Heterogeneous distribution of avian malaria parasites across mosquito species: disproportionate involvement of Culex restuans in the Midwestern United States

Abstract

Background

Avian malaria parasites and related haemosporidians are diverse and widespread vector-borne parasites that circulate within complex host-vector networks. Despite their ecological importance, their diversity and circulation within mosquito communities remain poorly understood in temperate North America. The Midwestern United States, located along major North American migratory flyways, supports diverse avian habitats and mosquito assemblages, providing an ideal setting to investigate these interactions. Here, we characterized the occurrence, phylogenetic diversity, and mosquito-lineage associations of avian haemosporidians in mosquitoes.

Methods

A total of 233 pools comprising 6170 unfed female mosquitoes from seven species were collected from 38 protected natural areas in northern, central, and southern Illinois. Samples were screened for avian haemosporidian DNA by nested PCR targeting the mitochondrial cytochrome b gene. Positive samples were analyzed by multiplex PCR and sequencing to identify parasite lineages and assess potential mixed infections. Phylogenetic relationships were reconstructed, and mosquito-lineage associations were visualized using a bipartite network. Infection rates were estimated using maximum likelihood estimation (MLE) and minimum infection rate (MIR), and factors associated with infection prevalence in pooled samples were evaluated using pooled-binomial regression.

Results

Of 233 pools, 44 (18.9%) were positive for avian haemosporidians. Eleven lineages were identified, including nine Plasmodium and two Haemoproteus lineages; one Plasmodium lineage was novel. pTUMIG03 (Plasmodium unalis) was the most frequently detected lineage, whereas pSYAT05 (P. vaughani) showed the broadest mosquito distribution. Culex restuans harbored the highest lineage diversity and infection rate among the mosquito species examined. Mosquito species was a significant predictor of infection prevalence estimated from pooled samples, and Cx. restuans was most strongly associated with avian Plasmodium detection. Additionally, a deer-associated non-avian Plasmodium lineage was incidentally detected in two pools.

Conclusions

Mosquito populations in Illinois harbor a diverse assemblage of avian haemosporidians, with heterogeneous lineage distributions across mosquito taxa. Culex restuans emerged as the species most strongly associated with avian Plasmodium prevalence, suggesting an important role in local enzootic circulation. These findings expand current knowledge of avian haemosporidian diversity in North American mosquito communities and provide a basis for future studies integrating mosquito surveillance, avian host sampling, and vector competence experiments.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-026-05925-w.

Background

Mosquitoes are globally distributed blood-feeding insects, with females serving as important vectors for a wide range of pathogens, including viruses and parasites [1]. Mosquito-borne diseases are a key group of public health concern as they account for hundreds of millions of human infections annually and contribute substantially to morbidity and mortality worldwide [2]. Among these diseases, malaria caused by protozoan parasites of the genus Plasmodium is one of the most intensively studied mosquito-borne infections. This prominence is driven by the enormous global disease burden of malaria, with an estimated 212 million human cases reported annually, as well as by the wide geographic distribution of mosquito vectors [2]. However, beyond human malaria, the genus Plasmodium encompasses a broad diversity of lineages that infect non-human vertebrates, including ungulates, rodents, bats, reptiles, and birds [3]. These non-human Plasmodium lineages reflect the broader host range, phylogenetic diversity, and ecological complexity of malaria parasites.

Avian malaria parasites are among the most diverse, abundant, and widespread malaria parasites known to date [4]. These parasites, together with other avian haemosporidians (Apicomplexa: Haemosporida), have been reported from thousands of bird species across nearly all geographic regions, excluding polar areas [5]. Infections can result in a range of pathological outcomes, including anemia, anorexia, arthritis, weight loss, reduced flight performance, and mortality [5–7]. Furthermore, severe pathology may occur in non-competent hosts, as demonstrated by the accidental introduction of Plasmodium relictum to the Hawaiian Islands, where vector-mediated transmission resulted in severe population declines and the extinction of several endemic bird species [8–10]. Beyond their pathological effects, avian malaria parasites provide valuable systems for investigating ecological and co-evolutionary processes underlying vector-host-parasite interactions [11, 12]. Accordingly, examining the circulation of avian malaria parasites within vector populations offers important insight into their ecological dynamics, particularly in the context of avian conservation.

North America represents one of the world’s most extensive bird migratory networks, structured around interconnected Atlantic, Mississippi, Central, and Pacific flyways that facilitate the seasonal movement of billions of birds [13, 14]. These large-scale migratory movements connect diverse ecological regions and promote mixing among host populations, with important implications for pathogen transmission and redistribution [15, 16]. In this continentally connected system, avian malaria parasites provide a valuable model for understanding ecological and evolutionary processes relevant to emerging infectious diseases (EIDs), as they comprise a diverse multi-host assemblage of genetically-distinct lineages that include both generalist and specialist parasites with distributions structured at continental and regional scales [17–20]. Despite the ecological complexity and biogeographic connectivity of this system, knowledge of avian malaria circulation within mosquito vectors in North America remains limited, particularly in temperate regions where transmission dynamics may differ from tropical systems.

Illinois is located within the Mississippi Flyway, one of the major North American migratory corridors linking breeding and wintering grounds across the continent, and contains important stopover habitats, particularly along the Lake Michigan shoreline and major river systems [21, 22]. Its heterogeneous landscape, comprising agricultural fields, wetlands, riparian corridors, and urban habitats, supports both resident and migratory bird communities and diverse mosquito assemblages [23, 24]. This combination of high host turnover and seasonal vector activity makes Illinois a particularly suitable setting for investigating avian malaria transmission dynamics in a temperate Midwestern context. Nevertheless, avian haemosporidian research in Illinois has largely focused on infections detected in avian hosts from different parts of the state [25], whereas mosquito-based investigations have been more geographically restricted, primarily concentrated in Chicago and surrounding suburban areas [26–29]. Consequently, the potential contribution of different mosquito vector species to the maintenance and transmission of avian malaria lineages across Illinois remains only partially resolved.

In this study, we analyzed mosquito samples collected across Illinois, focusing on female mosquitoes from ornithophilic and opportunistic species without visible evidence of a recent blood meal. The objectives of the study were to (1) determine the occurrence of avian malaria parasites and related haemosporidians in mosquito species, (2) characterize the genetic diversity and phylogenetic relationships of detected parasite lineages, (3) estimate infection rates among mosquito taxa, and (4) identify mosquito species potentially associated with avian malaria circulation.

Methods

Study sites, mosquito sampling, and species identification

Mosquito specimens included in screening for avian malaria parasites and related haemosporidians were collected from 38 protected natural areas across Illinois (Fig. 1). Background land-use/land-cover data used in the map were obtained from the 2021 National Land Cover Database [30]. Sites were selected within the framework of a broader statewide mosquito surveillance program targeting zoonotic arboviruses, with the aim of capturing variation in surrounding urban development intensity and site-level habitat characteristics, particularly wetland composition and extent. In some cases, site selection targeted specific wetland types associated with particular mosquito species (e.g., semi-permanent and permanent forested wetlands, vernal woodland pools), while other sites were selected based on overall wetland abundance and diversity. For analysis, sites were grouped into three broad geographic regions (North, Central, and South) to reflect the broad latitudinal extent of Illinois and associated regional variation in landscape composition and ecological conditions (Fig. 1).

Fig. 1.

Sampling locations within 38 protected natural lands across three regions of Illinois surveyed for mosquito vectors of avian haemosporidian parasites

Each selected site was sampled in one or more years (2020–2022, and/or 2024) at approximately three-week intervals between June and September, with 87 percent of the specimens selected for avian haemosporidian parasites screening collected in July or August. During each collection period, adult mosquitoes were sampled over an approximately 24-h period using multiple trap types baited with dry ice, including CDC light traps, miniature ultraviolet (UV) light traps, as well as BG Sentinel-2 traps supplemented with additional attractant cues (UV-LED light source, BG-Lure® and/or 1-Octen-3-ol). Additional mosquito specimens were collected by aspiration from artificial resting shelters (~ 76-L capacity black plastic or fabric containers) placed in shaded locations adjacent to wetland habitats.

Trap and resting shelter samples were transported to the laboratory on dry ice, stored at − 80 °C, and maintained on a cold chain during processing. Female mosquitoes without visible evidence of a recent blood meal were selected for avian haemosporidian screening. Mosquito specimens were identified using morphological characters [31–33]. A conservative approach was applied when differentiating Culex restuans, Cx. salinarius, and Cx. pipiens complex females, with rubbed or damaged specimens lacking sufficient diagnostic characters for confident species-level identification classified as “Culex (Cx.) sp.”. Because morphological identification of biotypes within Cx. pipiens complex is not possible for field-collected females, specimens assigned to this taxon are treated here as Cx. pipiens sensu lato. For brevity, this taxon is referred to hereafter as Cx. pipiens. Adult female specimens of three primarily ornithophilic species (Cx. pipiens, Cx. restuans, Culiseta melanura) and four species with opportunistic feeding behavior (Aedes albopictus, Ae. japonicus, Cx. erraticus, Cx. salinarius) were grouped into pools of 3–50 individuals by sampling site, collection date, and species prior to DNA extraction.

DNA extraction, PCR amplification, and sequencing

Genomic nucleic acids were extracted from mosquito pools using a modified magnetic bead-based protocol. Briefly, pooled mosquitoes were homogenized in 960 µL Takara LBP lysis buffer (NucleoSpin 96 DNA RapidLyse Kit, Takara Bio, Japan) supplemented with 40 µL 1 M DTT and 20 µL liquid Proteinase K. Homogenization was performed using a TissueLyser system (Qiagen, Hilden, Germany) at 30 Hz for two 5-min cycles, with the rack orientation changed between cycles, using five stainless steel beads per tube. Following centrifugation at 6000 rpm for 10 min, lysates were incubated at 56 °C for 10 min. A total of 200 µL of the clarified supernatant was subjected to automated nucleic acid purification using the MagMAX™ Viral/Pathogen Ultra Nucleic Acid Isolation Kit (Applied Biosystems, Thermo Fisher Scientific, Waltham, MA, USA) on a KingFisher™ Flex Magnetic Particle Processor (Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer’s instructions. Binding of nucleic acids was achieved using magnetic beads and Binding Solution, followed by sequential washes with Wash Buffer and 80% ethanol. Nucleic acids were eluted in 120 µL of Elution Solution. Extracted genomic DNA (gDNA) was quantified using a Qubit 3.0 Fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) to standardize template concentrations for subsequent PCR amplification.

A fragment of the mitochondrial cytochrome b (cyt b) gene was amplified for detection of avian Plasmodium and Haemoproteus parasites using the nested PCR protocol described by Bensch et al. [34] and Hellgren et al. [35]. The first-round PCRs were set up in total volumes of 25 μl and contained 12.5 μl of Q5® Hot Start High-Fidelity 2 × Master Mix (New England Biolabs, Ipswich, MA, USA), 1.25 μl of each primer (10 μM concentration; HaemNFI and HaemNR3), 8 μl of ddH₂O, and 2 μl of gDNA template (10–30 ng). The PCR conditions included an initial denaturation at 98 °C for 2 min, followed by 20 cycles of denaturation at 98 °C for 10 s, annealing at 50 °C for 30 s, and extension at 72 °C for 30 s, with a final extension at 72 °C for 5 min. For the second round of PCR, 1 μl of the first-round PCR product was used as template with internal primers HAEMF and HAEMR2. Reaction volumes and reagent proportions were identical to those of the first PCR, except that the annealing temperature was increased to 56 °C and 35 cycles were performed. All reactions were performed in a Veriti Thermal Cycler (Applied Biosystems, Thermo Fisher Scientific, Waltham, MA, USA). Each PCR run included one positive control (gDNA from a Plasmodium sp.-infected bird) and one negative control (ddH₂O instead of template DNA). Amplification products (5 µl) were electrophoretically resolved on 1.5% agarose gels stained with SYBR™ Safe DNA Gel Stain (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) and visualized using an E-Gel™ Imager Gel Documentation System (Thermo Fisher Scientific, Waltham, MA, USA). Samples yielding unclear or no bands were re-amplified at least once to confirm results.

All PCR-positive products were purified from agarose gel for sequencing using the Monarch® Spin DNA Gel Extraction Kit (New England Biolabs, Ipswich, MA, USA). The purified amplicons were sequenced in both directions using HAEMF and HAEMR2 primers at the Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign. The primer sequences were trimmed from all reads. The forward and reverse sequences were edited and aligned with Geneious Prime software (https://www.geneious.com) to obtain a single consensus sequence. The sequence electropherograms were checked for the presence of double nucleotide peaks that might indicate potential mixed infections.

Consensus cyt b sequences were compared against the MalAvi database [36] reference dataset to assign lineage identities. For this purpose, the MalAvi cyt b FASTA dataset (last available dataset, November 2025) was downloaded and formatted as a local BLAST database within Geneious Prime. Sequence identification was performed using the BLASTn algorithm with default parameters. Lineage names were assigned based on the closest matching reference sequences following MalAvi nomenclature guidelines [36]. Sequences exhibiting one or more nucleotide differences from all previously reported cyt b lineages were considered novel and designated as a new genetic lineage. Pairwise genetic distances between the putatively novel lineage(s) and their closest reference matches were calculated using the Kimura 2-parameter (K2P) model [37] implemented in MEGA11 [38]. The sequences generated in this study were deposited in GenBank (accession numbers: PZ204997-PZ205017) and submitted to the MalAvi database. For lineages detected multiple times within the same mosquito species, a single representative sequence was deposited.

All samples that tested positive in the nested PCR were subsequently subjected to a multiplex PCR protocol as described by Ciloglu et al. [39] to detect potential mixed infections of Plasmodium spp. and Haemoproteus spp. This assay amplifies genus-specific mitochondrial DNA fragments of different sizes, allowing genus-level identification based on fragment size following agarose gel electrophoresis. Samples positive in the multiplex PCR assay were not subjected to sequencing.

Phylogenetic analysis

Phylogenetic reconstruction based on the cyt b gene region of the parasite lineages was conducted separately for the genera Plasmodium and Haemoproteus using Maximum Likelihood (ML). For Plasmodium, the phylogenetic dataset comprised the focal lineages detected in this study together with additional reference lineages retrieved from the MalAvi database. Reference selection was initially guided by morphospecies-assigned lineages showing high sequence similarity (> 95%) to the morphologically undescribed Plasmodium lineages identified in this study (N = 14), and was subsequently expanded by incorporating additional representative lineages (N = 18) from the corresponding focal clades identified in a broader preliminary genus-level phylogenetic framework reconstructed from all Plasmodium lineages available in MalAvi database (accessed November 2025) and used to guide taxon sampling for the final tree (Supplementary Fig. S1A). For Haemoproteus, reference selection was initially based on the closest-matching cyt b lineages available in MalAvi database, including those previously assigned to morphospecies (N = 9), and was subsequently expanded by incorporating additional representative lineages (N = 11) from the corresponding focal clades identified in a broader preliminary genus-level phylogeny reconstructed from all Haemoproteus lineages available in MalAvi database (Supplementary Fig. S1B), while avoiding overrepresentation of highly similar taxa. Sequences generated in this study were aligned together with the additional lineages using the Geneious Alignment algorithm implemented in Geneious Prime with default parameters. The final alignment consisted of 478 bp and was manually inspected for ambiguities.

The best-fit DNA substitution model for ML analyses was selected based on the corrected Akaike Information Criterion (AICc) using the “Find Best DNA/Protein Models” function implemented in MEGA11. The General Time Reversible model with gamma-distributed rate variation and a proportion of invariant sites (GTR + G + I) was selected as the optimal model. ML phylogenies were then reconstructed separately for Plasmodium and Haemoproteus in MEGA11 using 1,000 bootstrap replicates to assess nodal support. Taxa in the final trees were labelled using the corresponding MalAvi lineage names together with available morphospecies designations. The final ML trees were midpoint-rooted for visualization.

Mosquito-lineage association network

A bipartite mosquito-lineage association network was constructed to visualize cyt b lineage associations across mosquito species. Sequence-confirmed detections were aggregated across all study regions, and unique mosquito-lineage combinations were retained. In the network, nodes represent mosquito species and haemosporidian lineages. Edge width was scaled according to the total number of detections per mosquito-lineage pair, and node size corresponds to the node degree (number of unique connections). The network was generated and visualized in R v4.5.2 [40] using the igraph and ggraph packages.

Statistical analysis

All statistical analyses were conducted in R. Pool positivity was calculated as the proportion of PCR-positive pools among the total number of pools examined, and exact 95% confidence intervals (CI) for binomial proportions were obtained using the Clopper-Pearson method implemented in base R.

Infection rates were estimated using a maximum likelihood estimation (MLE) approach for pooled samples to account for unequal pool sizes [41]. Under the standard pooled-binomial framework, the probability of a positive pool depends on pool size and the underlying individual infection probability. Because no closed-form solution is available for unequal pool sizes, MLEs were obtained by numerical optimization in R, and 95% confidence intervals were calculated using profile likelihood [41]. This approach assumes that infections are independently distributed among mosquitoes and that each mosquito within a pool has the same probability of infection. For comparison with previous literature, minimum infection rates (MIR) were also calculated as the number of positive pools divided by the total number of mosquitoes tested × 1000 [41].

To evaluate factors associated with infection prevalence estimated from pooled mosquito samples, pooled-binomial regression models were fitted in R using the PoolTestR package [42], which implements a Generalized Linear Model (GLM) framework adapted for pooled data. The response variable was pool-level PCR status (positive/negative), and mosquito species and geographic region (North, Central, South) were included as explanatory variables. Pool size was incorporated directly into the pooled-binomial model structure, such that the probability of a positive pool was modeled as a function of both pool size and the underlying individual infection probability. Exponentiated regression coefficients [exp(β)] and 95% confidence intervals were used to summarize the direction and magnitude of associations. Overall significance of model terms was assessed using likelihood ratio tests (LRT), whereas p-values for individual regression coefficients were obtained from Wald tests. Reference categories were Cx. pipiens for mosquito species, given its established role in avian Plasmodium systems, and North for geographic region as the baseline category for regional comparisons. To further explore within-species variation in the taxon with the highest estimated infection prevalence, additional pooled-binomial models were fitted for Cx. restuans alone, using either geographic region or sampling month as explanatory variables.

Data handling and summaries were performed in R using the dplyr and tidyr packages. Figures were generated using the ggplot2 package. Statistical significance was set at p < 0.05.

Results

Mosquito species composition and detection of avian haemosporidians

A total of 233 pools containing 6170 female mosquitoes were screened for avian Plasmodium and Haemoproteus DNA. Seven mosquito species were included in the analysis (Table 1). Culex erraticus represented the largest proportion of individuals (2291 specimens in 54 pools), followed by Cx. salinarius (958 in 32 pools), Cx. pipiens (901 in 36 pools), Aedes albopictus (773 in 30 pools), Cx. restuans (603 in 38 pools), Ae. japonicus (423 in 24 pools), and Culiseta melanura (221 in 19 pools).

Table 1.

Distribution of pooled mosquito samples and avian haemosporidian detections by geographic region (North, Central, South)

Region	Mosquito Species	Individuals tested [n]	Pools tested [n]	Plasmodium spp. positive pools [n]	Haemoproteus spp. positive pools [n]	Positive pools [%]
North	Ae. japonicus	389	19	1	–	5.3
	Cx. erraticus	859	19	3	–	15.8
	Cx. pipiens	629	18	8	–	44.4
	Cx. restuans	389	18	11	–	61.1
	Cx. salinarius	488	12	1	–	8.3
	Cs. melanura	216	18	–	1	5.6
	Total	2970	104	24	1	24.0
Central	Ae. albopictus	732	25	–	–	0
	Ae. japonicus	34	5	–	–	0
	Cx. erraticus	498	15	–	–	0
	Cx. pipiens	153	11	1	–	9.1
	Cx. restuans	154	13	6	1	53.8
	Cx. salinarius	127	10	1	–	10.0
	Total	1698	79	8	1	11.4
South	Ae. albopictus	41	5	1	–	20.0
	Cx. erraticus	934	20	4	–	20.0
	Cx. pipiens	119	7	–	–	0
	Cx. restuans	60	7	5	–	71.4
	Cx. salinarius	343	10	–	–	0
	Cs. melanura	5	1	–	–	0
	Total	1502	50	10	0	20.0
Overalla		6170	233	42	2	18.9

^aTwo additional nested PCR-positive pools were excluded following sequencing confirmation of a non-avian Plasmodium lineage

Genus-level identification of avian haemosporidian-positive pools was based on sequencing confirmation. Percent positivity represents the proportion of confirmed positive pools relative to the total number of pools tested for each species and region

Overall, 46 of 233 pools were positive by nested PCR screening; however, subsequent sequencing revealed that two positive pools corresponded to a non-avian Plasmodium lineage and were therefore excluded from further analyses of avian haemosporidians. Accordingly, 44 of 233 pools (18.9%) were confirmed as positive for avian haemosporidian DNA. Confirmed positive pools were distributed across all three geographic regions (North, Central, and South), with regional positivity ranging from 11.4% to 24.0% (Table 1).

Detection frequency differed among mosquito species (Table 1). The highest proportion of positive pools was observed in Cx. restuans (23/38), followed by Cx. pipiens (9/36) and Cx. erraticus (7/54). In contrast, only single positive pools were detected in Ae. albopictus (1/30), Ae. japonicus (1/24), and Cs. melanura (1/19). At the regional level, Cx. restuans consistently exhibited the highest positivity, reaching 61.1% in the North, 53.8% in the Central region, and 71.4% in the South.

Multiplex PCR results were consistent with nested PCR screening outcomes, although complete concordance was not observed for all pools. Of the two pools, one Cx. salinarius pool from the Central region and one Cx. pipiens pool from the North region, in which nested PCR followed by sequencing identified a non-avian Plasmodium lineage, only one was positive by multiplex PCR. In addition, the two pools that yielded Haemoproteus cyt b sequences upon sequencing were classified by multiplex PCR as positive only for Haemoproteus spp., with no concurrent Plasmodium signal detected.

Lineage diversity

In total, 11 distinct avian haemosporidian cyt b lineages belonging to the genera Plasmodium (N = 9) and Haemoproteus (N = 2) were identified among the 44 sequence-confirmed positive pools (Table 2). One of the Plasmodium lineages, pCXSAL01, was recorded in the MalAvi database for the first time and represents a novel lineage described in this study. pTUMIG03 (P. unalis) was the most frequently detected lineage and occurred across all three geographic regions (North, Central, and South). This lineage was predominantly associated with Cx. restuans. pSYAT05 (P. vaughani), pPADOM11, and pWW3 were also widely distributed and were detected in multiple mosquito species and regions. Lineage-level identification was based on high-quality bidirectional consensus sequences with unambiguous chromatograms. Although electropherograms were systematically screened for double nucleotide peaks that might suggest mixed infections, no mixed-lineage patterns were observed among the 44 sequence-confirmed samples, and each sample was therefore assigned to a single haemosporidian lineage.

Table 2.

Distribution and frequency of avian haemosporidian cyt b lineages detected in mosquito pools by species and geographic region (North, Central, South)

Mosquito species	Region	Number of detections	Parasite species	Lineage name
Ae. albopictus	South	1	Plasmodium vaughani	SYAT05
Ae. japonicus	North	1	Plasmodium vaughani	SYAT05
Cx. erraticus	North	1	Plasmodium matutinum	LINN1
		1	Plasmodium vaughani	SYAT05
		1	Plasmodium unalis	TUMIG03
	South	2	Plasmodium sp.	SPMEN03
		2	Plasmodium sp.	BUSTR03
Cx. pipiens	North	3	Plasmodium matutinum	LINN1
		2	Plasmodium cathemerium	SEIAUR01
		3	Plasmodium vaughani	SYAT05
	Central	1	Plasmodium vaughani	SYAT05
Cx. restuans	North	1	Plasmodium cathemerium	SEIAUR01
		5	Plasmodium unalis	TUMIG03
		1	Plasmodium vaughani	SYAT05
		2	Plasmodium sp.	PADOM11
		2	Plasmodium sp.	WW3
	Central	4	Plasmodium unalis	TUMIG03
		1	Plasmodium sp.	PADOM11
		1	Plasmodium sp.	WW3
		1	Haemoproteus sp.	STVAR06
	South	2	Plasmodium unalis	TUMIG03
		2	Plasmodium sp.	PADOM11
		1	Plasmodium sp.	WW3
Cx. salinarius	North	1	Plasmodium unalis	TUMIG03
	Central	1	Plasmodium sp.	CXSAL01
Cs. melanura	North	1	Haemoproteus sp.	MAFUS02
Overall	–	44	–	11 lineages

Morphospecies assignments follow the MalAvi database nomenclature. “Number of detections” refers to the number of sequence-confirmed positive pools in which a given lineage was identified. The newly described lineage identified in this study is shown in bold. In the final row, 44 indicates the total number of lineage detections, and 11 lineages indicates the total number of distinct Plasmodium and Haemoproteus lineages detected in the study

Several lineages exhibited more restricted geographic distributions. pSPMEN03 and pBUSTR03 were detected exclusively in the southern region. The newly described lineage pCXSAL01 was confined to Cx. salinarius in the central region and was not observed in any other mosquito species or geographic region. Additional lineages, such as pLINN1 (P. matutinum) and pSEIAUR01 (P. cathemerium), were restricted to the northern region.

Lineage richness varied among regions, with the North harboring seven distinct lineages, whereas both the Central and South regions harbored six lineages each (Table 2). Among mosquito species, Cx. restuans harbored six distinct lineages, representing the highest lineage diversity observed in the study. This was followed by Cx. erraticus, in which five lineages were detected among seven positive pools, and Cx. pipiens, which harbored three lineages. In contrast, lineage detections in Ae. albopictus, Ae. japonicus, and Cs. melanura were each limited to a single lineage, although each of these species was represented by only one positive pool.

Interestingly, sequencing of two nested PCR-positive pools revealed an identical Plasmodium lineage that did not show an exact match to any lineage in the MalAvi database. The closest lineage in the MalAvi database (pFORCOL01) shared 93.7% nucleotide identity with this sequence. In contrast, BLAST comparisons against GenBank indicated that this sequence showed > 99% nucleotide identity to Plasmodium sequences previously reported from wild ungulate hosts (GenBank accession numbers: OR759079, OR759082, LC326033—35). These detections originated from Cx. salinarius in the Central region and Cx. pipiens in the North region. This lineage was excluded from subsequent analyses focused on avian haemosporidians.

Phylogenetic relationships

Maximum-likelihood phylogenies inferred from cyt b sequences for Plasmodium and Haemoproteus are shown in Fig. 2A and B, respectively. In the Plasmodium tree (Fig. 2A), the lineages detected in the present study were distributed across several distinct parts of the phylogeny rather than clustering within a single assemblage. The lineage pTUMIG03 grouped with pTFUS06 (P. unalis) and was positioned close to pDUMCAR09 and pTURCHI02. The lineage pSYAT05 was recovered in a separate cluster together with pTUMER13, pCXPIP34, and pTURPEL04. The lineage pSEIAUR01 clustered with other P. cathemerium lineages, including pZONCAP15 and pPADOM02, whereas pPADOM11 grouped closely with pGRW06 (P. elongatum) and pDUMCAR26.

Fig. 2.

Maximum-likelihood phylogenies of avian haemosporidian parasite lineages based on the mitochondrial cyt b gene fragment for Plasmodium (A) and Haemoproteus (B). Bootstrap support values from 1000 replicates ≥ 50 are shown above the nodes. Lineages identified in the present study are indicated by red squares. Tip labels include lineage names and their corresponding parasite species assignments. Scale bars indicate the number of substitutions per nucleotide position

Within another portion of the Plasmodium phylogeny (Fig. 2A), pLINN1 clustered with pCXPIP32, pTUPHI09, and pTUMER06, while pWW3 was recovered near pAEMO01 and pGEOTRI06. The lineage pSPMEN03 grouped with pSETPET02, whereas pBUSTR03 and the newly identified lineage pCXSAL01 were placed within the same broader cluster that also included pIXOMIN03, pCXPIP24, pDONANA02, and pSPMAG10. In addition, the P. relictum group (pGRW11, pPHCOL01, pGRW04, pLZFUS01) and pTURDUS1 (P. circumflexum) formed separate, well-defined lineages within the tree.

The Haemoproteus phylogeny (Fig. 2B) likewise recovered the lineages detected in this study in two different parts of the tree. The lineage hMAFUS02 was placed within a cluster containing hTOXCUR01, hPOECAR05, hTURAMA06, hTURMIG02, hPOEATR08, and hDUMCAR23. In contrast, hSTVAR06 was positioned in a separate subgroup together with hSTVAR07, and in proximity to hPLAMIN01, hSTAL06, hCULKIB01 (H. syrnii), and hSTRURA01. Other morphologically assigned Haemoproteus lineages included in the analysis, such as hCOLL2 (H. pallidus), hTUPHI01 (H. minutus), hPHSIB2 (H. homopalloris), hHAWF2 (H. concavocentralis), hSPMAG12 (H. larae), hFREAND01 (H. valkiunasi), and hCELEC01 (H. fuscae), provided a broader phylogenetic context for the placement of the focal lineages.

Pairwise genetic distance analysis under the K2P model further supported the distinctiveness of the newly identified lineage pCXSAL01. Although a BLASTn search against the MalAvi database indicated that pCXSAL01 shared its highest sequence identity among morphologically characterized lineages with pLZFUS01 (P. relictum), the K2P distance between these two taxa was 0.056 (94.4% similarity). In contrast, markedly higher similarities were observed between pCXSAL01 and several Plasmodium lineages not yet linked to morphologically described species, including pSPMAG10 (99.8%), pDONANA02 (99.6%), pCXPIP24 (99.4%), and pIXOMIN03 (99.2%). Among the lineages recovered in the present study, pCXSAL01 showed the highest similarity to pBUSTR03 (97.4%), followed by pSPMEN03 (96.1%). Moderate similarities were observed with pSEIAUR01 (P. cathemerium; 93.9%), pLINN1 (P. matutinum; 93.2%), and pPADOM11 (93.2%), whereas lower similarities were detected in comparisons with pTUMIG03 (P. unalis; 92.3%), pWW3 (92.3%), and pSYAT05 (P. vaughani; 92.0%). These pairwise comparisons were consistent with the phylogenetic placement of pCXSAL01 within a broader cluster of undescribed Plasmodium lineages rather than with morphologically characterized species-level lineages.

Bipartite network analysis of mosquito- avian haemosporidian associations

The bipartite network integrated 44 sequence-confirmed detections, involving seven mosquito species and 11 distinct haemosporidian lineages (Fig. 3). Culex restuans exhibited the highest degree (6), indicating associations with six distinct lineages.

Fig. 3.

Bipartite mosquito-lineage association network based on sequence-confirmed cyt b detections. Nodes represent mosquito species (blue) and haemosporidian lineages (red). Edges indicate observed mosquito-lineage associations, and edge thickness corresponds to the total number of detections per mosquito-lineage combination. Node size reflects the number of connections (degree) for each node

Among the detected parasites, the lineage pSYAT05 showed the broadest distribution, being identified in five mosquito species. In contrast, some lineages, such as pBUSTR03 and pCXSAL01, were detected in a single mosquito species. Edge thickness variation reflected differences in detection frequency, with the association between Cx. restuans and pTUMIG03 representing the most frequently detected mosquito-lineage combination in the study.

Infection rates and factors associated with infection prevalence estimated from pooled samples

The infection burden within the mosquito populations was quantified using both maximum likelihood estimation (MLE) and minimum infection rate (MIR) per 1000 mosquitoes. Based on the screening of 6170 mosquitoes in 233 pools, the overall MLE of the infection rate was 7.85 per 1000 mosquitoes (95% CI 5.78–10.42). For comparison with previous studies and historical surveillance data, the MIR was calculated as 7.13 per 1000 mosquitoes. The slightly higher MLE compared to the MIR likely reflects that MLE accounts for the possibility of multiple infected mosquitoes within a positive pool, whereas MIR assumes only one infected mosquito per positive pool.

Species-specific pooled MLE estimates demonstrated substantial heterogeneity in infection rates among mosquito species, with the highest infection rate observed in Cx. restuans (MLE: 76.11 per 1000; 95% CI 47.56–115.42) (Fig. 4A). This species-specific estimate was substantially higher than the overall infection rate, reflecting the uneven distribution of infections among mosquito taxa. In contrast, regional estimates showed comparatively limited variation (Supplementary Tables S1-S2).

Fig. 4.

Species-specific infection rate and relative prevalence of avian haemosporidians in pooled mosquito samples from Illinois. A Maximum likelihood estimate (MLE) of infection rate per 1000 mosquitoes, with 95% confidence intervals. B Relative prevalence from pooled-binomial regression, expressed as exponentiated regression coefficients [exp(β)] with 95% confidence intervals, using Culex pipiens as the reference species

To evaluate factors associated with infection prevalence estimated from pooled samples, pooled-binomial regression models were fitted. In the overall model including all mosquito species, mosquito species was strongly associated with infection prevalence (likelihood ratio test: χ2 = 82.30, df = 6, p < 0.001), whereas geographic region was not significantly associated (χ2 = 1.26, df = 2, p = 0.532) (Supplementary Table S3). Compared with Cx. pipiens (reference), Cx. restuans showed significantly higher estimated infection prevalence [exp(β) = 6.97, 95% CI 3.03–16.02, p < 0.001]. In contrast, Cx. erraticus [exp(β) = 0.24, 95% CI 0.09–0.69, p = 0.008] and Cx. salinarius [exp(β) = 0.16, 95% CI 0.03–0.77, p = 0.022] showed significantly lower estimated infection prevalence than Cx. pipiens (Fig. 4B). Lower point estimates were also observed for Ae. albopictus, Ae. japonicus, and Cs. melanura, however, these comparisons were not statistically significant (Supplementary Table S3). Given that Cx. restuans exhibited the highest estimated infection prevalence, additional pooled-binomial models were fitted to examine within-species variation. Geographic region was not significantly associated with infection prevalence in Cx. restuans (χ2 = 3.59, df = 2, p = 0.166), although the southern region showed a nominally higher point estimate compared with the northern region [exp(β) = 3.53, 95% CI 0.99–12.56, p = 0.051] (Supplementary Table S4). Regarding temporal patterns, Cx. restuans pools were distributed evenly across the primary sampling months, with 12, 11, and 12 pools collected in July, August, and September, respectively; positive pools were detected in each month. In a model restricted to these months, sampling month was not significantly associated with infection prevalence overall (χ2 = 4.57, df = 2, p = 0.102), indicating that the elevated infection burden in Cx. restuans was not restricted to a single sampling month (Supplementary Table S5).

Discussion

In this study, we investigated the occurrence and diversity of avian haemosporidian parasites in seven mosquito species from collections across Illinois. Using molecular screening of pooled mosquito samples followed by sequencing, we identified multiple Plasmodium and Haemoproteus cyt b lineages and documented their associations with several mosquito species. Overall, the detected parasite assemblage included eleven distinct lineages distributed across different mosquito taxa and geographic regions. The distribution of these lineages across mosquito species and geographic regions indicates that avian malaria parasites circulate within complex mosquito-parasite-host interaction networks in the study area. These findings highlight a substantial diversity of avian haemosporidian parasites in local mosquito communities and suggest that certain mosquito species may play a disproportionate role in their circulation within the Midwestern United States.

Avian haemosporidian parasites have been reported from a wide range of mosquito taxa worldwide, spanning multiple regions, including North America, Europe, Africa, Asia, and the Neotropics [43]. Although several mosquito genera are represented (e.g., Aedes, Anopheles, Culiseta, Coquillettidia, Mansonia, Uranotaenia) [5, 44], the majority of published detections involve mosquitoes of the genus Culex. Repeated findings of avian Plasmodium DNA have been reported in multiple Culex species across different geographic regions, most frequently in Cx. pipiens [44], but also in species such as Cx. quinquefasciatus, Cx. modestus, Cx. perexiguus, Cx. theileri, Cx. salinarius, and Cx. restuans [44]. The prominent representation of Culex mosquitoes in the literature is consistent with the predominantly ornithophilic feeding behavior observed in many species of this genus [45, 46], which increases the likelihood of contact with avian hosts that serve as reservoirs of haemosporidian parasites. Consistent with this pattern, our results revealed a heterogeneous distribution of parasite detections among the seven mosquito species examined in Illinois, with Cx. restuans emerging as the species most strongly associated with avian Plasmodium circulation in the pooled-sample dataset. The mosquito-lineage association network identified Cx. restuans as the species with the highest degree of connectivity (six lineage associations). This pattern was further supported by the pooled-binomial regression analysis, which identified mosquito species as a significant predictor of infection prevalence estimated from pooled mosquito samples. Within this framework, Cx. restuans exhibited substantially higher estimated infection prevalence than Cx. pipiens (~ sevenfold higher odds), whereas Cx. erraticus and Cx. salinarius showed markedly lower prevalence (~ fourfold and ~ sixfold lower odds, respectively). Despite the well-established role of Cx. pipiens as a principal vector of avian Plasmodium parasites worldwide [47–49], our results indicate substantial heterogeneity among sympatric Culex species in Illinois. The comparatively lower prevalence estimates for Cx. erraticus and Cx. salinarius also suggest that not all locally abundant Culex species contribute equally to avian haemosporidian circulation, although the ecological basis of these differences remains to be clarified.

Infection rate estimates further indicated substantial parasite transmission in the study area. To facilitate comparison with previous literature, we calculated both MLE and MIR values, which revealed that the overall infection burden in our study (MLE: 7.85 per 1000; MIR: 7.13 per 1000) is consistent with the upper range of pooled infection estimates reported globally [50–52]. Pooled infection estimates for avian Plasmodium in mosquitoes are highly variable and strongly influenced by sampling design and pooling strategy. In Cx. pipiens, reported MIR values generally range from very low levels, such as 0.05% in pooled mosquito surveillance in Italy [53], to approximately 3.3% in long-term field studies of Cx. pipiens populations in Japan [52]. Other multi-year mosquito surveillance programs have reported MIR values of approximately 8–16 infections per 1000 mosquitoes for Cx. pipiens in Central Europe [51]. In addition, some focal transmission systems or low-sample strata in other mosquito taxa can yield markedly higher MIR values exceeding 5%, particularly when calculated from small denominators or species with limited sample sizes [50]. Within this broader context, the markedly elevated infection rates observed in Cx. restuans (MLE: 76.11 per 1000; MIR: 38.14 per 1000) suggest that this species may play a disproportionate role in local avian malaria transmission. The substantially higher infection rate observed in Cx. restuans compared with the overall estimate likely reflects the heterogeneous distribution of infections across mosquito species, with most other species exhibiting considerably lower infection rates. In addition to the infection rate estimates, the network-based patterns also suggest that Cx. restuans may represent an important component of the local avian Plasmodium transmission system.

While both Cx. restuans and Cx. pipiens are primarily ornithophilic mosquitoes, it is possible that seasonal differences in their population dynamics may help explain the elevated infection burden observed in Cx. restuans. In many regions of the Midwestern United States, including Illinois, Cx. restuans tends to increase earlier in the season and may reach peak abundance in late spring or early summer, whereas Cx. pipiens becomes more abundant later in the summer, often peaking from late July through August [54–57]. The early seasonal activity of Cx. restuans coincides with the breeding period of many passerine birds. During this period, avian malaria transmission often intensifies because birds tend to be more infectious in late spring and early summer, driven by spring relapses in chronically infected adults [5, 58, 59] and the appearance of numerous immunologically naïve juveniles that are highly susceptible to infection [5, 10, 60]. As the season progresses, parasitemia levels in avian hosts may decline and partial immunity can develop, potentially reducing the probability of parasite acquisition by later-season mosquitoes such as Cx. pipiens [5, 60]. This seasonal synchronization between vector phenology and host infectiousness may partly explain the higher infection rates observed in Cx. restuans compared with Cx. pipiens. However, this interpretation was not formally supported by the species-specific exploratory model, in which infection prevalence in Cx. restuans did not differ significantly across July–September, despite positive pools being detected in each month.

Beyond seasonal timing, geographic and fine-scale ecological variation may also have contributed to heterogeneity in transmission. Although geographic region was not a significant predictor in the species-specific exploratory model for Cx. restuans, prevalence estimates were highest in the southern part of the study area, suggesting that local ecological variation may also contribute to this pattern. Fine-scale ecological differences, including habitat use and host contact patterns, could also play a role, although a study from the Chicago region found little difference in blood-feeding choices between Cx. pipiens and Cx. restuans [28]. Whether similar patterns occur in the more natural areas sampled in northern, central, and southern Illinois remains an open question for future research.

Although avian malaria parasites are most commonly associated with ornithophilic mosquito species, particularly within the genus Culex [43], we also included the invasive species Ae. japonicus and Ae. albopictus in our screening to explore their potential involvement in local parasite circulation. Invasive Aedes mosquitoes have expanded widely across many regions of North America and Europe, and their ecological interactions with wildlife pathogens remain incompletely understood [61, 62]. Previous studies indicate that Ae. albopictus feeds predominantly on mammals but occasionally takes blood meals from birds, suggesting that contact between this species and avian malaria parasites can occur in nature [47, 62, 63]. Laboratory experiments and field surveys further suggest that some avian Plasmodium species can infect this mosquito and have occasionally been detected in field-collected individuals, although the species generally appears less susceptible than typical Culex vectors [62, 64–66]. Similarly, other invasive Aedes species, such as Ae. japonicus, primarily feed on mammals but may also utilize avian hosts, suggesting that interactions with avian haemosporidian parasites are possible even if their epidemiological importance appears limited [62, 63]. Therefore, including these invasive species in molecular screening provides valuable information about potential host-vector-parasite encounters and helps clarify whether newly established mosquitoes may contribute to local transmission dynamics, even if they ultimately function only as incidental or secondary participants in the enzootic cycle. Consistent with previous studies [52, 66–68], our molecular screening revealed a very low level of parasite detection in the invasive Aedes species examined. Only one Plasmodium-positive pool was detected in each of Ae. albopictus and Ae. japonicus, whereas pooled infection estimates were substantially higher in sympatric populations of Cx. restuans. These findings support the view that although invasive Aedes mosquitoes may occasionally encounter avian malaria parasites through incidental blood feeding on birds, their contribution to maintaining local enzootic transmission cycles is likely limited compared with ornithophilic Culex mosquitoes, particularly Cx. restuans.

The molecular characterization of positive pools revealed a diverse assemblage of nine distinct avian Plasmodium lineages. The most frequently detected was pTUMIG03 (P. unalis), which occurred across all three geographic regions and in multiple Culex species. According to the MalAvi database (accessed November 2025), this lineage has a broad host range across several passerine families in North and South America, with a particularly strong representation in thrushes (Turdidae), including the American robin (Turdus migratorius). The high frequency of this lineage in our samples likely reflects the feeding ecology of the vectors involved. Blood meal analyses have consistently shown that American robins are primary hosts for Cx. restuans and Cx. pipiens in the Midwest [46, 69, 70]. Field observations from Illinois further support this pattern, as robins are among the most abundant passerines in the region and exhibit high seasonal availability [46, 70]. In particular, the early season dominance of American robins, when their densities are high relative to other bird species, overlaps with the peak activity of Cx. restuans and the expected spring relapse of avian malaria [70, 71]. Previous reports of pTUMIG03 in North American Culex mosquitoes further indicate that this lineage commonly circulates within regional host vector systems [72, 73]. Our findings align with this ecological pattern, as pTUMIG03 was most frequently detected in Cx. restuans pools, although it was also present in Cx. erraticus and Cx. salinarius. These results suggest that the seasonal synchronization of robin abundance, mosquito feeding preferences, and parasite transmission dynamics explains the predominance of pTUMIG03 in Illinois.

In contrast to the more concentrated association observed for pTUMIG03, the lineage pSYAT05 (P. vaughani) exhibited the broadest vector range in our study. We detected this lineage in five distinct mosquito species: Cx. restuans, Cx. pipiens, Cx. erraticus, and notably, the invasive species Ae. albopictus and Ae. japonicus. The high degree of connectivity for pSYAT05 in our mosquito-lineage network (Fig. 3) reflects its status as one of the most cosmopolitan avian malaria lineages globally. This broad vector distribution likely mirrors the widespread occurrence of pSYAT05 in common avian hosts across the region. Similar to our observations with pTUMIG03, North American records from the MalAvi database (accessed November 2025) and recent studies highlight American robins as a major reservoir for pSYAT05, with frequent detections reported in neighboring Indiana as well as Michigan, Vermont, and New York [74–77]. The abundance of robins in Illinois, combined with their role as a primary blood source for ornithophilic Culex mosquito species, may provide a consistent source of infection that allows pSYAT05 to circulate widely across various mosquito taxa.

Several additional avian Plasmodium lineages were also detected in our mosquito collections, including the newly identified lineage pCXSAL01. Most of these lineages are globally established components of avian malaria transmission systems [43, 74]. Phylogenetic reconstruction showed that these lineages span multiple well-supported clades within the Plasmodium genus. These findings indicate that the mosquito-associated Plasmodium assemblage in Illinois is both diverse and phylogenetically structured, reflecting interactions among multiple avian hosts and mosquito vectors.

Broad avian haemosporidian phylogenies based on the MalAvi database cyt b lineages are generally consistent with the placement of the focal lineages recovered in this study. Previous cyt b studies have repeatedly identified recurrent lineage groups within Plasmodium, including the P. relictum, P. cathemerium, P. matutinum, and P. vaughani complexes, whereas analyses of morphologically identified Haemoproteus have often recovered compact species-level clusters or closely related species complexes [78–82]. Accordingly, the placement of pSEIAUR01 among lineages assigned to P. cathemerium and related lineages is consistent with the close relationship reported among pPADOM02, pPADOM09, and pSEIAUR01-associated lineages in the same part of the phylogeny [82]. Likewise, the recovery of pLINN1 and pSYAT05 in separate parts of the Plasmodium tree agrees with previous cyt b phylogenies that place pLINN1 within a distinct P. matutinum group and pSYAT05 within the P. vaughani group [78, 80]. The association of pCXSAL01 with undescribed Plasmodium lineages rather than with a clearly defined morphospecies cluster is also in line with broader syntheses showing that many cyt b lineages remain unlinked to morphologically described species [78, 83]. In the Haemoproteus tree, the proximity of hCOLL2 and hTUPHI01 is similarly consistent with a previous study showing that H. minutus lineages, including hTUPHI1, are closely related to H. pallidus lineages such as hCOLL2 despite clear morphological differences between the corresponding morphospecies [84]. Minor differences in the branching order of closely related lineages relative to some published trees are not unexpected, because our final analyses were intentionally restricted to focal reference lineages and representative neighbouring clades and were based on the standard cyt b barcode fragment widely used in avian haemosporidian research [36, 79]. Although this marker is highly informative for lineage recognition, many avian haemosporidian lineages remain unlinked to morphospecies, and single-locus datasets do not always provide robust phylogenetic resolution across highly diverse haemosporidian taxa [83, 85]. Broader taxon sampling and multi-gene approaches may therefore lead to some changes in topology [85–87].

In this study, we detected two Haemoproteus lineages (hSTVAR06 and hMAFUS02) in Cx. restuans and Cs. melanura pools. However, the detection of Haemoproteus DNA in mosquitoes is not unusual, as several molecular surveys have reported similar findings, which are generally interpreted as residual parasite DNA originating from infected avian blood meals rather than evidence of successful parasite development [49, 51, 88]. Experimental evidence further supports this interpretation, showing that Haemoproteus DNA may persist in mosquito tissues for several weeks after an infected blood meal [89, 90]. This may explain why Haemoproteus DNA was detectable in our mosquito pools despite the absence of visible recent blood meals. In this context, the presence of Haemoproteus DNA in our mosquito pools most likely reflects recent blood-feeding contact between these mosquito species and birds infected with Haemoproteus parasites in the Illinois landscape. Although these detections do not indicate vector competence, they provide useful ecological information on host-vector interactions and help characterize avian haemosporidian circulation in natural systems.

The detection of a Plasmodium lineage closely related to parasites previously reported from wild ungulates was an unexpected finding in our dataset. Although our study primarily targeted avian haemosporidians, BLAST comparisons linked this sequence to the Plasmodium species complex that infects both North American white-tailed deer (Odocoileus virginianus) and South American pampas deer (Ozotoceros bezoarticus), suggesting that closely related ungulate-associated Plasmodium lineages occur in both North and South American cervids [91, 92]. In North America, deer malaria is caused by P. odocoilei, a parasite known to infect white-tailed deer and likely transmitted by mosquitoes [93, 94]. Previous studies have shown natural infection of Anopheles mosquitoes with P. odocoilei, supporting the role of mosquitoes in the transmission ecology of deer malaria [95, 96]. In our study, the ungulate-associated lineage was detected in pools of Cx. pipiens and Cx. salinarius. In this context, while Cx. pipiens is primarily ornithophilic, published blood meal studies indicate that it can occasionally feed on mammals, including white-tailed deer [69, 97]. Cx. salinarius, however, appears considerably more opportunistic and has been reported to take mammalian blood meals much more frequently, with white-tailed deer representing a substantial proportion of identified hosts in some studies [69, 97]. This feeding plasticity provides a plausible ecological explanation for the incidental detection of an ungulate-associated Plasmodium lineage in mosquito pools collected during avian malaria surveillance in Illinois, and underscores how mosquito-based molecular surveillance can occasionally reveal haemosporidian parasites outside the primary host group targeted in a given study.

Since a combination of molecular methods is often recommended to improve detection in avian haemosporidian surveys [98, 99], we used multiplex PCR alongside nested PCR to screen for mixed infections and obtain preliminary genus-level discrimination between Plasmodium and Haemoproteus. For the avian haemosporidian-positive pools, the two assays yielded similar results. However, a discrepancy was observed for the deer-associated non-avian Plasmodium lineage, as only one of the two nested PCR-positive pools was also positive by multiplex PCR. Lineage assignment in this study was based on sequencing of nested PCR products, and multiplex PCR-positive products were not sequenced separately; therefore, it remains unclear whether this signal reflected amplification of the deer-associated lineage itself or of a concurrent avian Plasmodium infection. Future studies should therefore test more directly whether this multiplex PCR protocol can amplify deer-associated Plasmodium parasites. Nevertheless, the overall concordance between multiplex PCR and nested PCR for the avian haemosporidian-positive pools provides additional support for the robustness of our molecular screening approach. At the same time, as noted previously, PCR-based approaches can be less effective for resolving mixed infections at the lineage level, particularly when multiple lineages belonging to the same parasite genus co-occur in the same sample and differ in relative abundance or amplify unequally [39]. In such cases, high-throughput sequencing approaches may provide a more complete picture of within-pool lineage diversity [100].

Conclusions

In conclusion, our study demonstrates that mosquito populations in Illinois harbor a diverse assemblage of avian haemosporidian parasites, including multiple Plasmodium and Haemoproteus lineages detected across several mosquito taxa. Among the species examined, Cx. restuans emerged as the mosquito species most strongly associated with avian Plasmodium prevalence in pooled samples, supporting the view that this species may be an important component of local enzootic transmission cycles in the Midwestern United States, at least in the types of natural habitats sampled in this study. The detection of both widespread cosmopolitan lineages and a newly identified avian Plasmodium lineage further highlights the complexity and diversity of parasite circulation within local avian host-vector systems. At the same time, the incidental detection of a deer-associated non-avian Plasmodium lineage raises the possibility that mosquitoes in the study area may also participate in the local circulation of ungulate-associated haemosporidians. Overall, these findings expand current knowledge of the diversity and lineage composition of avian malaria parasites and related haemosporidians circulating in North American mosquito communities and highlight the need for future studies integrating mosquito surveillance, avian host screening, and vector competence experiments to better resolve the ecological roles of different mosquito species in parasite transmission.

Author contributions

AC, CMS, and AJM conceived and designed the study. AJM and CC collected and identified the mosquitoes. AC, CK, AM, and JY performed the laboratory work. AC analyzed and interpreted the data and wrote the original draft of the manuscript. All authors reviewed and edited the manuscript. CMS supervised the project and secured the funding. All authors approved the final version of the manuscript.

Funding

The mosquito collections were performed as part of an agreement with the Illinois Department of Public Health. Points of view or opinions expressed in this document are those of the authors and do not necessarily represent the official position or policies of the Illinois Department of Public Health. This work was supported by the State of Illinois Used Tire Management and Emergency Public Health funds.

Availability of data and materials

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.