Maize streak virus strain A (MSV-A), the causal agent of maize streak disease, is today one of the most serious biotic threats to African food security. Determining where MSV-A originated and how it spread transcontinentally could yield valuable insights into its historical emergence as a crop pathogen. Similarly, determining where the major extant MSV-A lineages arose could identify geographical hot spots of MSV evolution. Here, we use model-based phylogeographic analyses of 353 fully sequenced MSV-A isolates to reconstruct a plausible history of MSV-A movements over the past 150 years. We show that since the probable emergence of MSV-A in southern Africa around 1863, the virus spread transcontinentally at an average rate of 32.5 km/year (95% highest probability density interval, 15.6 to 51.6 km/year). Using distinctive patterns of nucleotide variation caused by 20 unique intra-MSV-A recombination events, we tentatively classified the MSV-A isolates into 24 easily discernible lineages. Despite many of these lineages displaying distinct geographical distributions, it is apparent that almost all have emerged within the past 4 decades from either southern or east-central Africa. Collectively, our results suggest that regular analysis of MSV-A genomes within these diversification hot spots could be used to monitor the emergence of future MSV-A lineages that could affect maize cultivation in Africa.

Stunting is a global public health issue. We sought to train and evaluate machine learning (ML) classification algorithms on the Zambia Demographic Health Survey (ZDHS) dataset to predict stunting among children under the age of five in Zambia. We applied Logistic regression (LR), Random Forest (RF), SV classification (SVC), XG Boost (XgB) and Naïve Bayes (NB) algorithms to predict the probability of stunting among children under five years of age, on the 2018 ZDHS dataset. We calibrated predicted probabilities and plotted the calibration curves to compare model performance. We computed accuracy, recall, precision and F1 for each machine learning algorithm. About 2327 (34.2%) children were stunted. Thirteen of fifty-eight features were selected for inclusion in the model using random forest. Calibrating the predicted probabilities improved the performance of machine learning algorithms when evaluated using calibration curves. RF was the most accurate algorithm, with an accuracy score of 79% in the testing and 61.6% in the training data while Naïve Bayesian was the worst performing algorithm for predicting stunting among children under five in Zambia using the 2018 ZDHS dataset. ML models aids quick diagnosis of stunting and the timely development of interventions aimed at preventing stunting.

Live attenuated oral vaccines against rotavirus (RV) have been shown to be less efficacious in children from developing countries. Reasons for this disparity are not fully understood. We assessed the role of maternal factors including breast milk RV-specific IgA, transplacentally acquired infant serum RV-specific IgG and maternal HIV status in seroconversion among Zambian infants routinely immunized with Rotarix™ (RV1). 420 mother-child pairs were recruited at infant age 6–12 weeks in Lusaka. Clinical information and samples were collected at baseline and at one month following the second dose of RV1. Determination of breast milk RV-specific IgA and serum RV-specific IgA and IgG was done using standardized ELISA. Seroconversion was defined as a ≥ 4 fold rise in serum IgA titre from baseline to one-month post RV1 dose 2, while seropositivity of IgA was defined as serum titre ≥ 40 and antibody variables were modelled on log-base 2. Logistic regression was used to identify predictors of the odds of seroconversion. Baseline infant seropositivity was 25.5% (91/357). The seroconversion frequency was 60.2% (130/216). Infants who were IgA seropositive at baseline were less likely to seroconvert compared to their seronegative counterparts (P = 0.04). There was no evidence of an association between maternal HIV status and seroconversion (P = 0.25). Higher titres of breast milk rotavirus-specific IgA were associated with a lower frequency of seroconverson (Nonparametric test for trend Z = -2.84; P<0.01): a two-fold increase in breast milk RV-specific IgA titres was associated with a 22% lower odds of seroconversion (OR = 0.80; 95% CI = 0.68–0.94; P = 0.01). There was seasonal variation in baseline breast milk rotavirus-specific IgA titres, with significantly higher GMTs during the cold dry months (P = 0.01). Low immunogenicity of RV1 vaccine could be explained in part by exposure to high antibody titres in breast milk and early exposure to wild-type rotavirus infections. Potential interference of anti-RV specific IgA in breast milk and pre-vaccination serum RV specific-IgA and IgG titres with RV1 seroconversion and effectiveness requires further research.

Background: Inappropriate antimicrobial usage is a key driver of antimicrobial resistance (AMR). Low- and middle-income countries (LMICs) are disproportionately burdened by AMR and young children are especially vulnerable to infections with AMR-bearing pathogens. The impact of antibiotics on the microbiome, selection, persistence, and horizontal spread of AMR genes is insufficiently characterized and understood in children in LMICs. This systematic review aims to collate and evaluate the available literature describing the impact of antibiotics on the infant gut microbiome and resistome in LMICs. Methods and findings: In this systematic review, we searched the online databases MEDLINE (1946 to 28 January 2023), EMBASE (1947 to 28 January 2023), SCOPUS (1945 to 29 January 2023), WHO Global Index Medicus (searched up to 29 January 2023), and SciELO (searched up to 29 January 2023). A total of 4,369 articles were retrieved across the databases. Duplicates were removed resulting in 2,748 unique articles. Screening by title and abstract excluded 2,666 articles, 92 articles were assessed based on the full text, and 10 studies met the eligibility criteria that included human studies conducted in LMICs among children below the age of 2 that reported gut microbiome composition and/or resistome composition (AMR genes) following antibiotic usage. The included studies were all randomized control trials (RCTs) and were assessed for risk of bias using the Cochrane risk-of-bias for randomized studies tool. Overall, antibiotics reduced gut microbiome diversity and increased antibiotic-specific resistance gene abundance in antibiotic treatment groups as compared to the placebo. The most widely tested antibiotic was azithromycin that decreased the diversity of the gut microbiome and significantly increased macrolide resistance as early as 5 days posttreatment. A major limitation of this study was paucity of available studies that cover this subject area. Specifically, the range of antibiotics assessed did not include the most commonly used antibiotics in LMIC populations. Conclusion: In this study, we observed that antibiotics significantly reduce the diversity and alter the composition of the infant gut microbiome in LMICs, while concomitantly selecting for resistance genes whose persistence can last for months following treatment. Considerable heterogeneity in study methodology, timing and duration of sampling, and sequencing methodology in currently available research limit insights into antibiotic impacts on the microbiome and resistome in children in LMICs. More research is urgently needed to fill this gap in order to better understand whether antibiotic-driven reductions in microbiome diversity and selection of AMR genes place LMIC children at risk for adverse health outcomes, including infections with AMR-bearing pathogens.

Childhood stunting is associated with impaired cognitive development and increased risk of infections, morbidity, and mortality. The composition of the enteric microbiota may contribute to the pathogenesis of stunting. We systematically reviewed and synthesized data from studies using high-throughput genomic sequencing methods to characterize the gut microbiome in stunted versus non-stunted children under 5 years in LMICs. We included 14 studies from Asia, Africa, and South America. Most studies did not report any significant differences in the alpha diversity, while a significantly higher beta diversity was observed in stunted children in four out of seven studies that reported beta diversity. At the phylum level, inconsistent associations with stunting were observed for Bacillota, Pseudomonadota, and Bacteroidota phyla. No single genus was associated with stunted children across all 14 studies, and some associations were incongruent by specific genera. Nonetheless, stunting was associated with an abundance of pathobionts that could drive inflammation, such as Escherichia/Shigella and Campylobacter, and a reduction of butyrate producers, including Faecalibacterium, Megasphera, Blautia, and increased Ruminoccoccus. An abundance of taxa thought to originate in the oropharynx was also reported in duodenal and fecal samples of stunted children, while metabolic pathways, including purine and pyrimidine biosynthesis, vitamin B biosynthesis, and carbohydrate and amino acid degradation pathways, predicted linear growth. Current studies show that stunted children can have distinct microbial patterns compared to non-stunted children, which could contribute to the pathogenesis of stunting.

Environmental enteropathy (EE) is an asymptomatic abnormality of small bowel structure and function, which may underlie vaccine inefficacy in the developing world. HIV infection co-exists in many of these populations. There is currently no effective treatment. We conducted a secondary analysis of a randomised controlled trial of high dose multiple micronutrient (MM) supplementation on small bowel architecture in EE in participants with or without HIV infection.