Abstract
BackgroundThe co-occurrence of human immunodeficiency virus (HIV) infection and malaria in humans in endemic areas raises the question of whether one of these infections affects the course of the other. Although epidemiological studies have shown the impact of HIV infection on malaria, the mechanism(s) are not yet fully understood. Using a Chinese rhesus macaque coinfection model with simian immunodeficiency virus (SIV) and Plasmodium cynomolgi (Pc) malaria, we investigated the effect of concurrent SIV infection on the course of malaria and the underlying immunological mechanism(s).MethodsWe randomly assigned ten Chinese rhesus monkeys to two groups based on body weight and age. The SIV-Pc coinfection animals (S + P group) were infected intravenously with SIVmac251 eight weeks prior to malaria infection, and the control animals (P group) were infected intravenously with only Pc-infected red blood cells. After malaria was cured with chloroquine phosphate, we also initiated a secondary malaria infection that lasted 4 weeks.We monitored body weight, body temperature and parasitemia, measured SIV viral loads, hemoglobin and neopterin, and tracked the CD4+, CD8+, and CD4+ memory subpopulations, Ki67 and apoptosis by flow cytometry. Then, we compared these parameters between the two groups.ResultsThe animals infected with SIV prior to Pc infection exhibited more severe malaria symptoms characterized by longer episodes, higher parasitemia, more severe anemia, greater body weight loss and higher body temperature than the animals infected with Pc alone. Concurrent SIV infection also impaired immune protection against the secondary Pc challenge infection. The coinfected animals showed a reduced B cell response to Pc malaria and produced lower levels of Pc-specific antibodies. In addition, compared to the animals subjected to Pc infection alone, the animals coinfected with SIV and Pc had suppressed total CD4+ T cells, CD4+CD28highCD95high central memory T cells, and CD4+CD28lowCD95− naïve T cells, which may result from the imbalanced immune activation and faster CD4+ T cell turnover in coinfected animals.ConclusionsSIV infection aggravates malaria physiologically and immunologically in Chinese rhesus monkeys. This nonhuman primate SIV and Pc malaria coinfection model might be a useful tool for investigating human HIV and malaria coinfection and developing effective therapeutics.
Highlights
The co-occurrence of human immunodeficiency virus (HIV) infection and malaria in humans in endemic areas raises the question of whether one of these infections affects the course of the other
Limited clinical and experimental studies showed that impaired immune activation, reduced anti-malaria antibody production and subsequent immunosuppression were associated with an increased frequency of clinical malaria and parasitemia in HIV-infected individuals [9,10,11,12,13,14]
Eight weeks after simian immunodeficiency virus (SIV) infection, animals in both the S + P and P groups were subjected to Plasmodium cynomolgi (Pc) infection when the viral loads in the animals in the S + P group decreased to a stable level
Summary
The co-occurrence of human immunodeficiency virus (HIV) infection and malaria in humans in endemic areas raises the question of whether one of these infections affects the course of the other. Epidemiological studies have shown the impact of HIV infection on malaria, the mechanism(s) are not yet fully understood. Given that the endemic regions of Plasmodium and HIV infection overlap extensively and that many people are infected, there is an increased risk of coinfection with these two pathogens. Because these two infections have a profound impact on human health, many studies have been conducted to investigate the potential interactions between them. The incidence of malaria infection is increased in HIVendemic regions and in pregnant women [5, 6], and more severe clinical symptoms of malaria occur in HIV+ adults with partial immunity to the parasites [7, 8]. The immunological interaction between these two important infectious diseases is not fully understood
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