Baobab Index

Tuberculosis outbreaks in nonhuman primate (NHP) colonies can result in disastrous financial, scientific, animal welfare, and public health outcomes. Tuberculin skin testing (TST) has been the standard diagnostic method for identifying Mycobacterium tuberculosis (Mtb) infection in NHPs but has limited sensitivity and specificity. In humans, Mtb-specific interferon-γ release assays (IGRAs) have become the preferred diagnostic method, overcoming significant limitations of the TST. We compared the diagnostic qualities of the TST and IGRA in a cohort of 673 rhesus and cynomolgus macaques with experimental Mtb infection. Serial TST and IGRA data were curated retrospectively for animals before and after Mtb infection and temporally matched to assess sensitivity, specificity, and agreement between the 2 tests. The overall sensitivity of the IGRA was 0.84 compared with 0.49 sensitivity of the TST test in detecting Mtb infection. Specificity of the IGRA and the TST was 0.83 and 1.0, respectively, with an overall agreement rate of 72% between the 2 tests. Sensitivity peaked at 3-5 weeks postinfection for TST and 5-7 weeks for IGRA. Data from a second cohort of animals (n = 227) that were not experimentally infected with Mtb, but for whom testing was done for screening and investigational purposes, demonstrated an agreement rate of 96%. To our knowledge, this is the largest reported comparison of TST and IGRA testing in NHPs. Although IGRAs are more labor intensive than TSTs, our data suggest that IGRAs have better diagnostic accuracy in detecting Mtb infection. Our data also suggest that the threshold for a positive TST could be lowered to improve sensitivity.

Characterizing population structure and admixture events between ancestral groups plays a key role in understanding the evolutionary history of species and crops. Most tools for inferring admixture have been developed for diploids and are not suitable for polyploids, in particular those with high and mixed ploidy such as Saccharum. Here we present AdmixPoly, an R-package designed to infer admixture in polyploid species both at the genome-wide scale and locally along chromosomes. We compare AdmixPoly with state-of-the-art methods using simulations, demonstrating its precision and computational efficiency. Notably, local admixture inference in complex scenarios, such as high ploidy levels, large numbers of ancestral groups and alleles per marker is enabled through efficient approximations of emission and transition probabilities within a hidden Markov model framework. We apply this approach to characterize the contributions of wild Saccharum species to the complex polyploid genome of modern sugarcane cultivars. A panel of wild and cultivated Saccharum accessions is genotyped for 80K genomic regions, each revealing approximately 50 read-scale haplotypes. The results reveal that most of the approximately 12 copies of each basic chromosome in modern cultivars are derived from the domesticated species Saccharum officinarum, with one to four copies typically contributed by distinct subgroups of the wild species Saccharum spontaneum. In addition, contributions from an unknown wild Saccharum group originating from the Pacific were identified in most cultivars. The conserved pattern of these introgressions suggests that they can be traced back to the early stages of sugarcane breeding approximately a century ago.

Invasive species adversely affect biodiversity, but little is known about how ecologically similar invaders interact. Such intraguild interactions may drive non-native community dynamics and their broader impacts on biodiversity. In native systems, intraguild interactions are widespread strong eco-evolutionary pressures; understanding whether similar patterns occur among invaders is key to predicting invasion outcomes. We investigated the role of intraguild predation in a community of non-native ant species inhabiting a tropical island with no native ants. Using dietary metabarcoding, we quantified intraguild predation, applied null models to test dietary and spatial preferences, conducted food bait experiments to assess competition for resources, and quantified potential competition strength using a hypergraph network approach. Metabarcoding 755 ants across 12 species revealed that ~50% of prey detections represented ant-ant consumption. Ants preferentially consumed other ants over native arthropods but only once the globally invasive big-headed ant, Pheidole megacephala, was removed from the null model analysis due to its hyperabundance. Additionally, 35% of food resources were identified as foci for potential interspecific exploitation where ant species spatially co-occurred. Pheidole megacephala occupied a key structural role in the community: it frequently competed with others for prey, was consumed less often than expected given its abundance, and was spatially avoided by other ants. Overall, interference competition was dominated by P. megacephala, but exploitation competition was high across the community. These findings suggest that intraguild interactions strongly structure invaded communities, influencing the ecological impact of multiple invaders within the same guild.

Bacterial diseases of banana are a growing global threat, causing yield losses and increased management costs. Major diseases include Moko, banana blood disease (BBD), and banana Xanthomonas wilt (BXW), caused by Ralstonia solanacearum, Ralstonia syzygii subsp. celebesensis, and Xanthomonas vasicola pv. musacearum, respectively. Effective surveillance requires point-of-care diagnostics such as loop-mediated isothermal amplification (LAMP) for on-site use. We aimed to develop three LAMP assays to specifically detect the bacteria responsible for Moko, BBD and BXW, directly from banana tissues, using a simplified DNA extraction protocol. The BBD - and BXW-LAMP assays demonstrated 100% specificity, yielding negative results for a broad range of non-target bacteria, including closely related species as well as pathogenic and endophytic strains associated with banana, and positive results for all the tested target strains. For Moko disease, a duplex-LAMP assay was developed to detect all strains from the four globally most relevant sequevars: IIB-3, IIB-4, IIA-6, and IIA-24. The duplex-LAMP successfully detected all target strains, except one that was shown to be non-pathogenic to Cavendish bananas. All non-target strains tested negative, with the exception of a delayed signal for one strain belonging to Ralstonia thomasi, not associated with banana environment (hospital strain). These results were supported by an extensive in silico analysis conducted on 9,668 Burkholderiaceae and 7,483 Xanthomonadaceae genomes. Detection limits ranged from 0.1 pg/µl to 1 pg/µl DNA, and from 104 to 105 CFU/ml on banana tissues spiked with calibrated bacterial suspensions, depending on the assay. The LAMP assays prove highly effective for detecting target pathogens in both artificially inoculated banana plants and field samples, offering a promising tool for improving disease management strategies.

Data science methods can provide novel and pragmatic approaches for preventing and controlling non-communicable diseases (NCDs) in Africa. This study highlights current efforts, opportunities, and challenges in leveraging data science methods to accelerate and advance the prevention and control of NCDs in Africa. We undertake a systematic review and gap analysis, as registered in PROSPERO (CRD42023406237). Our findings suggest several data science methods have been used in research across the four leading NCDs in Africa. However, limited information exists on their application to improve disease surveillance, risk factor identification and characterization, prevention, treatment, drug discovery and rehabilitation. Machine learning outperforms traditional statistical methods in improving risk stratification in most studies (80.8%) designed for the prevention and control of NCDs. Notwithstanding, most (76.0%) data science techniques for NCDs prevention and control remain in the exploratory research phase, with limited clinical or public health application and minimal impact on the African population. There are critical gaps along the continuum of data generation, data quality, method development, and validation, which may be attributed to inadequate funding, capacity development, policy shortcomings, and infrastructure deficits. Considerable gaps exist in intra-African collaboration, data sharing, and replication, which hinder the cross-cultural replication and applicability of data science methods for NCDs prevention and control in Africa. Multi-sectoral interventions that promote interdisciplinary capacity building, investment, and knowledge linkages, taking into account indigenous epistemologies, are needed to harness the enormous potential of data science to accelerate the prevention and control of NCDs in Africa. Data science offers innovative and practical approaches for accelerating the prevention and control of non-communicable diseases (NCDs). However, there are significant limitations that hinder their use for improving health outcomes in Africa. We highlight current efforts, opportunities, and challenges in leveraging data science to accelerate the prevention and control of NCDs in Africa. Most data science applications for NCD prevention and control in Africa remain in the exploratory phase, thereby limiting real-world clinical or public health utility. Multi-sectoral interventions that promote interdisciplinary capacity building, investment, and the linking of datasets are needed to harness the enormous potential of data science to accelerate the prevention and control of NCDs in Africa.

A high prevalence of onchocerciasis-associated epilepsy (OAE) has been observed in onchocerciasis-endemic areas with high ongoing In Maridi County, an onchocerciasis endemic area in South Sudan with a high prevalence of OAE, we will conduct an exploratory case-control study enrolling 40 persons aged 12 years and above with palpable onchocerciasis nodules. Cases will be participants with OAE (n=20), who will be age- and village-matched with controls without epilepsy (n=20). For each study participant, two skin snips at the iliac crest will be obtained to collect The protocol has been approved by the Ethics Committee of the University of Antwerp and the Ministry of Health of South Sudan. Findings will be disseminated nationally and internationally via meetings and peer-reviewed publications. ClinicalTrials.gov registration NCT05868551 ( https://clinicaltrials.gov/study/NCT05868551). 1.1, dated 09/05/2023.

The East African Community (EAC) grapples with many challenges in tackling infectious disease threats and antimicrobial resistance (AMR), underscoring the importance of regional and robust pathogen genomics capacities. However, a significant disparity exists among EAC Partner States in harnessing bacterial pathogen sequencing and data analysis capabilities for effective AMR surveillance and outbreak response. This study assesses the current landscape and challenges associated with pathogen next-generation sequencing (NGS) within EAC, explicitly focusing on World Health Organization (WHO) AMR-priority pathogens. The assessment adopts a comprehensive approach, integrating a questionnaire-based survey amongst National Public Health Laboratories (NPHLs) with an analysis of publicly available metadata on bacterial pathogens isolated in the EAC countries. In addition to the heavy reliance on third-party organizations for bacterial NGS, the findings reveal a significant disparity among EAC member States in leveraging bacterial pathogen sequencing and data analysis. Approximately 97% (n = 4,462) of publicly available high-quality bacterial genome assemblies of samples collected in the EAC were processed and analyzed by external organizations, mainly in Europe and North America. Tanzania led in-country sequencing efforts, followed by Kenya and Uganda. The other EAC countries had no publicly available samples or had all their samples sequenced and analyzed outside the region. Insufficient local NGS sequencing facilities, limited bioinformatics expertise, lack of adequate computing resources, and inadequate data-sharing mechanisms are among the most pressing challenges that hinder the EAC's NPHLs from effectively leveraging pathogen genomics data. These insights emphasized the need to strengthen microbial pathogen sequencing and data analysis capabilities within the EAC to empower these laboratories to conduct pathogen sequencing and data analysis independently. Substantial investments in equipment, technology, and capacity-building initiatives are crucial for supporting regional preparedness against infectious disease outbreaks and mitigating the impact of AMR burden. In addition, collaborative efforts should be developed to narrow the gap, remedy regional imbalances, and harmonize NGS data standards. Supporting regional collaboration, strengthening in-country genomics capabilities, and investing in long-term training programs will ultimately improve pathogen data generation and foster a robust NGS-driven AMR surveillance and outbreak response in the EAC, thereby supporting global health initiatives.

Leptospirosis is a neglected emerging and zoonotic disease reported worldwide. This study sought to determine the molecular and serological prevalence of Leptospira spp. and the associated risk factors in slaughtered cattle from the Bahr El Ghazal region of South Sudan. Between January 16th and February 25th, 2023, blood and urine samples were collected from 402 cattle at the Lokoloko Municipal Slaughterhouse in Western Bahr El-Ghazal State. Serum samples were tested using the microscopic agglutination test (MAT), with a panel of 12 serovars (sv) from 12 serogroups (sg) and 4 species (spp) of Leptospira spp. These serovars had been previously identified in Sudan and the East African region. Simultaneously, 400 corresponding urine samples were screened using qualitative real-time polymerase chain reaction (PCR) to detect the shedding of Leptospira spp. in urine. To identify the associated risk factors, the age, sex, breed and body condition score of each sampled cattle was noted at the time of sampling and subsequently analysed using logistic regression models. Among the 402 serum samples screened, a substantial 81.8% (329/402, 95% CI 77.9-85.3) displayed seropositivity for Leptospira spp. with a MAT titre ≥ 100. The prevalence of urine shedding determined by PCR was 6% (23/400, 95% CI 3.8-8.4), while probable recent leptospirosis with a MAT ≥ 1:800 was observed in 33.1% (133/402, 95% CI 28.6-37.8) of the cattle. Multiple reactions were detected in 34.8% (140/402, 95% CI 30.6-39.5) serum samples. The seropositivity was against L. borgpetersenii sg. Tarassovi (78.6%; 316/402, 95% CI 74.4-82.3), followed by L. borgpetersenii sg. Ballum at 20.4% (82/402, 95% CI, 16.7-24.4%), L. kirschneri sg. Autumnalis At 8.7% (35/402, 95% CI 5.7-11.7), L. interrogans sg. of Pomona at 7.0% (28/402, 95% CI 4.5-9.5), and L. interrogans sg. Hebdomadis was 5.0% (20/402, 95% CI 2.8-7.2). Several risk factors are associated with seropositivity. Older animals (≥ 2 years) had 2.0 times greater odds (95% CI 1.14-3.5) of being seropositive than younger animals (< 2 years), P-value = 0.016. Female animals demonstrated 2.1 times greater odds (95% CI 1.2-3.6) of seropositivity than males did (P-value = 0.008). Additionally, Felata/Mbororo cattle exhibited 2.4 times greater odds (95% CI 1.3-4.5) of being seropositive than did local Nilotic cattle (P-value = 0.005). The agreement between the MAT and PCR results was poor, as indicated by a kappa statistic value of 0.001 and a P-value of 0.913. But there was a moderate agreement between MAT high titres ≥ 800 and PCR positivity with a kappa statistic value = 0.501 and a P-value < 0.001. In addition to the high seroprevalence, Leptospira spp. were found in the urine of slaughtered cattle, suggesting that leptospirosis is endemic to the study area. This finding underscores the significance of cattle as potential sources of infection for slaughterhouse workers, the general public, and other animal species. To address this issue effectively in the Bahr El Ghazal Region and South Sudan, a comprehensive strategy involving a multidisciplinary approach is essential to minimize disease among animals, hence reducing potential zoonotic risks to humans.

The East African Community (EAC) is experiencing an unprecedented, emerging mpox outbreak since July 2024 in five of eight partner states. We highlight rapid regional response measures, initiated August 2024 coordinated by EAC: field deployment of six mobile laboratories in Burundi, Rwanda, Uganda, Tanzania, Kenya, South Sudan to high-risk areas, donation of one mobile laboratory to Democratic Republic of the Congo and genomic monkeypox virus (MPXV) surveillance support. These interventions aim to limit local mpox spread and support international containment.

In April 2023, an outbreak of acute hepatitis was reported amongst internally displaced persons in the Nazareth community of South Sudan. IgM serology-based screening suggested the likely etiologic agent to be Hepatitis E virus (HEV). In this study, plasma specimens collected from anti-HEV IgM-positive cases were subjected to additional RT-qPCR testing and sequencing of extracted nucleic acids, resulting in the recovery of five full and eight partial HEV genomes. Maximum likelihood phylogenetic reconstruction confirmed the genomes belong to HEV genotype 1. Using distance-based methods, we show that genotype 1 is best split into three sub-genotypes instead of the previously proposed seven, and that these sub-genotypes are geographically restricted. The South Sudanese sequences confidently cluster within sub-genotype 1e, endemic to northeast, central, and east Africa. Bayesian Inference of phylogeny incorporating sampling dates shows that this new outbreak is not directly descended from other recent local outbreaks for which sequence data is available. However, the analysis suggests that sub-genotype 1e has been consistently and cryptically circulating locally for at least the past half century and that the known outbreaks are often not directly descended from one another. The ongoing presence of HEV, combined with poor sanitation and hygiene in the conflict-affected areas in the region, place vulnerable populations at risk for infection and its more serious effects, including progression to fulminant hepatitis.