Rapid Emergence and Evolution of SARS-CoV-2 Variants in Advanced HIV Infection.

Previous studies have linked the evolution of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genetic variants to persistent infections in people with immunocompromising conditions1-4, but the evolutionary processes underlying these observations are incompletely understood. Here we used high-throughput, single-genome amplification and sequencing (HT-SGS) to obtain up to ~103 SARS-CoV-2 spike gene sequences in each of 184 respiratory samples from 22 people with HIV (PWH) and 25 people without HIV (PWOH). Twelve of 22 PWH had advanced HIV infection, defined by peripheral blood CD4 T cell counts (i.e., CD4 counts) <200 cells/µL. In PWOH and PWH with CD4 counts ≥200 cells/µL, most single-genome spike sequences in each person matched one haplotype that predominated throughout the infection. By contrast, people with advanced HIV showed elevated intra-host spike diversity with a median of 46 haplotypes per person (IQR 14-114). Higher intra-host spike diversity immediately after COVID-19 symptom onset predicted longer SARS-CoV-2 RNA shedding among PWH, and intra-host spike diversity at this timepoint was significantly higher in people with advanced HIV than in PWOH. Composition of spike sequence populations in people with advanced HIV fluctuated rapidly over time, with founder sequences often replaced by groups of new haplotypes. These population-level changes were associated with a high total burden of intra-host mutations and positive selection at functionally important residues. In several cases, delayed emergence of detectable serum binding to spike was associated with positive selection for presumptive antibody-escape mutations. Taken together, our findings show remarkable intra-host genetic diversity of SARS-CoV-2 in advanced HIV infection and suggest that adaptive intra-host SARS-CoV-2 evolution in this setting may contribute to the emergence of new variants of concern (VOCs).

Genomics for public health and international surveillance of antimicrobial resistance.

Historically, epidemiological investigation and surveillance for bacterial antimicrobial resistance (AMR) has relied on low-resolution isolate-based phenotypic analyses undertaken at local and national reference laboratories. Genomic sequencing has the potential to provide a far more high-resolution picture of AMR evolution and transmission, and is already beginning to revolutionise how public health surveillance networks monitor and tackle bacterial AMR. However, the routine integration of genomics in surveillance pipelines still has considerable barriers to overcome. In 2022, a workshop series and online consultation brought together international experts in AMR and pathogen genomics to assess the status of genomic applications for AMR surveillance in a range of settings. Here we focus on discussions around the use of genomics for public health and international AMR surveillance, noting the potential advantages of, and barriers to, implementation, and proposing recommendations from the working group to help to drive the adoption of genomics in public health AMR surveillance. These recommendations include the need to build capacity for genome sequencing and analysis, harmonising and standardising surveillance systems, developing equitable data sharing and governance frameworks, and strengthening interactions and relationships among stakeholders at multiple levels.

Multidrug-resistant Gram-negative bacterial colonization in patients, carriage by healthcare workers and contamination of hospital environments in Ghana.

BACKGROUND: Patients already colonized with multidrug-resistant (MDR) Gram-negative bacteria (GNB) on admission to critical care units may be an important source of transmission of these bacteria in hospitals. We sought to determine the prevalence of MDR GNB colonization in patients, staff and the ward environment and to assess the risk factors for colonization of patients in wards. METHODS: The study was conducted from April 2021 to July 2021 in a teaching hospital in Ghana. MDR GNB were isolated from rectal, and hand swabs were taken from patients on admission and after 48 h. Swabs from HCW's hands and the ward environment were also taken. Risk factors for colonization with MDR GNB were assessed using univariate and multivariate analysis. RESULTS: MDR GNB rectal colonization rate among patients was 50.62% on admission and 44.44% after 48 h. MDR GNB were isolated from 6 (5.26%) and 24 (11.54%) of HCW's hand swabs and environmental swabs, respectively. Previous hospitalization (p-value = 0.021, OR, 95% CI= 7.170 (1.345-38.214) was significantly associated with colonization by MDR GNB after 48 h of admission. Age (21-30 years) (p-value = 0.022, OR, 95% CI = 0.103 (0.015-0.716) was significantly identified as a protective factor associated with a reduced risk of rectal MDR GNB colonization. CONCLUSION: The high colonization of MDR GNB in patients, the carriage of MDR GNB on HCW's hands, and the contamination of hospital environments highlights the need for patient screening and stringent infection prevention and control practices to prevent the spread of MDR GNB in hospitals.

SARS-CoV-2 genomic surveillance in wastewater as a model for monitoring evolution of endemic viruses.

As global SARS-CoV-2 burden and testing frequency have decreased, wastewater surveillance has emerged as a key tool to support clinical surveillance efforts. The aims of this study were to identify and characterize SARS-CoV-2 variants in wastewater samples collected from urban centers across South Africa. Here we show that wastewater sequencing analyses are temporally concordant with clinical genomic surveillance and reveal the presence of multiple lineages not detected by clinical surveillance. We show that wastewater genomics can support SARS-CoV-2 epidemiological investigations by reliably recovering the prevalence of local circulating variants, even when clinical samples are not available. Further, we find that analysis of mutations observed in wastewater can provide a signal of upcoming lineage transitions. Our study demonstrates the utility of wastewater genomics to monitor evolution and spread of endemic viruses.

Impact of Environmental Sub-Inhibitory Concentrations of Antibiotics, Heavy Metals, and Biocides on the Emergence of Tolerance and Effects on the Mutant Selection Window in E. coli.

Bacteria's ability to withstand the detrimental effects of antimicrobials could occur as resistance or tolerance with the minimum inhibitory concentration, the mutant prevention concentration, and the mutant selection window as salient concepts. Thus, this study assessed the impact of exposure to extremely high doses of ampicillin on the level of persistence and tolerance development in isolates previously exposed to different concentrations of selected antibiotics, biocides, and heavy metals. These isolates were previously exposed to oxytetracycline (OXYTET), amoxicillin (AMX), copper (Cu), zinc (Zn), benzalkonium chloride (BAC) 10, dimethylammonium chloride (DADMAC) 12 and a combination of all the individual pollutants (ALL). The isolates were exposed to very high concentrations (25 × MIC) of ampicillin, and their tolerance was calculated as the time required to kill 99.9% of the bacterial population (MDK99.9). The MDK99.9 increased by 30 to 50% in test isolates (DADMAC, OXYTET, Zinc = 28 h; BAC, Copper = 30 h; amoxycillin, ALL = 26 h) compared to the untreated control. BAC-exposed isolates decreased from 2.5 × 108 CFU/mL to 2.5 × 104 CFU/mL on the second day, displaying the highest tolerance increase. The tolerance appeared to originate from two sources, i.e., stochastic persistence and genetic-induced persistence, involving multiple genes with diverse mechanisms. The mutant selection window of the isolates to ampicillin, amoxicillin, and oxytetracycline also slightly increased compared to the control, indicating the selective survival of persister cells during the 30-day exposure. These findings indicate that bacterial exposure to sub-inhibitory concentrations of environmental chemical stressors may not always result in the development of antimicrobial resistance but could initiate this process by selecting persisters that could evolve into resistant isolates.

Antibiotic, Heavy Metal, and Biocide Concentrations in a Wastewater Treatment Plant and Its Receiving Water Body Exceed PNEC Limits: Potential for Antimicrobial Resistance Selective Pressure.

Although the rise in antimicrobial resistance has been attributed mainly to the extensive and indiscriminate use of antimicrobials such as antibiotics and biocides in humans, animals and on plants, studies investigating the impact of this use on water environments in Africa are minimal. This study quantified selected antibiotics, heavy metals, and biocides in an urban wastewater treatment plant (WWTP) and its receiving water body in Kwazulu-Natal, South Africa, in the context of the predicted no-effect concentrations (PNEC) for the selection of antimicrobial resistance (AMR). Water samples were collected from the WWTP effluent discharge point and upstream and downstream from this point. Heavy metals were identified and quantified using the United States Environmental Protection Agency (US EPA) method 200.7. Biocides and antibiotic residues were determined using validated ultra-high-performance liquid chromatography with tandem mass spectrometry-based methods. The overall highest mean antibiotic, metal and biocide concentrations were observed for sulfamethoxazole (286.180 µg/L), neodymium (Nd; 27.734 mg/L), and benzalkonium chloride (BAC 12) (7.805 µg/L), respectively. In decreasing order per sampling site, the pollutant concentrations were effluent > downstream > upstream. This implies that the WWTP significantly contributed to the observed pollution in the receiving water. Furthermore, most of the pollutants measured recorded values exceeding the recommended predicted no-effect concentration (PNEC) values, suggesting that the microbes in such water environments were at risk of developing resistance due to the selection pressure exerted by these antimicrobials. Further studies are required to establish such a relationship.

Environmental concentrations of antibiotics, biocides, and heavy metals fail to induce phenotypic antimicrobial resistance in Escherichia coli.

Most anthropogenically affected environments contain mixtures of pollutants from different sources. The impact of these pollutants is usually the combined effect of the individual polluting constituents. However, how these stressors contribute to the development of antimicrobial resistance in environmental microorganisms is poorly understood. Thus, a 30-day exposure experiment to environmental and sub-inhibitory concentrations of oxytetracycline, amoxicillin, zinc, copper, BAC (benzalkonium chloride) 10 and DADMAC (diallyldimethylammonium chloride) 12, was conducted using fully susceptible E. coli ATCC 25922 to ascertain any development of phenotypic or genotypic resistance. Furthermore, wild-type isolates were collected from the same aquatic environment as the stressors, analysed for phenotypic resistance using the disk diffusion method and genotypically through whole genome sequencing. Exposure to the various concentrations and combinations of the stressors did not trigger phenotypic resistance in the experimental bacteria. Furthermore, genotypic analysis of the WGS on the exposed isolates only found the macrolide resistance mdf(A) gene (also present in the control strain) and the disinfectant resistance gene sitABCD. With further analysis for single nucleotide variants (SNV), mutations were detected for 19 genes that encoded for oxidative stress, DNA repair, membrane proteins efflux systems, growth and persister formations except for the robA, a transcription protein subset of the ArcC/XylS family of proteins, which confer multidrug resistance in E. coli. This indicates that exposure to sub-inhibitory concentrations of antibiotics, heavy metals and biocide residues in the aquatic environmental concentrations of the stressors identified in the current study could not induce phenotypic or genotypic resistance but encoded for genes responsible for the development of persistence and tolerance in bacteria, which could be a precursor to the development of resistance in environmental bacteria.

Identifying Patient Populations in Texts Describing Drug Approvals Through Deep Learning-Based Information Extraction: Development of a Natural Language Processing Algorithm.

BACKGROUND: New drug treatments are regularly approved, and it is challenging to remain up-to-date in this rapidly changing environment. Fast and accurate visualization is important to allow a global understanding of the drug market. Automation of this information extraction provides a helpful starting point for the subject matter expert, helps to mitigate human errors, and saves time. OBJECTIVE: We aimed to semiautomate disease population extraction from the free text of oncology drug approval descriptions from the BioMedTracker database for 6 selected drug targets. More specifically, we intended to extract (1) line of therapy, (2) stage of cancer of the patient population described in the approval, and (3) the clinical trials that provide evidence for the approval. We aimed to use these results in downstream applications, aiding the searchability of relevant content against related drug project sources. METHODS: We fine-tuned a state-of-the-art deep learning model, Bidirectional Encoder Representations from Transformers, for each of the 3 desired outputs. We independently applied rule-based text mining approaches. We compared the performances of deep learning and rule-based approaches and selected the best method, which was then applied to new entries. The results were manually curated by a subject matter expert and then used to train new models. RESULTS: The training data set is currently small (433 entries) and will enlarge over time when new approval descriptions become available or if a choice is made to take another drug target into account. The deep learning models achieved 61% and 56% 5-fold cross-validated accuracies for line of therapy and stage of cancer, respectively, which were treated as classification tasks. Trial identification is treated as a named entity recognition task, and the 5-fold cross-validated F1-score is currently 87%. Although the scores of the classification tasks could seem low, the models comprise 5 classes each, and such scores are a marked improvement when compared to random classification. Moreover, we expect improved performance as the input data set grows, since deep learning models need to be trained on a large enough amount of data to be able to learn the task they are taught. The rule-based approach achieved 60% and 74% 5-fold cross-validated accuracies for line of therapy and stage of cancer, respectively. No attempt was made to define a rule-based approach for trial identification. CONCLUSIONS: We developed a natural language processing algorithm that is currently assisting subject matter experts in disease population extraction, which supports health authority approvals. This algorithm achieves semiautomation, enabling subject matter experts to leverage the results for deeper analysis and to accelerate information retrieval in a crowded clinical environment such as oncology.

A Genomic Snapshot of Antibiotic-ResistantEnterococcus faecalis within Public Hospital Environments in South Africa.

Enterococci are among the most common opportunistic hospital pathogens. This study used whole-genome sequencing (WGS) and bioinformatics to determine the antibiotic resistome, mobile genetic elements, clone and phylogenetic relationship of Enterococcus faecalis isolated from hospital environments in South Africa. This study was carried out from September to November 2017. Isolates were recovered from 11 frequently touched sites by patients and healthcare workers in different wards at 4 levels of healthcare (A, B, C, and D) in Durban, South Africa. Out of the 245 identified E. faecalis isolates, 38 isolates underwent whole-genome sequencing (WGS) on the Illumina MiSeq platform, following microbial identification and antibiotic susceptibility tests. The tet(M) (31/38, 82%) and erm(C) (16/38, 42%) genes were the most common antibiotic-resistant genes found in isolates originating from different hospital environments which corroborated with their antibiotic resistance phenotypes. The isolates harboured mobile genetic elements consisting of plasmids (n = 11) and prophages (n = 14) that were mostly clone-specific. Of note, a large number of insertion sequence (IS) families were found on the IS3 (55%), IS5 (42%), IS1595 (40%), and Tn3 transposons the most predominant. Microbial typing using WGS data revealed 15 clones with 6 major sequence types (ST) belonging to ST16 (n = 7), ST40 (n = 6), ST21 (n = 5), ST126 (n = 3), ST23 (n = 3), and ST386 (n = 3). Phylogenomic analysis showed that the major clones were mostly conserved within specific hospital environments. However, further metadata insights revealed the complex intraclonal spread of these E. faecalis major clones between the sampling sites within each specific hospital setting. The results of these genomic analyses will offer insights into antibiotic-resistantE. faecalis in hospital environments relevant to the design of optimal infection prevention strategies in hospital settings.

Genomic epidemiology of SARS-CoV-2 during the first four waves in Mozambique.

Mozambique reported the first case of coronavirus disease 2019 (COVID-19) in March 2020 and it has since spread to all provinces in the country. To investigate the introductions and spread of SARS-CoV-2 in Mozambique, 1 142 whole genome sequences sampled within Mozambique were phylogenetically analyzed against a globally representative set, reflecting the first 25 months of the epidemic. The epidemic in the country was marked by four waves of infection, the first associated with B.1 ancestral lineages, while the Beta, Delta, and Omicron Variants of Concern (VOCs) were responsible for most infections and deaths during the second, third, and fourth waves. Large-scale viral exchanges occurred during the latter three waves and were largely attributed to southern African origins. Not only did the country remain vulnerable to the introductions of new variants but these variants continued to evolve within the borders of the country. Due to the Mozambican health system already under constraint, and paucity of data in Mozambique, there is a need to continue to strengthen and support genomic surveillance in the country as VOCs and Variants of interests (VOIs) are often reported from the southern African region.

Household Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 From Adult Index Cases With and Without Human Immunodeficiency Virus in South Africa, 2020-2021: A Case-Ascertained, Prospective, Observational Household Transmission Study.

BACKGROUND: In South Africa, 19% of adults are living with human immunodeficiency virus (HIV; LWH). Few data on the influence of HIV on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) household transmission are available. METHODS: We performed a case-ascertained, prospective household transmission study of symptomatic adult index SARS-CoV-2 cases LWH and not living with HIV (NLWH) and their contacts from October 2020 to September 2021. Households were followed up 3 times a week for 6 weeks to collect nasal swabs for SARS-CoV-2 testing. We estimated household cumulative infection risk (HCIR) and duration of SARS-CoV-2 positivity (at a cycle threshold value <30 as proxy for high viral load). RESULTS: HCIR was 59% (220 of 373), not differing by index HIV status (60% LWH vs 58% NLWH). HCIR increased with index case age (35-59 years: adjusted OR [aOR], 3.4; 95% CI, 1.5-7.8 and ≥60 years: aOR, 3.1; 95% CI, 1.0-10.1) compared with 18-34 years and with contacts' age, 13-17 years (aOR, 7.1; 95% CI, 1.5-33.9) and 18-34 years (aOR, 4.4; 95% CI, 1.0-18.4) compared with <5 years. Mean positivity was longer in cases LWH (adjusted hazard ratio, 0.4; 95% CI, .1-.9). CONCLUSIONS: Index HIV status was not associated with higher HCIR, but cases LWH had longer positivity duration. Adults aged >35 years were more likely to transmit and individuals aged 13-34 to be infected SARS-CoV-2 in the household. As HIV infection may increase transmission, health services must maintain HIV testing and antiretroviral therapy initiation.

Antibacterial, Resistance Modulation, Anti-Biofilm Formation, and Efflux Pump Inhibition Properties of Loeseneriella africana (Willd.) N. Halle (Celastraceae) Stem Extract and Its Constituents.

This study investigated the antibacterial, resistance modulation, biofilm inhibition, and efflux pump inhibition potentials of Loeseneriella africana stem extract and its constituents. The antimicrobial activity was investigated by the high-throughput spot culture growth inhibition (HT-SPOTi) and broth microdilution assays. The resistance modulation activity was investigated using the anti-biofilm formation and efflux pump inhibition assays. Purification of the extract was carried out by chromatographic methods, and the isolated compounds were characterized based on nuclear magnetic resonance, Fourier transform infrared and mass spectrometry spectral data and comparison with published literature. The whole extract, methanol, ethyl acetate, and pet-ether fractions of L. africana all showed antibacterial activity against the test bacteria with MICs ranging from 62.5 to 500.0 µg/mL The whole extract demonstrated resistance modulation effect through strong biofilm inhibition and efflux pump inhibition activities against S. aureus ATCC 25923, E. coli ATCC 25922 and P. aeruginosa ATCC 27853. Chromatographic fractionation of the ethyl acetate fraction resulted in the isolation of a triterpenoid (4S,4αS,6αR,6ßS,8αS,12αS,12ßR,14αS,14ßR)-4,4α,6ß,8α,11,11,12ß,14α-Octamethyloctadecahydropicene-1,3(2H,4H)-dione) and a phytosterol (ß-sitosterol). These compounds showed antibacterial activity against susceptible bacteria at a MIC range of 31-125 µg/mL and potentiated the antibacterial activity of amoxicillin (at » MIC of compounds) against E. coli and P. aeruginosa with modulation factors of 32 and 10, respectively. These compounds also demonstrated good anti-biofilm formation effect at a concentration range of 3-100 µg/mL, and bacterial efflux pump inhibition activity at ½ MIC and » MIC against E. coli and P. aeruginosa. Loeseneriella africana stem bark extracts and constituents elicit considerable antibacterial, resistance modulation, and biofilm and efflux pump inhibition activities. The results justify the indigenous uses of L. africana for managing microbial infections.

Risk Factors for Severe Coronavirus Disease 2019 Among Human Immunodeficiency Virus-Infected and -Uninfected Individuals in South Africa, April 2020-March 2022: Data From Sentinel Surveillance.

Background: Data on risk factors for coronavirus disease 2019 (COVID-19)-associated hospitalization and mortality in high human immunodeficiency virus (HIV) prevalence settings are limited. Methods: Using existing syndromic surveillance programs for influenza-like-illness and severe respiratory illness at sentinel sites in South Africa, we identified factors associated with COVID-19 hospitalization and mortality. Results: From April 2020 through March 2022, severe acute respiratory syndrome coronavirus 2 was detected in 24.0% (660 of 2746) of outpatient and 32.5% (2282 of 7025) of inpatient cases. Factors associated with COVID-19-associated hospitalization included the following: older age (25-44 [adjusted odds ratio {aOR}= 1.8, 95% confidence interval (CI) = 1.1-2.9], 45-64 [aOR = 6.8, 95% CI = 4.2-11.0] and ≥65 years [aOR = 26.6, 95% CI = 14.4-49.1] vs 15-24 years); black race (aOR, 3.3; 95% CI, 2.2-5.0); obesity (aOR, 2.3; 95% CI, 1.4-3.9); asthma (aOR, 3.5; 95% CI, 1.4-8.9); diabetes mellitus (aOR, 5.3; 95% CI, 3.1-9.3); HIV with CD4 ≥200/mm3 (aOR, 1.5; 95% CI, 1.1-2.2) and CD4 <200/mm3 (aOR, 10.5; 95% CI, 5.1-21.6) or tuberculosis (aOR, 12.8; 95% CI, 2.8-58.5). Infection with Beta (aOR, 0.5; 95% CI, .3-.7) vs Delta variant and being fully vaccinated (aOR, 0.1; 95% CI, .1-.3) were less associated with COVID-19 hospitalization. In-hospital mortality was increased in older age (45-64 years [aOR, 2.2; 95% CI, 1.6-3.2] and ≥65 years [aOR, 4.0; 95% CI, 2.8-5.8] vs 25-44 years) and male sex (aOR, 1.3; 95% CI, 1.0-1.6) and was lower in Omicron-infected (aOR, 0.3; 95% CI, .2-.6) vs Delta-infected individuals. Conclusions: Active syndromic surveillance encompassing clinical, laboratory, and genomic data identified setting-specific risk factors associated with COVID-19 severity that will inform prioritization of COVID-19 vaccine distribution. Elderly people with tuberculosis or people with HIV, especially severely immunosuppressed, should be prioritized for vaccination.

Clinical severity of SARS-CoV-2 Omicron BA.4 and BA.5 lineages compared to BA.1 and Delta in South Africa.

Omicron lineages BA.4 and BA.5 drove a fifth wave of COVID-19 cases in South Africa. Here, we use the presence/absence of the S-gene target as a proxy for SARS-CoV-2 variant/lineage for infections diagnosed using the TaqPath PCR assay between 1 October 2021 and 26 April 2022. We link national COVID-19 individual-level data including case, laboratory test and hospitalisation data. We assess severity using multivariable logistic regression comparing the risk of hospitalisation and risk of severe disease, once hospitalised, for Delta, BA.1, BA.2 and BA.4/BA.5 infections. After controlling for factors associated with hospitalisation and severe outcome respectively, BA.4/BA.5-infected individuals had a similar odds of hospitalisation (aOR 1.24, 95% CI 0.98-1.55) and severe outcome (aOR 0.72, 95% CI 0.41-1.26) compared to BA.1-infected individuals. Newly emerged Omicron lineages BA.4/BA.5 showed similar severity to the BA.1 lineage and continued to show reduced clinical severity compared to the Delta variant.

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance.

Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern-particularly Alpha, Beta, Delta, and Omicron-on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century.

Omicron BA.4/BA.5 escape neutralizing immunity elicited by BA.1 infection.

SARS-CoV-2 Omicron (B.1.1.529) BA.4 and BA.5 sub-lineages, first detected in South Africa, have changes relative to Omicron BA.1 including substitutions in the spike receptor binding domain. Here we isolated live BA.4 and BA.5 viruses and measured BA.4/BA.5 neutralization elicited by BA.1 infection either in the absence or presence of previous vaccination as well as from vaccination without BA.1 infection. In BA.1-infected unvaccinated individuals, neutralization relative to BA.1 declines 7.6-fold for BA.4 and 7.5-fold for BA.5. In vaccinated individuals with subsequent BA.1 infection, neutralization relative to BA.1 decreases 3.2-fold for BA.4 and 2.6-fold for BA.5. The fold-drop versus ancestral virus neutralization in this group is 4.0-fold for BA.1, 12.9-fold for BA.4, and 10.3-fold for BA.5. In contrast, BA.4/BA.5 escape is similar to BA.1 in the absence of BA.1 elicited immunity: fold-drop relative to ancestral virus neutralization is 19.8-fold for BA.1, 19.6-fold for BA.4, and 20.9-fold for BA.5. These results show considerable escape of BA.4/BA.5 from BA.1 elicited immunity which is moderated with vaccination and may indicate that BA.4/BA.5 may have the strongest selective advantage in evading neutralization relative to BA.1 in unvaccinated, BA.1 infected individuals.

Salmonella Yoruba: A rare serotype revealed through genomic sequencing along the farm-to-fork continuum of an intensive poultry farm in KwaZulu-Natal, South Africa.

Salmonella enterica is a zoonotic pathogen of worldwide public health importance. We characterised Salmonella isolates from poultry along the farm-to-fork continuum using whole genome sequencing (WGS) and bioinformatic analyses. Three multilocus sequence types (MLSTs), i.e., ST15 (1.9%), ST152 (5.9%) and ST1316 (92.2%) and three serotypes, i.e., S. Heidelberg (1.9%), Kentucky (5.9%) and Yoruba (92.2%) were detected. The rare serotype, S. Yoruba, was detected among the farm and abattoir isolates and contained resistance and virulence determinants. Resistome analysis revealed the presence of the aac(6')-Iaa gene associated with aminoglycoside resistance, a single point mutation in the parC gene associated with fluoroquinolone and quinolone resistance, and a single isolate contained the fosA7 gene responsible for fosfomycin resistance. No antibiotic resistance genes (ARGs) were identified for isolates phenotypically non-susceptible to azithromycin, cephalosporins, chloramphenicol and nitrofurantoin and resistance was thought to be attributable to other resistance mechanisms. The fully susceptible profiles observed for the wastewater isolates suggest that the poultry environment may receive antibiotic-resistant strains and resistance determinants from poultry with the potential of becoming a pathway of Salmonella transmission along the continuum. Six plasmids were identified and were only carried by 92.2% of the S. Yoruba isolates in varying combinations. Four plasmids were common to all S. Yoruba isolates along the continuum; isolates from the litter and feces on the farm contained two additional plasmids. Ten Salmonella pathogenicity islands (SPIs) and 177 virulence genes were identified; some were serotype-specific. Phylogenetic analysis of S. Heidelberg and Kentucky showed that isolates were related to animal and human isolates from other countries. Phylogenetic analysis among the S. Yoruba isolates revealed four clades based on the isolate sources along the farm-to-fork continuum. Although the transmission of Salmonella strains along the farm-to-fork continuum was not evident, pathogenic, resistant Salmonella present in the poultry production chain poses a food safety risk. WGS analysis can provide important information on the spread, resistance, pathogenicity, and epidemiology of isolates and new, rare or emerging Salmonella strains to develop intervention strategies to improve food safety.

A Public Health Insight into Salmonella in Poultry in Africa: A Review of the Past Decade: 2010-2020.

Poultry is a cheap source of animal protein and constituent of diets in Africa. Poultry can serve as a reservoir for Salmonella and cause food-borne infections in humans. This review describes Salmonella contamination of food, poultry, and the farming environment, antimicrobial resistance profiles, and serotypes of Salmonella, as well as the farming systems, antimicrobial use (AMU), hygiene, and husbandry conditions used to rear poultry in Africa. Using the PRISMA (preferred reporting items for systematic reviews and meta-analysis) guidelines, PubMed, Science Direct, and Web of Science databases were searched using a set of predefined keywords. Full-length research articles in English were examined for the period 2010-2020 and relevant information extracted for the narrative synthesis. Of the articles that met the inclusion criteria, 63.1% were conducted on farms and among households, while 36.9% were undertaken at government-controlled laboratories, which quarantine imported birds, processing plants, and retail outlets. The farming systems were intensive, semi-intensive, and extensive. AMU was described in 11.5% of the studies and varied within and across countries. Multidrug-resistant (MDR) Salmonella isolates were detected in 30 studies and the prevalence ranged from 12.1% in Zimbabwe to 100% in Egypt, Ethiopia, Nigeria, Senegal, and South Africa. A total of 226 different Salmonella serotypes were reported. Twenty-four (19.7%) of the studies reported food-borne Salmonella contamination in eggs, poultry, and poultry products at retail outlets and processing plants. The apparent extensive use of antimicrobials and circulation of MDR Salmonella isolates of various serotypes in Africa is a concern. It is important to implement stricter biosecurity measures on farms, regulate the use of antimicrobials and implement surveillance systems, in addition to food safety measures to monitor the quality of poultry and poultry products for human consumption.