Anti-merozoite antibodies induce natural killer cell effector function and are associated with immunity against malaria.

Natural killer (NK) cells are potent immune effectors that can be activated via antibody-mediated Fc receptor engagement. Using multiparameter flow cytometry, we found that NK cells degranulate and release IFN-γ upon stimulation with antibody-opsonized Plasmodium falciparum merozoites. Antibody-dependent NK (Ab-NK) activity was largely strain transcending and enhanced invasion inhibition into erythrocytes. Ab-NK was associated with the successful control of parasitemia after experimental malaria challenge in African adults. In an independent cohort study in children, Ab-NK increased with age, was boosted by concurrent P. falciparum infections, and was associated with a lower risk of clinical episodes of malaria. Nine of the 14 vaccine candidates tested induced Ab-NK, including some less well-characterized antigens: P41, P113, MSP11, RHOPH3, and Pf_11363200. These data highlight an important role of Ab-NK activity in immunity against malaria and provide a potential mechanism for evaluating vaccine candidates.

Malaria attributable fractions with changing transmission intensity: Bayesian latent class vs logistic models.

BACKGROUND: Asymptomatic carriage of malaria parasites is common in high transmission intensity areas and confounds clinical case definitions for research studies. This is important for investigations that aim to identify immune correlates of protection from clinical malaria. The proportion of fevers attributable to malaria parasites is widely used to define different thresholds of parasite density associated with febrile episodes. The varying intensity of malaria transmission was investigated to check whether it had a significant impact on the parasite density thresholds. The same dataset was used to explore an alternative statistical approach, using the probability of developing fevers as a choice over threshold cut-offs. The former has been reported to increase predictive power. METHODS: Data from children monitored longitudinally between 2005 and 2017 from Junju and Chonyi in Kilifi, Kenya were used. Performance comparison of Bayesian-latent class and logistic power models in estimating malaria attributable fractions and probabilities of having fever given a parasite density with changing malaria transmission intensity was done using Junju cohort. Zero-inflated beta regressions were used to assess the impact of using probabilities to evaluate anti-merozoite antibodies as correlates of protection, compared with multilevel binary regression using data from Chonyi and Junju. RESULTS: Malaria transmission intensity declined from over 49% to 5% between 2006 and 2017, respectively. During this period, malaria attributable fraction varied between 27-59% using logistic regression compared to 10-36% with the Bayesian latent class approach. Both models estimated similar patterns of fevers attributable to malaria with changing transmission intensities. The Bayesian latent class model performed well in estimating the probabilities of having fever, while the latter was efficient in determining the parasite density threshold. However, compared to the logistic power model, the Bayesian algorithm yielded lower estimates for both attributable fractions and probabilities of fever. In modelling the association of merozoite antibodies and clinical malaria, both approaches resulted in comparable estimates, but the utilization of probabilities had a better statistical fit. CONCLUSIONS: Malaria attributable fractions, varied with an overall decline in the malaria transmission intensity in this setting but did not significantly impact the outcomes of analyses aimed at identifying immune correlates of protection. These data confirm the statistical advantage of using probabilities over binary data.

Controlled human malaria infection (CHMI) outcomes in Kenyan adults is associated with prior history of malaria exposure and anti-schizont antibody response.

BACKGROUND: Individuals living in endemic areas acquire immunity to malaria following repeated parasite exposure. We sought to assess the controlled human malaria infection (CHMI) model as a means of studying naturally acquired immunity in Kenyan adults with varying malaria exposure. METHODS: We analysed data from 142 Kenyan adults from three locations representing distinct areas of malaria endemicity (Ahero, Kilifi North and Kilifi South) enrolled in a CHMI study with Plasmodium falciparum sporozoites NF54 strain (Sanaria® PfSPZ Challenge). To identify the in vivo outcomes that most closely reflected naturally acquired immunity, parameters based on qPCR measurements were compared with anti-schizont antibody levels and residence as proxy markers of naturally acquired immunity. RESULTS: Time to endpoint correlated more closely with anti-schizont antibodies and location of residence than other parasite parameters such as growth rate or mean parasite density. Compared to observational field-based studies in children where 0.8% of the variability in malaria outcome was observed to be explained by anti-schizont antibodies, in the CHMI model the dichotomized anti-schizont antibodies explained 17% of the variability. CONCLUSIONS: The CHMI model is highly effective in studying markers of naturally acquired immunity to malaria. Trial registration Clinicaltrials.gov number NCT02739763. Registered 15 April 2016.

Distinct kinetics of antibodies to 111 Plasmodium falciparum proteins identifies markers of recent malaria exposure.

Strengthening malaria surveillance is a key intervention needed to reduce the global disease burden. Reliable serological markers of recent malaria exposure could improve current surveillance methods by allowing for accurate estimates of infection incidence from limited data. We studied the IgG antibody response to 111 Plasmodium falciparum proteins in 65 adult travellers followed longitudinally after a natural malaria infection in complete absence of re-exposure. We identified a combination of five serological markers that detect exposure within the previous three months with >80% sensitivity and specificity. Using mathematical modelling, we examined the antibody kinetics and determined that responses informative of recent exposure display several distinct characteristics: rapid initial boosting and decay, less inter-individual variation in response kinetics, and minimal persistence over time. Such serological exposure markers could be incorporated into routine malaria surveillance to guide efforts for malaria control and elimination.

protGear: A protein microarray data pre-processing suite.

Protein microarrays are versatile tools for high throughput study of the human proteome, but systematic and non-systematic sources of bias constrain optimal interpretation and the ultimate utility of the data. Published guidelines to limit technical variability whilst maintaining important biological variation favour DNA-based microarrays that often differ fundamentally in their experimental design. Rigorous tools to guide background correction, the quantification of within-sample variation, normalisation, and batch correction specifically for protein microarrays are limited, require extensive investigation and are not centrally accessible. Here, we develop a generic one-stop-shop pre-processing suite for protein microarrays that is compatible with data from the major protein microarray scanners. Our graphical and tabular interfaces facilitate a detailed inspection of data and are coupled with supporting guidelines that enable users to select the most appropriate algorithms to systematically address bias arising in customized experiments. The localization and distribution of background signal intensities determine the optimal correction strategy. A novel function overcomes the limitations in the interpretation of the coefficient of variation when signal intensities are at the lower end of the detection threshold. We demonstrate essential considerations in the experimental design and their impact on a range of algorithms for normalization and minimization of batch effects. Our user-friendly interactive web-based platform eliminates the need for prowess in programming. The open-source R interface includes illustrative examples, generates an auditable record, enables reproducibility, and can incorporate additional custom scripts through its online repository. This versatility will enhance its broad uptake in the infectious disease and vaccine development community.

Serological Profiling for Malaria Surveillance Using a Standard ELISA Protocol.

The enzyme-linked immunosorbent assay (ELISA) is a reliable and relatively low-cost method for measuring soluble ligands such as antibodies and proteins in biological samples. For analysis of specific antibodies in serum, a capture antigen is immobilized onto a solid polystyrene surface from which it can capture the antibodies. The captured antibodies are subsequently detected using a secondary antibody conjugated to an enzyme. Detection is accomplished by addition of a colorimetric substrate, and the readout is absorbance (optical density). Here, we provide a detailed standardized ELISA protocol for the quantification of antibodies against malaria antigens.

KILchip v1.0: A Novel Plasmodium falciparum Merozoite Protein Microarray to Facilitate Malaria Vaccine Candidate Prioritization.

Passive transfer studies in humans clearly demonstrated the protective role of IgG antibodies against malaria. Identifying the precise parasite antigens that mediate immunity is essential for vaccine design, but has proved difficult. Completion of the Plasmodium falciparum genome revealed thousands of potential vaccine candidates, but a significant bottleneck remains in their validation and prioritization for further evaluation in clinical trials. Focusing initially on the Plasmodium falciparum merozoite proteome, we used peer-reviewed publications, multiple proteomic and bioinformatic approaches, to select and prioritize potential immune targets. We expressed 109 P. falciparum recombinant proteins, the majority of which were obtained using a mammalian expression system that has been shown to produce biologically functional extracellular proteins, and used them to create KILchip v1.0: a novel protein microarray to facilitate high-throughput multiplexed antibody detection from individual samples. The microarray assay was highly specific; antibodies against P. falciparum proteins were detected exclusively in sera from malaria-exposed but not malaria-naïve individuals. The intensity of antibody reactivity varied as expected from strong to weak across well-studied antigens such as AMA1 and RH5 (Kruskal-Wallis H test for trend: p < 0.0001). The inter-assay and intra-assay variability was minimal, with reproducible results obtained in re-assays using the same chip over a duration of 3 months. Antibodies quantified using the multiplexed format in KILchip v1.0 were highly correlated with those measured in the gold-standard monoplex ELISA [median (range) Spearman's R of 0.84 (0.65-0.95)]. KILchip v1.0 is a robust, scalable and adaptable protein microarray that has broad applicability to studies of naturally acquired immunity against malaria by providing a standardized tool for the detection of antibody correlates of protection. It will facilitate rapid high-throughput validation and prioritization of potential Plasmodium falciparum merozoite-stage antigens paving the way for urgently needed clinical trials for the next generation of malaria vaccines.

Molecular characterization and antibiotic resistance profiles of Salmonella isolated from fecal matter of domestic animals and animal products in Nairobi.

BACKGROUND: Salmonella has significant public health implications causing food borne and zoonotic diseases in humans. Treatment of infections due to Salmonella is becoming difficult due to emergence of drug resistant strains. There is therefore need to characterize the circulating non-typhoidal Salmonella (NTS) serovars in domestic animals and animal products in Kenya as well as determine their antibiotic resistance profiles. METHODS: A total of 740 fecal samples were collected from cows (n = 150), pigs (n = 182), chicken (n = 191) and chicken eggs (n = 217) from various markets and abattoirs in Nairobi. The prevalence of NTS serovars using culture techniques and biochemical tests, antimicrobial sensitivity testing using disc diffusion method of the commonly prescribed antibiotics and phylogenetic relationships using 16S rRNA were determined. RESULTS: The results showed that the overall prevalence of Salmonella was 3.8, 3.6, 5.9 and 2.6% for pigs, chicken, eggs and cows respectively. Two serovars were isolated S. Typhimurium (85%) and S. Enteritidis (15%) and these two serovars formed distinct clades on the phylogenetic tree. Forty percent of the isolates were resistant to one or more antibiotics. CONCLUSION: The isolation of Salmonella Typhimurium and Salmonella Enteritidis that are resistant to commonly used antibiotics from seemingly healthy animals and animal products poses a significant public health threat. This points to the need for regular surveillance to be carried out and the chain of transmission should be viewed to ascertain sources of contamination.