Gordon Dougan and colleagues report whole-genome sequencing of a global collection of 179 Salmonella Typhimurium isolates, including 129 diverse sub-Saharan African isolates associated with invasive disease. They determine the phylogenetic structure of invasive Salmonella Typhimurium in sub-Saharan Africa and find that the majority are from two closely related highly conserved lineages, which emerged in the last 60 years in close temporal association with the current HIV epidemic. A highly invasive form of non-typhoidal Salmonella (iNTS) disease has recently been documented in many countries in sub-Saharan Africa. The most common Salmonella enterica serovar causing this disease is Typhimurium (Salmonella Typhimurium). We applied whole-genome sequence–based phylogenetic methods to define the population structure of sub-Saharan African invasive Salmonella Typhimurium isolates and compared these to global Salmonella Typhimurium populations. Notably, the vast majority of sub-Saharan invasive Salmonella Typhimurium isolates fell within two closely related, highly clustered phylogenetic lineages that we estimate emerged independently ∼52 and ∼35 years ago in close temporal association with the current HIV pandemic. Clonal replacement of isolates from lineage I by those from lineage II was potentially influenced by the use of chloramphenicol for the treatment of iNTS disease. Our analysis suggests that iNTS disease is in part an epidemic in sub-Saharan Africa caused by highly related Salmonella Typhimurium lineages that may have occupied new niches associated with a compromised human population and antibiotic treatment.

Case fatality rates among African children with cerebral malaria remain in the range of 15 to 25%. The key pathogenetic processes and causes of death are unknown, but a combination of clinical observations and pathological findings suggests that increased brain volume leading to raised intracranial pressure may play a role. Magnetic resonance imaging (MRI) became available in Malawi in 2009, and we used it to investigate the role of brain swelling in the pathogenesis of fatal cerebral malaria in African children. We enrolled children who met a stringent definition of cerebral malaria (one that included the presence of retinopathy), characterized them in detail clinically, and obtained MRI scans on admission and daily thereafter while coma persisted. Of 348 children admitted with cerebral malaria (as defined by the World Health Organization), 168 met the inclusion criteria, underwent all investigations, and were included in the analysis. A total of 25 children (15%) died, 21 of whom (84%) had evidence of severe brain swelling on MRI at admission. In contrast, evidence of severe brain swelling was seen on MRI in 39 of 143 survivors (27%). Serial MRI scans showed evidence of decreasing brain volume in the survivors who had had brain swelling initially. Increased brain volume was seen in children who died from cerebral malaria but was uncommon in those who did not die from the disease, a finding that suggests that raised intracranial pressure may contribute to a fatal outcome. The natural history indicates that increased intracranial pressure is transient in survivors. (Funded by the National Institutes of Health and Wellcome Trust U.K.)

Cryptococcal meningitis accounts for more than 100,000 human immunodeficiency virus (HIV)–related deaths per year. We tested two treatment strategies that could be more sustainable in Africa than the standard of 2 weeks of amphotericin B plus flucytosine and more effective than the widely used fluconazole monotherapy. We randomly assigned HIV-infected adults with cryptococcal meningitis to receive an oral regimen (fluconazole [1200 mg per day] plus flucytosine [100 mg per kilogram of body weight per day] for 2 weeks), 1 week of amphotericin B (1 mg per kilogram per day), or 2 weeks of amphotericin B (1 mg per kilogram per day). Each patient assigned to receive amphotericin B was also randomly assigned to receive fluconazole or flucytosine as a partner drug. After induction treatment, all the patients received fluconazole consolidation therapy and were followed to 10 weeks. A total of 721 patients underwent randomization. Mortality in the oral-regimen, 1-week amphotericin B, and 2-week amphotericin B groups was 18.2% (41 of 225), 21.9% (49 of 224), and 21.4% (49 of 229), respectively, at 2 weeks and was 35.1% (79 of 225), 36.2% (81 of 224), and 39.7% (91 of 229), respectively, at 10 weeks. The upper limit of the one-sided 97.5% confidence interval for the difference in 2-week mortality was 4.2 percentage points for the oral-regimen group versus the 2-week amphotericin B groups and 8.1 percentage points for the 1-week amphotericin B groups versus the 2-week amphotericin B groups, both of which were below the predefined 10-percentage-point noninferiority margin. As a partner drug with amphotericin B, flucytosine was superior to fluconazole (71 deaths [31.1%] vs. 101 deaths [45.0%]; hazard ratio for death at 10 weeks, 0.62; 95% confidence interval [CI], 0.45 to 0.84; P=0.002). One week of amphotericin B plus flucytosine was associated with the lowest 10-week mortality (24.2%; 95% CI, 16.2 to 32.1). Side effects, such as severe anemia, were more frequent with 2 weeks than with 1 week of amphotericin B or with the oral regimen. One week of amphotericin B plus flucytosine and 2 weeks of fluconazole plus flucytosine were effective as induction therapy for cryptococcal meningitis in resource-limited settings. (ACTA Current Controlled Trials number, ISRCTN45035509.)

A major impediment to tuberculosis control in Africa is the difficulty in diagnosing active tuberculosis (TB), particularly in the context of HIV infection. We hypothesized that a unique host blood RNA transcriptional signature would distinguish TB from other diseases (OD) in HIV-infected and -uninfected patients, and that this could be the basis of a simple diagnostic test. Adult case-control cohorts were established in South Africa and Malawi of HIV-infected or -uninfected individuals consisting of 584 patients with either TB (confirmed by culture of Mycobacterium tuberculosis [M.TB] from sputum or tissue sample in a patient under investigation for TB), OD (i.e., TB was considered in the differential diagnosis but then excluded), or healthy individuals with latent TB infection (LTBI). Individuals were randomized into training (80%) and test (20%) cohorts. Blood transcriptional profiles were assessed and minimal sets of significantly differentially expressed transcripts distinguishing TB from LTBI and OD were identified in the training cohort. A 27 transcript signature distinguished TB from LTBI and a 44 transcript signature distinguished TB from OD. To evaluate our signatures, we used a novel computational method to calculate a disease risk score (DRS) for each patient. The classification based on this score was first evaluated in the test cohort, and then validated in an independent publically available dataset (GSE19491). In our test cohort, the DRS classified TB from LTBI (sensitivity 95%, 95% CI [87–100]; specificity 90%, 95% CI [80–97]) and TB from OD (sensitivity 93%, 95% CI [83–100]; specificity 88%, 95% CI [74–97]). In the independent validation cohort, TB patients were distinguished both from LTBI individuals (sensitivity 95%, 95% CI [85–100]; specificity 94%, 95% CI [84–100]) and OD patients (sensitivity 100%, 95% CI [100–100]; specificity 96%, 95% CI [93–100]). Limitations of our study include the use of only culture confirmed TB patients, and the potential that TB may have been misdiagnosed in a small proportion of OD patients despite the extensive clinical investigation used to assign each patient to their diagnostic group. In our study, blood transcriptional signatures distinguished TB from other conditions prevalent in HIV-infected and -uninfected African adults. Our DRS, based on these signatures, could be developed as a test for TB suitable for use in HIV endemic countries. Further evaluation of the performance of the signatures and DRS in prospective populations of patients with symptoms consistent with TB will be needed to define their clinical value under operational conditions. Please see later in the article for the Editors' Summary Tuberculosis (TB), caused by Mycobacterium tuberculosis, is curable and preventable, but according to the World Health Organization (WHO), in 2011, 8.7 million people had symptoms of TB (usually a productive cough and fever) and 1.4 million people—95% from low- and middle-income countries—died from this infection. Worldwide, TB is also the leading cause of death in people with HIV. For over a century, diagnosis of TB has relied on clinical and radiological features, sputum microscopy, and tuberculin skin testing but all of these tests have major disadvantages, especially in people who are also infected with HIV (HIV/TB co-infection) in whom results are often atypical or falsely negative. Furthermore, current tests cannot distinguish between inactive (latent) and active TB infection. Therefore, there is a need to identify biomarkers that can differentiate TB from other diseases common to African populations, where the burden of the HIV/TB pandemic is greatest. Previous studies have suggested that TB may be associated with specific transcriptional profiles (identified by microarray analysis) in the blood of the infected patient (host), which might make it possible to differentiate TB from other conditions. However, these studies have not included people co-infected with HIV and have included in the differential diagnosis diseases that are unrepresentative of the range of conditions common to African patients. In this study of patients from Malawi and South Africa, the researchers investigated whether blood RNA expression could distinguish TB from other conditions prevalent in African populations and form the basis of a diagnostic test for TB (through a process using transcription signatures). The researchers recruited patients with suspected TB attending one clinic in Cape Town, South Africa between 2007 and 2010 and in one hospital in Karonga district, Malawi between 2007 and 2009 (the training and test cohorts). Each patient underwent a series of tests for TB (and had a blood test for HIV) and was diagnosed as having TB if there was microbiological evidence confirming the presence of Mycobacterium tuberculosis. At recruitment, each patient also had blood taken for microarray analysis and following this assessment, the researchers selected minimal transcript sets that distinguished TB from latent TB infection and TB from other diseases, even in HIV-infected individuals. In order to help form the basis of a simple, low cost, diagnostic test, the researchers then developed a statistical method for the translation of multiple transcript RNA signatures into a disease risk score, which the researchers then checked using a separate cohort of South African patients (the independent validation cohort). Using these methods, after screening 437 patients in Malawi and 314 in South Africa, the researchers recruited 273 patients to the Malawi cohort and 311 adults to the South African cohort (the training and test cohorts). Following technical failures, 536 microarray samples were available for analysis. The researchers identified a set of 27 transcripts that could distinguish between TB and latent TB and a set of 44 transcripts that could distinguish TB from other diseases. These multi-transcript signatures were then used to calculate a single value disease risk score for every patient. In the test cohorts, the disease risk score had a high sensitivity (95%) and specificity (90%) for distinguishing TB from latent TB infection (sensitivity is a measure of true positives, correctly identified as such and specificity is a measure of true negatives, correctly identified as such) and for distinguishing TB from other diseases (sensitivity 93% and specificity 88%). In the independent validation cohort, the researchers found that patients with TB could be distinguished from patients with latent TB infection (sensitivity 95% and specificity 94%) and also from patients with other diseases (sensitivity 100% and specificity 96%). These findings suggest that a distinctive set of RNA transcriptional signatures forming a disease risk score might provide the basis of a diagnostic test that can distinguish active TB from latent TB infection (27 signatures) and also from other diseases (44 signatures), such as pneumonia, that are prevalent in African populations. There is a concern that using transcriptional signatures as a clinical diagnostic tool in resource poor settings might not be feasible because they are complex and costly. The relatively small number of transcripts in the signatures described here may increase the potential for using this approach (transcriptional profiling) as a clinical diagnostic tool using a single blood test. In order to make most use of these findings, there is an urgent need for the academic research community and for industry to develop innovative methods to translate multi-transcript signatures into simple, cheap tests for TB suitable for use in African health facilities. Please access these websites via the online version of this summary at http://dx.doi.org/ 10.1371/journal.pmed.1001538.

Improved diagnostic tests for tuberculosis in children are needed. We hypothesized that transcriptional signatures of host blood could be used to distinguish tuberculosis from other diseases in African children who either were or were not infected with the human immunodeficiency virus (HIV). The study population comprised prospective cohorts of children who were undergoing evaluation for suspected tuberculosis in South Africa (655 children), Malawi (701 children), and Kenya (1599 children). Patients were assigned to groups according to whether the diagnosis was culture-confirmed tuberculosis, culture-negative tuberculosis, diseases other than tuberculosis, or latent tuberculosis infection. Diagnostic signatures distinguishing tuberculosis from other diseases and from latent tuberculosis infection were identified from genomewide analysis of RNA expression in host blood. We identified a 51-transcript signature distinguishing tuberculosis from other diseases in the South African and Malawian children (the discovery cohort). In the Kenyan children (the validation cohort), a risk score based on the signature for tuberculosis and for diseases other than tuberculosis showed a sensitivity of 82.9% (95% confidence interval [CI], 68.6 to 94.3) and a specificity of 83.6% (95% CI, 74.6 to 92.7) for the diagnosis of culture-confirmed tuberculosis. Among patients with cultures negative for Mycobacterium tuberculosis who were treated for tuberculosis (those with highly probable, probable, or possible cases of tuberculosis), the estimated sensitivity was 62.5 to 82.3%, 42.1 to 80.8%, and 35.3 to 79.6%, respectively, for different estimates of actual tuberculosis in the groups. In comparison, the sensitivity of the Xpert MTB/RIF assay for molecular detection of M. tuberculosis DNA in cases of culture-confirmed tuberculosis was 54.3% (95% CI, 37.1 to 68.6), and the sensitivity in highly probable, probable, or possible cases was an estimated 25.0 to 35.7%, 5.3 to 13.3%, and 0%, respectively; the specificity of the assay was 100%. RNA expression signatures provided data that helped distinguish tuberculosis from other diseases in African children with and those without HIV infection. (Funded by the European Union Action for Diseases of Poverty Program and others).