 of the V3 loop, and the geographic location of the subject were associated with tropism. A unit increase in V3 loop's net-charge increased the odds of a virus being CXCR4-tropic by 2.4 times (OR = 2.40, 95%CI = 1.35-5.00, P = .007). Second, amino acid threonine at position 22 of V3 loop increased the odds of a strain being X4 by 55.7 times compared to the alanine which occurred in CCR5-tropic strains (OR = 55.7, 95%CI = 4.04-84.1, P < .003). The Kawangware sex worker outreach program clinic was associated with CXCR4-tropic strains (P = .034), but there was there was no evidence of a distinct CXCR4-tropic transmission cluster. In conclusion, this study revealed a high concordance of WebPSSMR5X4 and Geno2Pheno in predicting HIV tropism. The most striking finding was that amino acid position 22 of the V3 loop is linked to tropism in HIV-1 subtype A1. Additional studies with a large dataset are warranted to confirm our findings.

Cost analysis of implementing HIV drug resistance testing in Kenya: a case study of a service delivery site at a tertiary level hospital in Kenya

Background: HIV drug resistance (HIVDR) threatens progress achieved in response to the HIV epidemic. Understanding the costs of implementing HIVDR testing programs for patient management and surveillance in resource-limited settings is critical in optimizing resource allocation. Here, we estimate the unit cost of HIVDR testing and identify major cost drivers while documenting challenges and lessons learnt in implementation of HIVDR testing at a tertiary level hospital in Kenya. Methods: We employed a mixed costing approach to estimate the costs associated with performing a HIVDR test from the provider's perspective. Data collection involved a time and motion study of laboratory procedures and interviewing laboratory personnel and the management personnel. Cost analysis was based on estimated 1000 HIVDR tests per year. Data entry and analysis were done using Microsoft Excel and costs converted to US dollars (2019). Results: The estimated unit cost for a HIVDR test was $271.78 per test. The main cost drivers included capital ($102.42, 37.68%) and reagents (101.50, 37.35%). Other costs included: personnel ($46.81, 17.22%), utilities ($14.69, 5.41%), equipment maintenance costs ($2.37, 0.87%) and quality assurance program ($4, 1.47%). Costs in relation to specific laboratory processes were as follows: sample collection ($2.41, 0.89%), RNA extraction ($22.79, 8.38%), amplification ($56.14, 20.66%), gel electrophoresis ($10.34, 3.80%), sequencing ($160.94, 59.22%), and sequence analysis ($19.16, 7.05%). A user-initiated modification of halving reagent volumes for some laboratory processes (amplification and sequencing) reduced the unit cost for a HIVDR test to $233.81 (13.97%) reduction.  Conclusions: Capital expenditure and reagents remain the most expensive components of HIVDR testing. This cost is bound to change as the sequencing platform is utilized towards maximum capacity or leveraged for use with other tests. Cost saving in offering HIVDR testing services is also possible through reagent volume reduction without compromising on the quality of test results.