Assessment of genetic variability among groundnut accessions under natural rosette disease infestation in Malawi

Groundnut production in East and South African region is low due to several constraints. Success in development of resilient varieties rides on genetic diversity in available germplasm for key traits in question. This study was undertaken to dissect the magnitude of variability among groundnut accessions. The experimental design was an alpha lattice design replicated thrice. Significant differences in yield traits were observed among the accessions. There was high phenotypic (PCV) and genotypic (GCV) coefficient of variation in most of the traits except for the number of primary branches and shelling percentage. A combination of high heritability and genetic advance was recorded for the number of secondary branches, height, seed yield and rosette incidence. This indicates that it is possible to carry out phenotypic selection based on the mean for successful improvement of yield and resistance to rosette disease

Phenotypic correlation, path coefficient and multivariate analysis for yield and yield-associated traits in groundnut accessions

Yield is a complex quantitative trait largely influenced by the environment. Direct selection for grain yield is less efficient in improving groundnut productivity. The selection efficiency can be enhanced by exploiting the relationship between yield and its related traits. Moreover, the use of genetically diverse parents is essential to generate genetic variation for successful selection of genotypes in a breeding program. Therefore, the study aimed at analysing the relationship between grain yield and its related traits and determining the morphological diversity among selected groundnut genotypes under natural rosette disease (GRD) infestation. The genotypes were evaluated in a 7 × 4 alpha lattice design with three replications. Data were collected on yield and yield-related traits. Correlation, path coefficient and multivariate analyses were done. The results revealed that yield was directly associated with plant height, number of pods per plant, hundred seed weight, GRD incidence and number of secondary branches. Therefore, these traits should be considered in selection when improving groundnut for yield. Cluster analysis revealed existence of diversity among the evaluated groundnut genotypes with no influence of geographical origin to the clustering pattern. The Principal Components Analysis (PCA) biplot was effective in showing the genetic distance among the genotypes and the results were comparable with those of the cluster analysis. Moreover, Shannon-Weaver diversity indices revealed existence of high diversity among the genotypes, an implication that groundnut improvement for yield is possible through selection in breeding

Antigen-Specific T-Cell Activation Distinguishes between Recent and Remote Tuberculosis Infection

Rationale: Current diagnostic tests fail to identify individuals at higher risk of progression to tuberculosis disease, such as those with recent Mycobacterium tuberculosis infection, who should be prioritized for targeted preventive treatment. Objectives: To define a blood-based biomarker, measured with a simple flow cytometry assay, that can stratify different stages of tuberculosis infection to infer risk of disease. Methods: South African adolescents were serially tested with QuantiFERON-TB Gold to define recent (QuantiFERON-TB conversion 1 yr) infection. We defined the ΔHLA-DR median fluorescence intensity biomarker as the difference in HLA-DR expression between IFN-γ+ TNF+ Mycobacterium tuberculosis-specific T cells and total CD3+ T cells. Biomarker performance was assessed by blinded prediction in untouched test cohorts with recent versus persistent infection or tuberculosis disease and by unblinded analysis of asymptomatic adolescents with tuberculosis infection who remained healthy (nonprogressors) or who progressed to microbiologically confirmed disease (progressors). Measurements and Main Results: In the test cohorts, frequencies of Mycobacterium tuberculosis-specific T cells differentiated between QuantiFERON-TB- (n = 25) and QuantiFERON-TB+ (n = 47) individuals (area under the receiver operating characteristic curve, 0.94; 95% confidence interval, 0.87-1.00). ΔHLA-DR significantly discriminated between recent (n = 20) and persistent (n = 22) QuantiFERON-TB+ (0.91; 0.83-1.00); persistent QuantiFERON-TB+ and newly diagnosed tuberculosis (n = 19; 0.99; 0.96-1.00); and tuberculosis progressors (n = 22) and nonprogressors (n = 34; 0.75; 0.63-0.87). However, ΔHLA-DR median fluorescent intensity could not discriminate between recent QuantiFERON-TB+ and tuberculosis (0.67; 0.50-0.84). Conclusions: The ΔHLA-DR biomarker can identify individuals with recent QuantiFERON-TB conversion and those with disease progression, allowing targeted provision of preventive treatment to those at highest risk of tuberculosis. Further validation studies of this novel immune biomarker in various settings and populations at risk are warranted

Multidimensional analyses reveal modulation of adaptive and innate immune subsets by tuberculosis vaccines

We characterize the breadth, function and phenotype of innate and adaptive cellular responses in a prevention of Mycobacterium tuberculosis infection trial. Responses are measured by whole blood intracellular cytokine staining at baseline and 70 days after vaccination with H4:IC31 (subunit vaccine containing Ag85B and TB10.4), Bacille Calmette-Guerin (BCG, a live attenuated vaccine) or placebo (n = ~30 per group). H4:IC31 vaccination induces Ag85B and TB10.4-specific CD4 T cells, and an unexpected NKTlike subset, that expresses IFN-γ, TNF and/or IL-2. BCG revaccination increases frequencies of CD4 T cell subsets that either express Th1 cytokines or IL-22, and modestly increases IFNγ-producing NK cells. In vitro BCG re-stimulation also triggers responses by donor-unrestricted T cells, which may contribute to host responses against mycobacteria. BCG, which demonstrated efficacy against sustained Mycobacterium tuberculosis infection, modulates multiple immune cell subsets, in particular conventional Th1 and Th22 cells, which should be investigated in discovery studies of correlates of protection

T cell receptor repertoires associated with control and disease progression following Mycobacterium tuberculosis infection

Antigen-specific, MHC-restricted αβ T cells are necessary for protective immunity against Mycobacterium tuberculosis, but the ability to broadly study these responses has been limited. In the present study, we used single-cell and bulk T cell receptor (TCR) sequencing and the GLIPH2 algorithm to analyze M. tuberculosis-specific sequences in two longitudinal cohorts, comprising 166 individuals with M. tuberculosis infection who progressed to either tuberculosis (n = 48) or controlled infection (n = 118). We found 24 T cell groups with similar TCR-β sequences, predicted by GLIPH2 to have common TCR specificities, which were associated with control of infection (n = 17), and others that were associated with progression to disease (n = 7). Using a genome-wide M. tuberculosis antigen screen, we identified peptides targeted by T cell similarity groups enriched either in controllers or in progressors. We propose that antigens recognized by T cell similarity groups associated with control of infection can be considered as high-priority targets for future vaccine development

Biomarker-guided tuberculosis preventive therapy (CORTIS): a randomised controlled trial.

BACKGROUND: Targeted preventive therapy for individuals at highest risk of incident tuberculosis might impact the epidemic by interrupting transmission. We tested performance of a transcriptomic signature of tuberculosis (RISK11) and efficacy of signature-guided preventive therapy in parallel, using a hybrid three-group study design. METHODS: Adult volunteers aged 18-59 years were recruited at five geographically distinct communities in South Africa. Whole blood was sampled for RISK11 by quantitative RT-PCR assay from eligible volunteers without HIV, recent previous tuberculosis (ie, <3 years before screening), or comorbidities at screening. RISK11-positive participants were block randomised (1:2; block size 15) to once-weekly, directly-observed, open-label isoniazid and rifapentine for 12 weeks (ie, RISK11 positive and 3HP positive), or no treatment (ie, RISK11 positive and 3HP negative). A subset of eligible RISK11-negative volunteers were randomly assigned to no treatment (ie, RISK11 negative and 3HP negative). Diagnostic discrimination of prevalent tuberculosis was tested in all participants at baseline. Thereafter, prognostic discrimination of incident tuberculosis was tested in the untreated RISK11-positive versus RISK11-negative groups, and treatment efficacy in the 3HP-treated versus untreated RISK11-positive groups, during active surveillance through 15 months. The primary endpoint was microbiologically confirmed pulmonary tuberculosis. The primary outcome measures were risk ratio [RR] for tuberculosis of RISK11-positive to RISK11-negative participants, and treatment efficacy. This trial is registered with ClinicalTrials.gov, NCT02735590. FINDINGS: 20 207 volunteers were screened, and 2923 participants were enrolled, including RISK11-positive participants randomly assigned to 3HP (n=375) or no 3HP (n=764), and 1784 RISK11-negative participants. Cumulative probability of prevalent or incident tuberculosis disease was 0·066 (95% CI 0·049 to 0·084) in RISK11-positive (3HP negative) participants and 0·018 (0·011 to 0·025) in RISK11-negative participants (RR 3·69, 95% CI 2·25-6·05) over 15 months. Tuberculosis prevalence was 47 (4·1%) of 1139 versus 14 (0·78%) of 1984 in RISK11-positive compared with RISK11-negative participants, respectively (diagnostic RR 5·13, 95% CI 2·93 to 9·43). Tuberculosis incidence over 15 months was 2·09 (95% CI 0·97 to 3·19) vs 0·80 (0·30 to 1·30) per 100 person years in RISK11-positive (3HP-negative) participants compared with RISK11-negative participants (cumulative incidence ratio 2·6, 95% CI 1·2 to 5·9). Serious adverse events related to 3HP included one hospitalisation for seizures (unintentional isoniazid overdose) and one death of unknown cause (possibly temporally related). Tuberculosis incidence over 15 months was 1·94 (95% CI 0·35 to 3·50) versus 2·09 (95% CI 0·97 to 3·19) per 100 person-years in 3HP-treated RISK11-positive participants compared with untreated RISK11-positive participants (efficacy 7·0%, 95% CI -145 to 65). INTERPRETATION: The RISK11 signature discriminated between individuals with prevalent tuberculosis, or progression to incident tuberculosis, and individuals who remained healthy, but provision of 3HP to signature-positive individuals after exclusion of baseline disease did not reduce progression to tuberculosis over 15 months. FUNDING: Bill and Melinda Gates Foundation, South African Medical Research Council

Validation of a host blood transcriptomic biomarker for pulmonary tuberculosis in people living with HIV: a prospective diagnostic and prognostic accuracy study.

BACKGROUND: A rapid, blood-based triage test that allows targeted investigation for tuberculosis at the point of care could shorten the time to tuberculosis treatment and reduce mortality. We aimed to test the performance of a host blood transcriptomic signature (RISK11) in diagnosing tuberculosis and predicting progression to active pulmonary disease (prognosis) in people with HIV in a community setting. METHODS: In this prospective diagnostic and prognostic accuracy study, adults (aged 18-59 years) with HIV were recruited from five communities in South Africa. Individuals with a history of tuberculosis or household exposure to multidrug-resistant tuberculosis within the past 3 years, comorbid risk factors for tuberculosis, or any condition that would interfere with the study were excluded. RISK11 status was assessed at baseline by real-time PCR; participants and study staff were masked to the result. Participants underwent active surveillance for microbiologically confirmed tuberculosis by providing spontaneously expectorated sputum samples at baseline, if symptomatic during 15 months of follow-up, and at 15 months (the end of the study). The coprimary outcomes were the prevalence and cumulative incidence of tuberculosis disease confirmed by a positive Xpert MTB/RIF, Xpert Ultra, or Mycobacteria Growth Indicator Tube culture, or a combination of such, on at least two separate sputum samples collected within any 30-day period. FINDINGS: Between March 22, 2017, and May 15, 2018, 963 participants were assessed for eligibility and 861 were enrolled. Among 820 participants with valid RISK11 results, eight (1%) had prevalent tuberculosis at baseline: seven (2·5%; 95% CI 1·2-5·0) of 285 RISK11-positive participants and one (0·2%; 0·0-1·1) of 535 RISK11-negative participants. The relative risk (RR) of prevalent tuberculosis was 13·1 times (95% CI 2·1-81·6) greater in RISK11-positive participants than in RISK11-negative participants. RISK11 had a diagnostic area under the receiver operating characteristic curve (AUC) of 88·2% (95% CI 77·6-96·7), and a sensitivity of 87·5% (58·3-100·0) and specificity of 65·8% (62·5-69·0) at a predefined score threshold (60%). Of those with RISK11 results, eight had primary endpoint incident tuberculosis during 15 months of follow-up. Tuberculosis incidence was 2·5 per 100 person-years (95% CI 0·7-4·4) in the RISK11-positive group and 0·2 per 100 person-years (0·0-0·5) in the RISK11-negative group. The probability of primary endpoint incident tuberculosis was greater in the RISK11-positive group than in the RISK11-negative group (cumulative incidence ratio 16·0 [95% CI 2·0-129·5]). RISK11 had a prognostic AUC of 80·0% (95% CI 70·6-86·9), and a sensitivity of 88·6% (43·5-98·7) and a specificity of 68·9% (65·3-72·3) for incident tuberculosis at the 60% threshold. INTERPRETATION: RISK11 identified prevalent tuberculosis and predicted risk of progression to incident tuberculosis within 15 months in ambulant people living with HIV. RISK11's performance approached, but did not meet, WHO's target product profile benchmarks for screening and prognostic tests for tuberculosis. FUNDING: Bill & Melinda Gates Foundation and the South African Medical Research Council

Genotype x environment interaction analysis of soybean (Glycine max (L.) Merrill) grain yield across production environments in southern Africa

Development of high yielding and stable cultivars of various crops across the Southern African Development Community (SADC) member states is in line with the recently enacted SADC’s seed harmonisation act. This study, therefore, focused on evaluating soybean [Glycine max (L.) Merrill] lines developed by the International Institute of Tropical Agriculture (IITA) for yield and stability across SADC test environments using the additive main effects and multiplicative interaction (AMMI) analysis. Twenty-five elite lines (five checks and 20 experimental) were evaluated at six locations across four SADC countries during the 2017/18 season in a 5*5 alpha lattice design, replicated three times at each location. The locations were: IITA-SARA, Lusaka West and Chipata in Zambia; Chitedze in Malawi; Nampula in Mozambique; and Rattray Arnold Research Station in Zimbabwe. The environment, genotype, and genotype x environment interaction (GEI) effects were highly significant (p < 0.001), with contributions to total observed variation of 21.04 %, 31.59 % and 47.36 %, respectively. The first two interaction principal component axes (IPCA1 and IPCA2) explained 44 % and 22 %, respectively of the variation due to GEI. Twelve genotypes (48 %) yielded above the grand mean of 3146.31 kg/ha. Check variety SC SAFARI was the highest yielder across environments followed by experimental lines TGx2014-5GM and TGx2002-23DM. Lines TGx2002-17DM, TGx2001-10DM, TGx2001-18DM, TGx2014-24FM, TGx2001-6FM and TGx2002-3DM were winners in Chitedze, Nampula, IITA-SARAH, Lusaka West, Chipata and Rattray Arnold Research Station, respectively. Since TGx2014-5GM was the most stable among all the genotypes across environments, highest yielder (4143 kg/ha) among the experimental lines and second to the highest yielding check (SC Safari), it is therefore recommended for release for production in the SADC after further evaluation. Lusaka West was the highest yielding environment and exhibited strongest interactive forces whilst Nambula had weakest interactive forces

Validation of Correlates of Risk of TB Disease in High Risk Populations (CORTIS-HR) Study: Public, subject-level RISK11 signature scores and metadata

The Validation of Correlates of Risk of TB Disease in High Risk Populations (CORTIS-HR) Study, a companion study of the CORTIS-01 Trial (ClinicalTrials.gov: NCT02735590), was conducted to test the diagnostic and prognostic performance of the RISK11 biomarker for tuberculosis (TB) disease in people living with HIV (PLHIV) in an ambulant community setting. The “CORTIS-HR pubdata.csv” is a public, subject-level dataset for the CORTIS-HR study containing key variables necessary to reconstruct the study findings. A data dictionary is provided below. The “CORTIS-HR PCR data.csv” provides subject-level TaqMan qPCR probe raw CT (cycle threshold) gene expression data from the Fluidigm microfluidic 96.96 Gene Expression Integrated Fluidic Circuits (chips) with sample quality control (“SAMPLE_QC”) results. Analyses of the qPCR probe data are ongoing; the embargo on this data ends 1 July 2021 when the data will be available on ZivaHub. “CORTIS-HR Protocol Version 1.0.pdf” and “CORTIS-HR SAP Version 1.0.pdf” are the protocol and the statistical analysis plan for the study respectively and have been included for reference