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Introduction: Non-malaria febrile illnesses such as bacterial bloodstream infections (BSI) are a leading cause of disease and mortality in the tropics. However, there are no reliable, simple diagnostic tests for identifying BSI or other severe non-malaria febrile illnesses. We hypothesized that different infectious agents responsible for severe febrile illness would impact on the host metabolome in different ways, and investigated the potential of plasma metabolites for diagnosis of non-malaria febrile illness., Methodology: We conducted a comprehensive mass-spectrometry based metabolomics analysis of the plasma of 61 children with severe febrile illness from a malaria-endemic rural African setting. Metabolite features characteristic for non-malaria febrile illness, BSI, severe anemia and poor clinical outcome were identified by receiver operating curve analysis., Principal Findings: The plasma metabolome profile of malaria and non-malaria patients revealed fundamental differences in host response, including a differential activation of the hypothalamic-pituitary-adrenal axis. A simple corticosteroid signature was a good classifier of severe malaria and non-malaria febrile patients (AUC 0.82, 95% CI: 0.70-0.93). Patients with BSI were characterized by upregulated plasma bile metabolites; a signature of two bile metabolites was estimated to have a sensitivity of 98.1% (95% CI: 80.2-100) and a specificity of 82.9% (95% CI: 54.7-99.9) to detect BSI in children younger than 5 years. This BSI signature demonstrates that host metabolites can have a superior diagnostic sensitivity compared to pathogen-detecting tests to identify infections characterized by low pathogen load such as BSI., Conclusions: This study demonstrates the potential use of plasma metabolites to identify causality in children with severe febrile illness in malaria-endemic settings.

The species of the Leishmania donovani species complex cause visceral leishmaniasis, a debilitating infectious disease transmitted by sandflies. Understanding molecular changes associated with population structure in these parasites can help unravel their epidemiology and spread in humans. In this study, we used a panel of standard microsatellite loci and genome-wide SNPs to investigate population-level diversity in L. donovani strains recently isolated from a small geographic area spanning India, Bihar and Nepal, and compared their variation to that found in diverse strains of the L. donovani complex isolates from Europe, Africa and Asia. Microsatellites and SNPs could clearly resolve the phylogenetic relationships of the strains between continents, and microsatellite phylogenies indicated that certain older Indian strains were closely related to African strains. In the context of the anti-malaria spraying campaigns in the 1960s, this was consistent with a pattern of episodic population size contractions and clonal expansions in these parasites that was supported by population history simulations. In sharp contrast to the low resolution provided by microsatellites, SNPs retained a much more fine-scale resolution of population-level variability to the extent that they identified four different lineages from the same region one of which was more closely related to African and European strains than to Indian or Nepalese ones. Joining results of in vitro testing the antimonial drug sensitivity with the phylogenetic signals from the SNP data highlighted protein-level mutations revealing a distinct drug-resistant group of Nepalese and Indian L. donovani. This study demonstrates the power of genomic data for exploring parasite population structure. Furthermore, markers defining different genetic groups have been discovered that could potentially be applied to investigate drug resistance in clinical Leishmania strains., (Copyright © 2011 Elsevier B.V. All rights reserved.)