Introduction

Vector-borne diseases (VBD) are a major cause of morbidity and mortality worldwide especially in the tropical and subtropical regions. In fact, according to a World Health Organization (WHO) report, approximately 80% of the world’s population is at risk of one or more vector-borne disease. Annually, over 700, 000 deaths are reported from VBDs, such as malaria, leishmaniasis, chagas disease, yellow fever, human African trypanosomiasis, dengue, Japanese encephalitis, and onchocerciasis [1]. Due to global warming, there has been increased distribution of vectors to regions that were previously inhabitable, thus increasing the risk of VBDs. This has increased a sense of urgency in the research and public health communities to develop novel effective vector control strategies to prevent a potential future vector-borne disease outbreak. One of vector control strategy is the symbiotic control, which employs the identification of suitable microbes that can spread among vector populations. Through paratransgenesis, these microbes are bioengineered to reduce or induce the fecundity and vector competence of insects [2,3,4]. Paratransgenic microbes can also be applied in development of transmission-blocking strategies, thus reducing disease transmissions while maintaining disease-free arthropods that maybe important in ecosystem food chains [5]. Identification of best candidates for paratransgenesis requires better understanding of composition, diversity, function, and role of host microbiota in vector–parasite interactions.

Many protozoan parasites that cause important human VBDs are heteroxenous i.e., during one stage of their lifecycle they live in the vertebrates and during other stages they live in the gut of bloodsucking insects. Therefore, there is a high possibility of interactions between parasite and microbiota of the host. Microbiota refers to the collective microorganisms (bacteria, archaea, viruses, fungi, and protozoans) that inhabit a host, while microbiome describes the entire genomic elements of microbiota [6]. Microbiota of important VBD vectors such as mosquitoes, sand fly, tsetse fly, triatomines and ticks have been previously well reviewed [3, 7,8,9]. Microbiota influence vector’s innate immunity, reproduction, feeding and behavior, ultimately affecting vectorial capacity of various arthropod vectors. Furthermore, microbiota is also significant in determining the pathogenicity and virulence of parasites such as Plasmodium sp., Leishmania sp., and Trypanosoma cruzi in mammalian hosts [10,11,12]. However, the mechanisms of interactions between parasite and microbiota, which play a role in the development and transmission of infections, are not fully clear.

To understand the effects and possible mechanisms of parasite-microbiota interactions on the development and transmission of malaria, we reviewed published articles on Plasmodium and microbiota interactions in both mammalian and mosquito hosts.

Vector-Borne Parasite and Microbiota Interactions

Humans and arthropods are colonized with a variety of bacteria, fungi, viruses, and protozoans that play important role in homeostatic balance of the host. Now, it has been revealed that the formation and severity of diseases are associated with microbial diversity in humans, as well as the roles of microbiota in food digestion, vitamin production and regulation of the immune system [13]. Several studies have reported the influence of gut microbiota in vector competence of mosquito, tsetse fly, and sand fly [14,15,16]. Regarding Anopheles mosquitoes, presence of some bacterial species increases the chances of Plasmodium to develop into transmissible stages while others are associated with negative growth of parasites in arthropod hosts [17,18,19].

Mosquitoes, sand flies, tsetse flies and triatomines have different biology, behavior, and ecologies, therefore, they have different core microbiota. Due to this microbial community, the interactions among microbiota, parasite, and host systems can significantly vary. However, outcomes of parasite- microbiota interactions can be summarized into three types: (i) perturbation of gut microbiota composition reduce\increases the survival of parasite and severity of disease in host; (ii) parasite infection reshapes microbial composition in the host; and (iii) microbiota and parasite influence on host’s metabolism and immune system (Table 1). These outcomes can result from competition in the use of resources, production of antimicrobial and antiparasitic metabolites, and modulation of host’s immune system by both the microbiota and parasite (Fig. 1).

Table 1 The interactions of Plasmodium and microbiota in mammalian/arthropod host
Full size table
Fig. 1
figure 1

Mechanisms involved in host microbiota and Plasmodium interactions. Microbiota and parasite can directly influence each other, independent of the host, via mechanisms that they induce individually (A). Furthermore, microbiota and parasite can indirectly influence each other via host modulated mechanisms such as immune response and metabolism (B). (Created with BioRender.com)

Full size image

Microbiota Analyzes

Accurate identification of host microbiota is the basis for investigating possible symbiont candidates for paratransgenesis and mechanisms involved in parasite-microbiota interaction. Currently culture-dependent and\or culture-independent techniques have been used in host microbiota studies [20, 21]. Although culture-dependent techniques are widely applied in microbial studies, they are limited to identification of culturable microbes. Consequently, various culture-independent methods such as gene sequencing have been developed for identification of all microorganisms. Recently, with the further development of sequencing technologies and data analysis methods, the composition and functions of the microbiota has been successfully revealed [21,22,23].

The most widely used method in microbiome analysis is marker gene (16 s rRNA) sequencing [20, 23]. Sequencing of the hypervariable regions of the 16 s rRNA gene, which is found in all bacteria and is highly conserved, enables the identification of bacterial species and taxonomic prediction [21, 24]. However, this technique can cause inaccuracies in species-level classification and only analyzes for bacterial species, ignoring other members of the community [20,21,22].

Another method, whole metagenome sequencing, examines unbiasedly at the full genomic content of the microbiota, rather than at a single gene in bacteria [22, 23], and functionally evaluates the genetic contribution of each member of the community [23, 25]. For this, shotgun metagenomic sequencing, in which long DNA molecules are randomly fragmented and then sequenced, is the most suitable strategy [23]. It allows for the identification of the full genome as well as a more accurate of species-level classification, and detection of less abundant taxa [22, 23]. It can also reveal the metabolic potential of these communities by providing information about functional genes [22, 26].

Plasmodium sp.–Microbiota Interactions

Plasmodium spp. are apicomplexan protozoan parasites that are transmitted by anopheline mosquitoes, causing malaria. WHO estimates that there are 219 million cases of malaria globally and more than 400, 000 deaths from the disease reported every year. Severity of malaria infection is dependent on many factors including Plasmodium species, age, genetic factors, nutrition status, immune status, duration of exposure, and history of previous exposure [27, 28]. In addition, recently, the role of composition of human gut microbiota in severity of malaria has been investigated. Yooseph et al. [10] performed a microbial analysis in the stool of subjects with lower and higher risk of P. falciparum infection and reported distinct microbiota profiles. After taking into account age and other potential co-features, the authors reported that higher proportion of Bifidobacterium, Streptococcus, Enterobacteriaceae, Escherichia, and Shigella in lower risk subjects compared to those at higher risk of P. falciparum infection. These results suggest possibility of modulation of gut microbiota through probiotics to supplement microbes such as Bifidobacterium to reduce severity of P. falciparum infection. Interestingly, Yilmaz et al. [29] reported that anti-α-gal antibodies produced against human gut E. coli 0.86: B7 expressed α-gal protected humans from malaria transmission. In addition, infection of α1,3GT- deficient mice with E. coli 0.86: B7 induced production of anti- α-gal antibodies that targeted Plasmodium sporozoites inoculated by Anopheles mosquitoes [29]. In the future it will be interesting to investigate the association of this bacteria’s α-gal expression with risk of P. falciparum infection in humans.

Changes in gut bacteria significantly affects severity of malaria in mammalian hosts. Mandal et al. [30] observed varying severity of P. yoelii infection in mice obtained from the same commercial vendor at different shipping times. Mice shipped in 2016 were able to clear P. yoelii infection faster than mice shipped in 2017, which had high malaria severity. Indeed, microbiota analysis of fecal samples from these two groups of mice showed a difference in bacteria abundance and composition. This result suggested that there was shift in microbiota in the microbiota of mice grown in the same environment over different time periods, thus, leading to a significant change in malaria severity. This result was validated by transferring fecal samples from both groups of mice to germ-free mice. Germ-free mice colonized with cecal contents from 2017 mice showed higher numbers of the parasite than those from 2016 mice [30]. Therefore, there are some difficulties in reproducing outcomes in experimental mouse models, even when using genetically identical mice ordered from the same production suite and vendor. In addition, it has been previously reported that mice from different vendors have different gut microbiota composition, thus showing significant varying levels of pathology upon Plasmodium infection [31]. Therefore, researchers should consider the impact of shift in gut microbiota during set up experiments and interpretation of outcomes of murine disease model systems. Particularly, researchers should include the vendor and shipping details of mice used in experiment at the time the results of publication to enable experimental reproducibility by other researchers/labs.

Mosquito first acquires its microbiota via trans-stadial transmission from the mother, and from breeding sites of its larva and pupa. Later, adult mosquitoes encounter microbes during feeding or mating. Specially, blood meal induces changes in gut microbiota community dynamics in mosquitoes [32, 33]. The shift in gut microbiota composition of the mosquito has profound effect on Plasmodium infection. For instance, introduction of P. putida, Pantoea sp., and S. marcescens resulted in strong inhibition of P. falciparum infection in An. gambiae [17]. A negative impact on numbers of P. falciparum oocyst has also been reported when infected An. gambiae mosquitoes were challenged by bacteria, such as Escherichia coli, Serratia marcescens, Pseudomonas stutzeri, Enterobacter spp., Acinetobacter septicus, Comamonas spp., and Bacillus pumilus [34]. E. coli, S. marcescens, and P. stutzeri had the highest effect on oocyst intensity. A study reported that S. marcescens increased mortality of P. vivax oocyst 13 times more than other bacteria in An. albimanus [35]. These studies highlight the significance of screening specific bacteria isolated from mosquitoes for anti-Plasmodium effects. They can be the basis of identifying bacteria candidates for vector control and transmission-blocking strategies. For instance, studies have shown that presence of Enterobacter bacterium renders mosquitoes 99% resistance to P. falciparum infection, it was then further investigated to determine specific anti-Plasmodium mechanism employed by the bacteria. The results show that bacteria inhibit the parasite infection via generation of reactive oxygen species (ROS) [36]. Other gut bacteria that have been investigated for inhibition of Plasmodium sp. infection in anopheles mosquitoes include Wolbachia (wAlb strain), Wickerhamomyces anomalus (WaF17.12 strain), paratransgenic Asaia, E. coli (351 and 444 strains), E. cloacae and Chromobacterium sp. (isolate Csp-P), [37,38,39,40,41,42,43]. Suggested mechanisms and outcomes of Plasmodium-microbiota interactions have been summarized in Table 1.

Experimental elimination of gut microbiota via antibiotic treatment have led to mosquitoes that are highly susceptible to Plasmodium spp. infection [44,45,46,47,48]. Antibiotic-treated mosquitoes are deprived of gut bacteria that play important role in antiparasitic activity in the insect. For instance, Gao et al. [48] reported that antibiotic treatment of mosquitoes inhibited the activation of Peptidoglycan Recognition Proteins LA (PGRP-LA), which is involved in antiparasitic defenses, and that gut microbiota played important role in the formation and integrity of the peritrophic membrane (PM), which inhibits Plasmodium development [48]. Song et al. [47] also showed that when the treatment of An. stephensi with antibiotics led to increased vector competence. Recolonization of the gut with Enterobacter sp. restored PM integrity and reduced susceptibility of the mosquitoes to P. berghei infection [47]. These two studies suggest that gut microbiota can also influence parasite establishment in the vector via PM formation and integrity. So, it will be interesting to research in detail, which mechanisms and specific microorganisms are involved in the interaction between gut microbiota and PM for development of transmission-blocking strategies.

Microbiota-mediated parasite control may be a consequence of microbiota influence on mosquito’s immune system and metabolism. Various transcriptomic analysis studies have shown activation of immune system in mosquito challenged by both parasite and microorganisms. When An. stephensi females were challenged with Serratia Y1 strain bacterium isolated from An. sinensis, an increase in the expression of some immunogenic genes such as C-type lectins, CLIP serine proteases, thioester-containing protein 1 (TEP1), fibrinogen immunolectin (FBN9), and leocine rich repeat protein (LRRD7), was detected [49]. These immune effectors have anti-plasmodium effect, as they rendered mosquitoes colonized with Serratia Y1 resistant to P. berghei infection. In addition, other immune effector molecules, such as anti-microbial peptide cecropin (CEC1), defensin (DEF1), and C-type lectin 4 (CTL4) have been reported to be involved in reducing Plasmodium infection in mosquitoes [50,51,52,53,54].

Although adaptive immunity has not been reported in insects there is a fair amount of specific immune response in mosquitoes. For instance, challenge of both An. stephensi and An. gambiae with Asaia bacterium showed upregulation of TEP1 in An. stephensi and not the latter [55]. Interestingly, there was a high reduction in Plasmodium replication in An. stephensi compared to An. gambiae. On the other hand, Bai et al. [49] also reported that Serratia J1 strain did not activate immune response in An. stephensi in contrast to Serratia Y1 strain. Notably, specific immune response in mosquitoes could be related to the ability of the bacteria to colonize the mosquito’s gut with dominant symbionts showing quick and consistent activation of host’s immune system [55]. Certainly, further studies are needed to confirm these hypotheses. However, it is also important to note that not all microorganisms enhance the immune response of mosquitoes to Plasmodium infection. For instance, Angleró-Rodríguez et al. [56] reported that the presence of Penicillium chrysogenum suppressed the immune response of An. gambiae rendering the mosquitoes susceptible to Plasmodium infections. According to the authors, the fungi secreted a heat-stable secondary metabolite that compromised mosquito defense mechanisms. Also, ingestion of Pe. chrysogenum resulted in upregulation of ornithine decarboxylase (ODC) gene, which limits the availability of L-arginine important for nitric oxide (NO) production [56]. Ultimately, specific microorganism-mosquito combinations need further research to identify “good” and “bad” symbionts in relation to Plasmodium infections. Identification of symbionts that enable parasite infections in mosquitoes may offer new opportunities to control transmission cycle via elimination of these symbionts.

In addition to feeding, the gut microbiota composition and diversity of mosquito are shaped by Plasmodium. Parasite infection may change the ecology of the gut via production of antimicrobials, competition for nutrients, and modification of the host physiology. As a result, some symbionts are eliminated while others gain dominance. Boissie`re et al. [18] reported a positive correlation between P. falciparum infection status and the prevalence of Enterobacteriaceae [18]. In addition, a study of dynamics of bacterial community in field-caught mosquitoes reported high abundance of Serratia and Methylobacterium in flies infected with P. falciparum compared to non-infected ones [57]. These studies suggest that the presence of certain bacteria is required for parasite development and transmission. However, within the scope of these Plasmodium-microorganisms cooperation, it remains unclear to decipher, which organism enables the existence of the other possible and the mechanisms involved.

Conclusion

Parasite-microbiota interactions are crucial in development, transmission, and severity of malaria. Inside the vector, the parasite must not only suppress the gut digestives enzymes and immune response, but also compete with the microbiota and protect themselves from antimicrobial effects of their metabolites. In addition, human microbiota plays a critical role in pathogenicity and virulence of the infecting parasite. Both microbiota and parasite can modulate the human immunity to control or exacerbate parasitic infections. Moreover, microbiota via production of antimicrobial metabolites, agglutination, modulation of nutrients and osmotic conditions, and formation of biofilms on parasite surfaces can kill or inhibit parasite growth. However, it remains unclear which exact mechanisms are directly employed by parasites to modulate microbiota composition and diversity. Further studies to determine the microbiota in vectors with high and low transmission capacity for malaria may provide new data for the development of molecules that target parasite-supporting bacteria and inhibit parasite-transmission in the vector. Moreover, investigation of microbiota in human with malaria may provide data for the development of new diagnostic, therapeutic and prevention strategies for plasmodium infections.