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PLOS Pathogens logoLink to PLOS Pathogens
. 2020 Sep 18;16(9):e1008739. doi: 10.1371/journal.ppat.1008739

Kinetics of Plasmodium midgut invasion in Anopheles mosquitoes

Gloria Volohonsky 1,*, Perrine Paul-Gilloteaux 2,3,4,¤a, Jitka Štáfková 1,¤b, Julien Soichot 1,¤c, Jean Salamero 2,3,4, Elena A Levashina 1,5,*
Editor: Kenneth D Vernick6
PMCID: PMC7526910  PMID: 32946522

Abstract

Malaria-causing Plasmodium parasites traverse the mosquito midgut cells to establish infection at the basal side of the midgut. This dynamic process is a determinant of mosquito vector competence, yet the kinetics of the parasite migration is not well understood. Here we used transgenic mosquitoes of two Anopheles species and a Plasmodium berghei fluorescence reporter line to track parasite passage through the mosquito tissues at high spatial resolution. We provide new quantitative insight into malaria parasite invasion in African and Indian Anopheles species and propose that the mosquito complement-like system contributes to the species-specific dynamics of Plasmodium invasion.

Author summary

The traversal of the mosquito midgut cells is one of the critical stages in the life cycle of malaria parasites. Motile parasite forms, called ookinetes, traverse the midgut epithelium in a dynamic process which is not fully understood.

Here, we harnessed transgenic reporters to track invasion of Plasmodium parasites in African and Indian mosquito species. We found important differences in parasite dynamics between the two Anopheles species and demonstrated a role of the mosquito complement-like system in regulation of parasite invasion of the midgut cells.

Introduction

Human malaria is a vector-borne human infectious disease caused by protozoan parasites of Plasmodium species. It is widespread in tropical and subtropical regions, including parts of the Americas, Asia, and Africa. Approximately 200 million annual cases of malaria result in half a million deaths [1]. Malaria-causing Plasmodium parasites are transmitted by Anopheles mosquitoes. Among more than 400 of known Anopheles species, only 40 are vectors of human malaria [2].

Plasmodium development in the mosquito begins with the ingestion of red blood cells infected with sexual-stage gametocytes. In the mosquito midgut, gametocytes differentiate into gametes that egress from the red blood cells and fuse to form the zygotes that develop into motile ookinetes within 16–18 h. The ookinetes penetrate the midgut epithelium 18–26 h after the infectious blood meal and transform into vegetative oocysts on the basal side of the midgut [3]. After 12–14 days, mature oocysts rupture and release thousands of sporozoites into the mosquito hemocoel. Released sporozoites invade the salivary glands, where they reside inside the salivary ducts to be injected into a new host when the infected mosquito feeds again [4].

The passage of the malaria parasite through the mosquito vector is characterized by a major population bottleneck. Previous studies revealed that mosquitoes kill the majority of invading Plasmodium parasites (reviewed by [5,6]), predominantly during the ookinete stage at the basal side of the epithelium [7].

The immune response of mosquitoes to Plasmodium parasites is multifaceted and involves multiple processes. In the midgut, reactive oxygen and nitrogen species, hemoglobin degradation products, as well as digestive enzymes and bacterial flora, all affect the rate of Plasmodium development (reviewed in [8]). As parasites traverse midgut epithelial cells, the invaded cells produce high levels of nitric oxide synthase and peroxidases, creating a toxic environment for the parasites [9]. As a result, some parasites undergo nitration which marks them for killing by the mosquito complement-like system. Furthermore, intracellular parasites can trigger apoptosis of invaded cells, causing their extrusion and clearance from the cellular layer into the midgut lumen [10]. As Plasmodium tries to evade reactive oxygen and nitrogen species inside the cells, these toxic molecules may shape the path taken by the parasite through the cellular layer. The passage of ookinetes through the cellular layer, whether between or through the midgut epithelial cells, was the subject of several studies (reviewed in [3]). These studies concluded that ookinetes always enter into the midgut epithelium intracellularly and that exit from the cellular layer can occur by either an intracellular or intercellular route, depending on extrusion of the invaded cells into the midgut lumen. Indeed, passage through the midgut cells is an obligatory step in parasite invasion as a P. falciparum line that could not enter the midgut cellular layer failed to establish infections in A. albimanus mosquitoes ([11]).

When the surviving parasites finally reach the basal lamina, they encounter soluble immune factors that circulate in the hemolymph. The complement-like protein TEP1 and leucine-rich repeat proteins APL1C and LRIM1 form a complex that mediates parasite killing [12,13]. Histological studies have shown that parasites crossing the cellular layer can be found both inside and in between midgut cells [3,14]. However, it is not yet known whether some parasites cross the cellular layer exclusively between cells, thus avoiding intracellular nitration and subsequent recognition by TEP1.

Despite accumulating evidence of molecular processes that govern the passage of motile ookinetes through mosquito tissues, the complexity and diversity of this dynamic process remains to be deciphered. Three modes of motility were reported for the invading ookinetes, namely spiraling, gliding and stationary rotation [15,16]. Spiraling and gliding movements result in active displacement of the parasite in space. In contrast, stationary rotation movement was observed for prolonged periods of time and resulted in no displacement of the ookinete. Because of the lack of markers of the entire midgut cellular layer, previous studies did not establish how distinct types of movements correlate with ookinete location in the midgut.

It has been previously demonstrated that Anopheles species differ in their vector competence [17]. In the laboratory, A. stephensi (As) and A. gambiae (Ag) can be infected with the murine parasite P. berghei (Pb) with As yielding higher parasite loads than Ag [18]. We set out to quantify by imaging in vivo migration of the RFP-expressing Pb ookinetes through the epithelial cells in these two genetically modified mosquito species that express GFP in the midgut cells. Using high-speed spinning disk microscopy and automated image analyses, we quantified parasite invasion dynamics at high spatial and temporal resolution. Our results uncovered differences in Pb invasion of closely-related mosquito species, pointing to important species-specific mechanisms that regulate mosquito–parasite interactions. Moreover, silencing of the major component of the mosquito complement-like system affected the parasite invasion dynamics, suggesting that TEP1 also regulates the early stages of the midgut invasion process.

Results and discussion

Effect of TEP1 on midgut invasion of P. berghei ookinetes

To study the passage of Pb ookinetes through the mosquito midgut, we combined multiscale imaging techniques with high-throughput data analysis and mining (Fig 1). We used transgenic mosquitoes expressing GFP under the mosquito midgut-specific G12 and Drosophila Actin5c promoters [19,20] to label mosquito midgut cells, and transgenic rodent Pb parasites expressing RFP under a constitutive promoter [21] (S1A Fig). We first made sure that expression of the reporters did not interfere with Plasmodium infection. As expected, a significant difference was observed in infection intensity between As and Ag. Regardless of the infection levels, As developed significantly higher oocysts numbers than Ag (S1B Fig). We concluded that the transgenic mosquito and Pb lines can be used for in vivo imaging.

Fig 1. Workflow and experimental settings.

Fig 1

A. stephensi (As) and A. gambiae (Ag) mosquitoes were blood-fed on P. berghei infected mice, their midguts dissected and visualized using fast confocal microscopy. Images from all experiments collected at different time points after infection were uploaded into an image database and annotated. Quantitative data was extracted from the images in the database regarding the number, position, and intensity of visualized parasites. The results of the data analysis reveal the kinetics of parasite invasion.

The transgenic mosquito lines expressed GFP in the entire midgut cell, therefore, we measured the exact position of RFP-expressing parasites relative to the cellular layer (Fig 2). To this end, we collected large series of z-stack images of live parasites inside the dissected mosquito midguts at different time points after infection (S2 Fig) and time-lapse images of selected parasites (S1 and S2 Tables). These tools enabled us to study the parasite invasion process at two time-scales: one was based on statistical analysis of parasites in three dimensional (3D) snapshots of the state of infection between 18 and 25 h post infection (hpi), the second tracked single parasites 18 to 25 hpi over a time of 20 min to 2 h. For each record, marked with a Global Unique IDentifier (guid), parasites and nuclei of the midgut cells were segmented and their positions in 3D space were calculated relative to the cellular layer at each examined time point after infection (Fig 2, S3 Fig). The position of parasites relative to the cellular layer was determined by fitting the midgut cell nuclei position by a cubic spline surface. This surface was then considered as the central position of the cellular layer (normalized z = 0). An average thickness of 5 μm above and below this surface defined the average cellular layer position.

Fig 2. Positions of the parasites relative to the midgut cells.

Fig 2

a. Schematic representation of the topology in the mosquito midgut. Motile ookinetes (red) traverse the mosquito midgut cells (green) and establish infection on the basal side under the basal lamina. b. A representative projection of a cross section of A. stephensi midgut, scale bar—50 μm. GFP-positive midgut cells are in green, RFP-positive P. berghei parasites are in red, nuclei are labeled by DAPI in blue. c. Schematic 3D representation of the same midgut as in (b), where the position of the cell layer is calculated relative to the nuclei. Positions of parasites are indicated as red dots, nuclei as blue dots. Deviation of the cell layer from a flat surface is color-coded from blue to red (blue no deviation, red—10 μm). Note the blood meal location of the majority of parasites (above the cell layer). d. Representation of nuclei (blue) and parasites (red) in the same midgut as (b) after segmentation. e. Pooled positions of the parasites from all records at all time points are shown for three layers relative to the midgut cells (blood meal, cell layer or basal lamina) for A. stephensi, A. gambiae and A. gambiae mosquitoes silenced for TEP1 (A. gambiaeTEP1KD). Each dot represents the number of parasites at a given position in a single midgut. The numbers of midguts analyzed (n) are indicated above the graph. Horizontal lines depict the mean number of parasites per position. The table below summarizes parasite distribution inside the mosquito midguts at 18–25 hpi. The percentage of ookinetes in the midguts of A. stephensi, A. gambiae and A. gambiae silenced for TEP1 (AgTEP1KD) at each location (blood meal, cell layer, and basal lamina) is shown in parentheses, n is the number of parasites at each position, total n is the total number of analyzed parasites. Statistical analyses were performed by Mann-Whitney t-test and the obtained P values are shown.

We next examined whether the dynamics of parasite invasion was similar in two Anopheles species and measured the number of parasites at each position (blood meal, cellular layer, and basal lamina) in As and Ag. Analyses of all time points did not detect significant differences in parasite localization between the two species (Fig 2E). The majority of ookinetes were detected in the blood meal (70%) and in the cellular level (20%). Only few ookinetes crossed the midgut and reached the basal side (10%). Interestingly, silencing of the major antiparasitic factor TEP1 in Ag (AgTEP1KD) significantly (p = 0.001, Mann-Whitney t-test) changed spatial distribution of the parasites with only 40% of ookinetes observed in the blood meal, 45% in the cellular layer and 15% at the basal side. The observed changes in the dynamics of Pb invasion in TEP1-depleted mosquitoes suggested that in addition to the role of TEP1 in ookinete killing at the basal side, this factor also inhibits earlier stages of ookinete midgut invasion. Previous studies reported TEP1 expression in the larval gastric caeca and adult midguts [22,23]. In line with these reports, silencing of TEP1 also affected midgut microbiota by an as yet unknown mechanism [24]. Furthermore, depletion of APL1 in As resulted in altered midgut microbiome, a change that could affect parasite invasion [25]. Our findings extend these observations to the early stages of parasite invasion and suggest that in addition to parasite killing at the basal side, TEP1 directly or indirectly inhibits Plasmodium midgut traversal.

Dynamics of ookinete midgut invasion

We next focused on P. berghei ookinete passage through the mosquito midgut cells at different time points after infection and examined the proportion of parasites at each position (blood meal, cellular layer, and basal lamina). To this end, we calculated the average proportion of parasites at each position at the early (18–20 hpi), intermediate (21–23 hpi) and late (24–25 hpi) intervals after infection (Fig 3A, S4 Fig).

Fig 3. Kinetics of P. berghei invasion of A. stephensi and A. gambiae midguts.

Fig 3

a. Positions of parasites in A. stephensi (As), A. gambiae (Ag) and in A. gambiae mosquitoes silenced for TEP1 (A. gambiaeTEP1KD) between 18 and 25 h post infection (hpi). Plots show the proportion of parasites at each position (blood meal, cell layer, and basal lamina) for three time intervals (18–20, 21–23 and 24–25 hpi). Each bar represents the average proportion of parasites in midguts that contained at least 10 parasites. Parasite positions were calculated by the distance from the cell layer: blood meal for ookinetes detected more than 5 μm above the cell layer; basal lamina for parasites observed more than 5 μm below the cell layer. Statistical analyses were performed by a Mann-Whitney t-test. The table below shows the number of midguts analyzed at each time interval for each mosquito type. b. Speed of parasites as function of the parasite position in As and Ag. Speed (μm/min) was determined by tracking the parasites position over time from the time-lapse series. Four time-lapse experiments were used: guid 1615 and guid 1628 for As and guid 1622 and guid 2109 for Ag. The table below details the number of frames (n) used for speed calculations. Statistical significance of differences in the average speed at each given position between As and Ag were examined by the Mann-Whitney t-test and P ≤ 0.0001 are designated by three asterisks.

We observed that in As mosquitoes the proportion of blood bolus-residing parasites did not change over time. The proportion of parasites within the cellular layer significantly increased from 14 to 32% during the transition between the early (18–20 hpi) and intermediate (21–23 hpi) time intervals. However, this increase did not cause accumulation of the ookinetes at the basal lamina. Instead, a significant decrease from 20 to 4% was detected in the proportion of basally located parasites between the early (18–20 hpi) and intermediate (21–23 hpi) time intervals. We were surprised to see that this decrease was temporal, as the proportion of parasites in the basal lamina significantly increased to 10% at the late time interval (24–25 hpi). A similar decrease in the proportion of basally located ookinetes was detected in Ag, where the proportion of parasites at the basal lamina declined from 12% at 18–20 hpi to 3% at 21–23 hpi, and then increased again to 14% at the late time interval.

Since the mosquito immune system targets the ookinetes at the basal side of the midgut [26], we examined whether the observed decrease in the proportion of basally located ookinetes was rescued by TEP1 knockdown. TEP1 silencing eliminated the decrease in the basally located ookinetes observed in Ag mosquitoes and at the same time increased the proportion of parasites within the cellular layer (Fig 3A). These results suggest that the first invading ookinetes are rapidly killed and lysed by the mosquito immune system. The most parsimonious explanation of the observed parasite accumulation at the basal lamina at later time points may be an asynchronous midgut invasion by Pb, where the first wave of invading ookinetes exhausts limited components of the mosquito immune system and, thereby, benefits the establishment of infection by the second wave of the parasites. This hypothesis is in line with the observation that not all parasites are recognized and killed by TEP1 at the basal lamina. We propose that early crossing parasites may serve as pioneers that locally deplete TEP1, allowing later-coming parasites to survive the immune attack, however, further experiments are necessary to validate this hypothesis.

To better understand Pb invasion dynamics, we measured ookinete motility in time-lapse experiments. The blood-filled midguts were dissected from infected mosquitoes and mounted ex vivo for imaging by spinning disk microscopy for a period of 20 to 120 min. In line with the previous work [15], we observed four distinct ookinete motility modes: (i) passive floating within the blood bolus (guid 2107, guid 1615, S1 Table), (ii) gliding within the cellular layer (guid 1628, S1 Table) (iii) spiraling in the blood meal and within the cellular layer (guid 1622, guid 1624, S2 Table) and (iv) stationary rotation without translocation within the cellular layer (guid 2115, S1 Table). Some ookinetes were observed within a midgut cell for more than one hour, suggesting that the parasites may remain intracellular for relatively long periods of time without inducing apoptosis. By measuring the parasite speed in the blood meal, cellular layer, and at the basal lamina, we found that the speed of ookinetes carried by the bolus content was the highest as compared to other locations (Fig 3B). Interestingly, the speed of the ookinetes in the blood bolus differed between As (8.2 μm/min) and Ag (3.4 μm/min) midguts, suggesting some differences in the blood bolus environment. The ookinete spiraling motility in the cellular layer was much slower in both mosquito species, namely 0.36 μm/min in As and 1.78 μm/min in Ag. The slowest stationary rotation movement of parasites was observed at the basal lamina (in As, average speed 0.28 μm/min, guid 2113, S1 Table, in Ag, average speed 0.54 μm/min, guid 1622, S2 Table). We noted that the speed of ookinetes within the cellular layer and at the basal lamina was faster in Ag than in As mosquitoes. This observation indicates important differences in the cellular organization of midguts of the closely related mosquito species.

Ookinete invasion routes

To characterize ookinete invasion routes, the intra- or extracellular location of the ookinetes at the cellular layer was examined in more detail. We developed an algorithm that classified intracellular, extracellular, and intercellular parasites based on the score of their 3D distance to the four nearest neighboring nuclei of the midgut cells. The score was calculated for each parasite in the cellular layer (Fig 4A and 4B). The parasites with the score between 0–0.45 were defined as extracellular, 0.45–0.55—as intercellular, and higher than 0.55—as intracellular. We noticed a proportion of parasites that was extracellular at all time points in both species (Fig 4C, S5 Fig). When comparing the distribution of intercellular and intracellular parasites, a higher proportion of intercellular ookinetes was observed in As (40%) than in Ag (20%) (Fig 4D, S6 Fig). These results point to intricate differences in parasite invasion routes between the two species.

Fig 4. Parasite distribution in the mosquito midgut.

Fig 4

Parasite positions within the cellular layer calculated relative to the distance of each parasites to the nuclei of surrounding midgut cells. a. Calculations of the distance of parasites from the nuclei of the nearest neighboring midgut cell. The score (s) determine whether the parasite is intercellular (0.45 ≤ s ≤ 0.55), extracellular (s < 0.45), or intracellular (s>0.55). Example images from a z stack, scale bar = 20 μm: (I) s = 0.74, the parasite (green arrow) is intracellular; (II) s = 0.45 (red arrow) the parasite is intercellular and (III) s = 0.36, the parasite is extracellular (blue arrow). b. Schematic representation of parasite (red) and nuclei (blue) positions with distances (green lines) used to calculate distances from the nuclei. c. Positions of parasites within the cell layer in A. stephensi (As), A. gambiae (Ag) and A. gambiae mosquitoes silenced for TEP1 (A. gambiaeTEP1KD). The table indicates the percentage of parasites at each position for each mosquito. The number (n) indicates the number of midguts analyzed for each mosquito genotype. d. Comparison of the proportion of intercellular parasites between As, Ag and AgTEP1KD. Each dot represents the proportion of parasites detected between cells in a single midgut. Midguts (n) with at least six parasites within the cellular layer were used for analyses. Statistically significant differences between As and Ag and between Ag and AgTEP1KD revealed by a non-parametric Mann-Whitney t-test are indicated by asterisks (*—P = 0.03; **—P = 0.003). The table details the mean proportions of parasites in each midgut and for each position for n mosquitoes.

Parasite viability within the midgut

As the transgenic P. berghei line used in this study expressed the fluorescence reporter under a constitutive promoter, we were surprised by high variability in the reporter fluorescence levels observed between individual parasites in the same midgut. We examined whether differences in fluorescence intensity correlated with parasite localization and time post infection in two mosquito species. To compare multiple experimental conditions, we normalized fluorescence intensity of each parasite based on the highest and lowest intensity of parasites in each image. For RFP expressing parasites, we found only modest overall differences in mean fluorescence intensities at different positions (basal lamina, cellular layer, blood meal) over time and between the two species (S7S9 Figs, S8 and S9 Tables). However, we also observed parasites lacking fluorescence that appeared as a black hole on the background of the midgut cells expressing GFP reporter in Ag mosquitoes (Fig 5A) that expressed GFP uniformly in all midgut cells. In contrast, irregular pattern of GFP expression in the midgut of As [19] made this analysis impossible for this species (S1 Fig). We considered the parasites that lost their fluorescence dying or dead [12,27]. On average, 10–15% of all recognized parasites had no fluorescence and were classified as dead (Fig 5B, S10 Fig). Significant differences in distribution within the cellular layer were observed for live and dead parasites (P = 0.009, Mann-Whitney test). While dead parasites were observed at the intercellular and intracellular positions, live parasites were mostly intracellular (compare Fig 5C and Fig 4D, S11 Fig, S12 Fig). This observation is suggestive of a more efficient extracellular killing of ookinetes located within the cellular layer. Interestingly, we hardly detected any dead parasites in AgTEP1KD mosquitoes, confirming the role of TEP1 in extracellular killing of parasites.

Fig 5. Quantification of dead parasites in A. gambiae.

Fig 5

a. Detection of dead parasites within the cellular layer. Due to uniform GFP expression with the midgut cells of the dmAct5C::dsx-eGFP line of A. gambiae, dead parasites that no longer express RFP could be distinguished in the midgut by their negative signal and a characteristic shape. Shown is a single z-section (scale bar = 20 μm) containing two live RFP-expressing parasites and one dead parasite, indicated by arrows. b. The proportion of dead parasites at different time points after Ag infection. Midguts (n) that contained at least 10 parasites were used for analyses. Each dot represents a single midgut. c. Distribution of dead parasites within the cellular layer. The table shows the percentage of parasites at each position at all time points. All images that contained dead parasites were analyzed. The number (n) is the number of midguts analyzed, total is the number of analyzed parasites.

Cell damage caused by parasite passage

Midgut regeneration is a natural process of epithelia renovation after a blood feeding, whether infective or not [28]. Blood meal generates a stressful environment as it contains bacteria, reactive oxygen species and digestive enzymes that may damage the midgut cells. It has been previously suggested that invaded midgut cells die after invasion and are expelled into the midgut lumen [29,30] resulting in accumulation of hundreds of extruded cells in highly infected midguts. However, we only once observed GFP-positive midgut cells in the midgut lumen. This result indicates that either dead midgut cells rapidly lose their GFP fluorescence upon expulsion, or that only few midgut cells are expelled after invasion. To resolve these conjectures, we investigated the integrity of the cell layer using high molecular weight Texas Red-conjugated dextran which is trapped inside damaged cells [31]. In these experiments, the fluorescent dextran was delivered into the midgut by blood feeding mosquitoes on mice injected intravenously with fluorescent dextran several minutes before mosquito feeding. We detected dextran-filled cells (Fig 6A), calculated their position relative to the cellular layer (Fig 6B) and measured the distance to the nearest parasite (Fig 6C). The majority (70%) of dextran-positive cells that contained a parasite in As were predominantly detected in the cellular layer. In contrast in Ag, dextran-filled cells were observed both in the cellular layer and in the midgut lumen (Fig 6B). As many as 30% of dextran-filled cells in Ag were observed in the midgut lumen. Half of these expelled cells contained a parasite (S10 Table). However, in all our experiments, only a single dextran-positive cell was detected in the midgut lumen of As mosquitoes shortly after infection. We also observed that at the later time interval (24–25 hpi) in Ag, the distance between the dextran-positive cell and the nearest parasite significantly increased as compared to the earlier time intervals (Fig 6C). Taken together, these results suggest that damaged cells with or without the parasites are readily extruded into the midgut lumen of Ag mosquitoes. It is important to note that while some dextran-positive cells contained a parasite, the majority of invaded midgut cells were dextran-negative, indicating that ookinete invasion damaged and killed only a few midgut cells. The “time bomb” theory of midgut invasion [29] postulates that the parasite passage irreparably damages and kills the invaded midgut cells. This model was further supported by studies of stained sections of As midguts infected with P. falciparum [30]. The authors reported extensive damage of invaded midgut cells and their expulsion into the lumen. The results of our study suggest that fewer midgut cells are damaged as a result of Pb invasion. While 261 parasites were detected in the cellular layer and basal lamina in Ag (Fig 2E), we observed only 50 dextran-positive cells (Fig 6C). Similar results were obtained in As mosquitoes where for 342 parasites detected in the cellular layer and basal lamina (Fig 2E), only 17 cell were dextran-positive (Fig 6C). We concluded that the majority of midgut cells in Ag and As survive Pb invasion and only few damaged cells are expelled into the midgut. The divergence between this study and the previous reports may relate to the use of different parasite and vector species or may be caused by methodological differences in midgut imaging, namely whole live midguts versus stained midgut sections. Interestingly, in both mosquito species, we never observed more than one parasite in a non-damaged midgut cell, indicating that either parasites refrain from entering already invaded cell, or that entries of multiple parasites swiftly destroy the cells. Similar to the earlier reports, we evidenced chains of connected dextran-positive cells, indicating that ookinetes can traverse multiple neighboring cells before exiting on the basal side of the cellular layer. In conclusion, our results led us to suggest that the route of ookinete invasion for the same parasite is shaped by the mosquito species-specific peculiarities of midgut tissue morphology, physiology, damage and immune responses. Future studies should examine invasion strategies of the human malaria P. falciparum parasites in diverse mosquito species.

Fig 6. Quantification of damaged cells.

Fig 6

a. Detection of dextran-positive cells in the midguts of A. stephensi (As) and A. gambiae (Ag) mosquitoes. Shown are single z-sections of GFP-expressing dissected midguts. Mosquitoes were fed on mice injected with Texas Red-conjugated dextran. Dextran-positive cells appeared red (scale bar = 50 μm). b. Positions of dextran-filled cells in the midgut layers of As and Ag. Each dot represents a single dextran-positive cell. The graph depicts positions of the dextran-positive cells within the mosquito midgut. Each layer is color coded: blood meal (blue), cell layer (green) and basal lamina (red). The number of dextran-filled cells (n) at each position is indicated. c. Distances of dextran-filled cells to the nearest parasite at different time points after infection of As and Ag. The number of dextran-positive cells analyzed (n) is shown. Statistical analysis was performed by a Mann-Whitney t-test.

Conclusions

By combining live imaging techniques with quantitative bioimage analysis workflow, we uncovered differences in ookinete invasion strategies in two related mosquito species. We found evidence that in both species, the “pioneer” parasites that first reach the basal side of the midgut were rapidly eliminated by the mosquito immune system, and that colonization of the mosquito midgut was initiated at later stages of the infection. High throughput image data analyses of two Anopheles species revealed important differences in parasite invasion routes. We showed that the average ookinete speed in the cellular layer is lower in As compared to Ag mosquitoes. Moreover, As midguts contained more intercellular parasites and displayed lower numbers of damaged parasite-harboring cells. These results indicate that faster ookinete speeds and preference for intracellular route may impede parasite survival during invasion in Ag, the mosquito species which is more resistant to P. berghei infection.

The reported here combination of live imaging and automated image analysis is highly adaptable and can be extended to functional analyses of gene knockdowns, mutations, and drug treatments. Moreover, the image data base and image analysis tools generated by this study offer a powerful tool for studying Plasmodium motility in Anopheles mosquitoes.

Materials and methods

Mosquito rearing

Transgenic Anopheles stephensi mosquitoes expressing GFP under the midgut-specific G12 promoter (pG12::EGFP) [19]) and Anopheles gambiae line expressing GFP under the Drosophila Acti5c promoter (DmActin5c::dsx-eGFP) [20]) were reared in the lab as previously described [32]. Briefly, mosquitoes were maintained in standard conditions (28°C, 75–80% humidity, 12/12 h light/dark cycle). Larvae were raised in deionized water and fed finely ground TetraMin fish food. Adults were fed on 10% sucrose ad libitum and females were blood-fed on anaesthetized mice. To obtain Ag mosquitoes that do not express TEP1, the dominant TEP1 knockdown AgTEP1KD transgenic line [33] was crossed to DmActin5c::dsx-eGFP mosquitoes. The F1 progeny had reduced TEP1 expression levels while expressing GFP in the midgut [33].

P. berghei infections

Mosquitoes were blood fed on P. berghei infected mice as previously described [34]. P. berghei pyrimethamine resistant strain (RMgm 296) constitutively expressed RFP [21]. For the visualization of damaged mosquito cells, mice were injected in the tail vein with 0.1 ml of 5% dextran (3,000 kDa Texas Red-conjugated, Invitrogen) diluted in PBS 10 min prior to blood feeding. Mosquitoes were blood-fed for 20 min on anesthetized mice and dissected between 18–24 h after blood feeding, as indicated in each experiment.

Confocal microscopy

Immediately prior to visualization, infected mosquitoes were dissected on ice in PBS buffer supplemented with 0.02% DAPI (Thermo Fisher, 4′,6-diamidino-2-phenylindole, 5 mg/mL), and with 0.2% tricaine (Sigma), 0.02% tetramisole (Sigma) to prevent midgut contraction during image acquisition. Blood-filled midguts were placed on 35 mm plastic dishes with glass bottom (Nunc, ThermoFisher). Dishes were mounted on inverted DMI6000 Leica Microscope, equipped with a Nipkow Disk confocal module (Andor Revolution), 20X objective. For time-lapse experiments, samples were visualized for up to two hours at 1 min intervals. The number of 1 μm-stacks, annotated for each image, ranged between 24 and 95 depending on tissue thickness. We noticed that As midguts were rigid and sturdy, allowing for longer live imaging. Ag midguts were more fragile and tended to move and tear during image acquisition. Live imaging data was collected from As (n = 16, S1 Table) and Ag midguts (n = 5, S2 Table). We were not able to follow parasites in mosquitoes lacking the immune protein TEP1 due to high fragility of AgTEP1KD midguts.

Image analyses

All images were uploaded to a database where they were annotated according to mosquito species and experimental conditions. Images were subjected to bulk analysis as well as manual verification. The annotated image database is accessible to JAVA programming using the Strand Avadis IManage data management software. All data (images and extracted data as text files) are available on cid.curie.fr, Project "Malaria parasite invasion in the mosquito tissues" at https://cid.curie.fr/iManage/standard/login.html. The META data is managed using OpenImadis https://strandls.github.io/openimadis/. Companion scripts are available here: https://github.com/PerrineGilloteaux/MalariaParasiteinMosquito.

The api documentation is accessible under API tab https://cid.curie.fr/iManage/api/client/. The api client jar can be found at https://cid.curie.fr/iManage/standard/downloads.html. For tutorial on access and use of database see: https://youtu.be/mznoB-y99Uo.

Companion scripts include segmentation of parasites, nuclei and quantification of intensities (corrected by background) and were performed using a set of ImageJ Plugins in Java. Analysis of the position of parasites relative to cell layer and statistics were performed with MATLAB.

The data set for a total of 2,557 parasites was collected from 110 independent experiments. More specifically, As: n = 45 midguts with 1,068 parasites; Ag: n = 34 midguts with 796 parasites; and AgTep1KD: n = 31 midguts with 693 parasites. There was no bias in the number of parasites per midgut across the time points and mosquito species (S2 Fig). As low infection levels affected quantification of parasite distribution (S3 Fig), only the images that contained at least 10 parasites were included in the analyses.

To determine the position of parasites relative to the epithelial cell layer, the position of the cell layer was modelled for each image as a 3D deformable mesh. The parameters of this mesh were obtained by minimizing the distance between the mesh and the nuclei centroids obtained after 3D segmentation of the nuclei. All data on the fitted meshes against the nuclei position are available in the database as CellLayerFitted_RecordGuid.jpeg from the user attachment panel, where blue spots are nuclei centroids and red stars represent parasite centroids. The positions of nuclei and parasites can be seen by activating the corresponding overlays.

Position of each parasite in Z was corrected according to Z of the nearest point on the mesh (the mesh Z position was created from the polynomial fit for every pixel of the image to increase the resolution of each parasite projection on the mesh). The cell layer was approximated by the average cell diameter, validated by iteration and returned to the data and the classification of parasites. Each parasite had an identifier, and its properties were stored as an attachment in the database so that any computed value can be validated visually. Parasites with corrected positions raging form -5 μm to +5 μm were considered at the cell layer position. Parasites at a distance greater than 5 μm above/below the cell layer were considered in the blood meal or basal lamina, depending on midgut orientation (metadata “reverse” in the database). For each record, a 3D projection in XZ and YZ is available for visualization of the parasite positions (result/bookmarks/xz_yz_visualization).

The position of parasites found within the cell layer was further defined relative to midgut cells. Each parasite was given a score based on a normalized ratio of the 3D Euclidean distance between the center of the parasite and the center of the nearest nuclei, and the average distance of the nuclei center between them (examples in Fig 4A and 4B). The scores were validated by visual examination and are available in the database.

For parasite kinetics tracking at short timescales, movies were first compensated for movement based on the 3D nuclei position. To this end, the 3D movies were cropped around each parasite’s X-Y trajectories by projection, and the movement of the cropped image was determined by the 3D drift compensation plugin (Fiji) using the DAPI (nuclei) channel as a reference to estimate the movement. This 3D compensation over time was then applied to the RFP channel showing the parasites. An example of a compensated movie is available at https://youtu.be/690AIgcAIj0. The compensated cropped movies were used to track the parasite over time, after visual validation that the nuclei were correctly stabilized (the original files can be found in the image database: Results/Bookmarks/Compensated movies). All data extracted from the database and used for figures can be found in S1 Data file.

Ethics statement

The animal work described in this study received agreement #E67-482-2 from the veterinary services of the region Bas-Rhin, France (Direction départementale des services vétérinaires).

Supporting information

S1 Fig. P. berghei infection intensities in the transgenic A. stephensi and A. gambiae mosquitoes expressing GFP in the midut cells.

a. GFP fluorescence in the midgut cells of A. stephensi G12::GFP line (upper) and A. gambiae dmActin5c::dsx-eGFP line (lower) 24 h after blood feeding. Enlarged are representative 20-fold magnification images showing GFP fluorescence in enterocytes (scale bar—50 μm). b. P. berghei infection intensities in A. stephensi and A. gambiae. Oocysts were counted in dissected midguts 7 days post infection. The results of two independent experiments are shown. Prevalence indicates the percentage of infected mosquito midguts in each experiment. Horizontal lines depict median number of oocysts per midgut. Statistical differences between infections of As and Ag were evaluated by a nonparametric t test, *** indicate P < 0.0005.

(TIF)

S2 Fig. Parasite numbers used for analyses in A. stephensi, A. gambiae, and A. gambiae depleted for TEP1 (A. gambiaeTEP1KD).

Each dot represents a single midgut. Similar numbers of parasites were analyzed in all mosquitoes at the indicated time points (h) after infection (hpi), where n is the number of analyzed midguts.

(TIF)

S3 Fig. Parasite distribution in A. stephensi, A. gambiae, and A. gambiae depleted for TEP1 (A. gambiaeTEP1KD) at different infection levels.

Localization of parasites in the blood meal (blue), cell layer (green) and basal lamina (red) in the midguts grouped by the infection level. Low infection (up to 15 parasites), intermediate (16–35 parasites) and high (more than 35 parasites per image) are compared. Each dot represents the proportion of parasites at a given position in a single midgut. n is the number of analyzed images.

(TIF)

S4 Fig. Temporal dynamics of parasite distribution in A. stephensi, A. gambiae, and A. gambiae depleted for TEP1 (A. gambiaeTEP1KD).

Proportion of parasites found in the blood meal (blue), cellar layer (green) and basal lamina (red) at the indicated time points (h) after infection (hpi). N is the number of analyzed images. All analyzed images contained at least ten parasites.

(TIF)

S5 Fig. Parasite distribution within the cell layer in A. stephensi, A. gambiae, and A. gambiae depleted for TEP1 (A. gambiaeTEP1KD).

Scatter plots depict the score for each parasite at indicated times after infection. Parasites are considered extracellular when the score s < 0.45, intercellular for the score 0.45 < s < 0.55 (red box) and intracellular if the score s > 0.55. n is the number of parasites analyzed at each time interval.

(TIF)

S6 Fig. Parasite positions within the cell layer in A. stephensi, A. gambiae, and A. gambiae depleted for TEP1 (A. gambiaeTEP1KD).

Scatter plots depict the proportion of parasites at each position within the cell layer: extracellular (blue), intercellular (red) and intracellular (green) at different time intervals after infection. Each dot represents a single image which contained at least 6 parasites in the cellular layer. n is the number of analyzed images.

(TIF)

S7 Fig. Intensity of parasite fluorescence versus position score in A. stephensi, A. gambiae, and A. gambiae depleted for TEP1 (A. gambiaeTEP1KD).

Each dot represents a parasite. n is the number of parasites depicted. No correlation was found between the position of the parasite and the level of fluorescence intensity when intensity is greater than zero.

(TIF)

S8 Fig. Intensity of parasite fluorescence in A. stephensi (As), A. gambiae (Ag), and A. gambiae depleted for TEP1 (AgTEP1KD).

Bar graphs depict the distribution of parasite fluorescence intensity at different positions: blood meal (blue), cell layer (green) and basal lamina (red). Parasites from all time points were pooled to calculate the average normalized intensity. Parasite intensity is normalized for each image, intensity ranges between 0.0 and 1.0, where 1.0 is the maximum intensity observed. Statistical significance of differences within each group was tested by one-way ANOVA, and differences supported by P < 0.0001 were considered significant.

(TIF)

S9 Fig

Parasite fluorescence intensity in A. stephensi (As), A. gambiae (Ag), and A. gambiae depleted for TEP1 (AgTEP1KD) at different times after infection and at different positions: blood meal (blue), cell layer (green) and basal lamina (red). Each circle represents a parasite. n is the number of analyzed parasites. Statistical analysis was performed by non-parametrical Mann Whitney test. Only images with more than 10 parasites were analyzed.

(TIF)

S10 Fig. Quantification of dead parasites in A. gambiae.

The proportion of parasites that are considered dead in each image at indicated time intervals after infection. Each dot represents one image, n is the number of analyzed images. All midguts were used for analysis.

(TIF)

S11 Fig. Distribution of dead parasites within the cell layer in A. gambiae.

Scatter plots depict the score for each parasite at indicated times after infection. Parasites are considered extracellular when the score s < 0.45, intercellular for the score 0.45 < s < 0.55 (red box) and intracellular if the score s > 0.55. n is the number of parasites analyzed at each time interval.

(TIF)

S12 Fig. Localization of dead parasites in A. gambiae within the cell layer.

Scatter plots depict the proportion of parasites at each position within the cell layer: extracellular (blue), intercellular (red) and intracellular (green) at different time intervals after infection. Each dot represents a single image, n is the number of analyzed images.

(TIF)

S1 Table. Time-lapse records of ookinete invasion of A. stephensi midguts.

(PDF)

S2 Table. Time-lapse records of ookinete invasion of A. gambiae midguts.

(PDF)

S3 Table. Kruskal-Wallis test of differences in ookinete localization between A. gambiae (Ag) and A. gambiae with silenced TEP1 (AgTEP1KD) at the indicated time points (h) post infection (hpi).

(PDF)

S4 Table. Kruskal-Wallis test of differences in parasite localization in A. stephensi (As), A. gambiae (Ag) and A. gambiae silenced for TEP1 (AgTEP1KD) between the indicated time points (h) after infection (hpi).

(PDF)

S5 Table. Kruskal-Wallis test of differences in parasite localization between A. stephensi (As), A. gambiae (Ag) and A. gambiae silenced for TEP1 (AgTEP1KD) at the indicated time points (h) after infection (hpi).

(PDF)

S6 Table. Kruskal-Wallis test of differences in parasite fluorescence intensities in A. stephensi (As), A. gambiae (Ag) and A. gambiae silenced for TEP1 (AgTEP1KD) between the indicated time points (h) after infection (hpi).

(PDF)

S7 Table. Kruskal-Wallis test of differences in parasite fluorescence intensities between A. stephensi (As), A. gambiae (Ag) and A. gambiae with silenced TEP1 (AgTEP1KD) at all time points.

(PDF)

S8 Table. Kruskal-Wallis test of differences in parasite fluorescence intensities between A. stephensi (As), A. gambiae (Ag) and A. gambiae silenced for TEP1 (AgTEP1KD) at the indicated time points (h) after infection (hpi).

(PDF)

S9 Table. Kruskal-Wallis analyses of parasite fluorescence intensities in A. stephensi (As), A. gambiae (Ag) and A. gambiae silenced for TEP1 (AgTEP1KD), in different locations: blood meal (BM), cell layer (CL) and basal lamina (BL) at the indicated time points (h) after infection (hpi).

(PDF)

S10 Table. Number of dextran-positive cells in A. gambiae and A. stephensi mosquitoes at 18–25 h post infection.

(PDF)

S11 Table. Summary of phenotypes A. stephensi (As), A. gambiae (Ag) and A. gambiae depleted for TEP1 (AgTEP1KD).

(PDF)

S1 Data. Summary of all data used to generate the Figure graphs.

(XLSX)

Acknowledgments

GV, JŠtáfková, JSoichot and EAL thank M.E. Moritz and C. Kappler for help with the mosquito colony and parasite cultures; and E. Marois for scientific discussions and support. JSalamero and PPG acknowledge the Structure fédérative de recherche santé François-Bonamy and the SERPICO team, are members of the national infrastructure "France BioImaging". Authors thank A. Volohonsky for graphic expertise.

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

EAL received funding by EC FP7 Capacities Specific Programme Research Infrastructures ‘‘INFRAVEC” under grant agreement 228421. EAL received funding from the International Associate Laboratory (LIA - Laboratoire International Associé) grant from CNRS. JeS and PPG acknowledge the Structure fédérative de recherche santé François-Bonamy and the SERPICO team, are members of the national infrastructure "France BioImaging" supported by the ANR PIA1 (ANR-10-INBS-04). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

David Sacks, Kenneth D Vernick

9 Apr 2020

Dear Prof. Levashina,

Thank you very much for submitting your manuscript "Kinetics of Plasmodium midgut invasion in Anopheles mosquitoes" for consideration at PLOS Pathogens. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. In light of the reviews (below this email), we would like to invite the resubmission of a significantly-revised version that takes into account the reviewers' comments.

The reviews are consistent in their recognition of the quality of the work. No new wet experiments are requested by reviewers, although you are free to perform them if you feel they are necessary to address reviewer concerns. However, new image, statistical and quantitative analyses are requested, as well as considerable textual changes. All of the major and minor points made by reviewers seem reasonable to us. Several critiques were shared across reviewers, and should be addressed particularly carefully. To summarize briefly, the main recurrent comment areas include:

  • Situate the work more thoroughly in the previous literature of invasion and motility.

  • Some claims are too strong and/or inadequately justified (e.g. “TEP1 inhibits midgut invasion”, line 112 “new function”, and others), and should be better supported or toned down.

  • Conversely, the apparent contrast of some of the current findings with the previous ookinete time bomb hypothesis, where most invaded cells apoptose and are extruded, was seen to be under-claimed and insufficiently interpreted, and should be treated more thoroughly.

  • There was concern and/or request for more detail about about the imaging analysis ("given the amount of movement in tissue making conclusions from the kinetics difficult"), and related comments on need to strengthen the statistical and quantitative analysis to be more clear and/or convincing.

We cannot make any decision about publication until we have seen the revised manuscript and your response to the reviewers' comments. Your revised manuscript is also likely to be sent to reviewers for further evaluation.

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to the review comments and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Please prepare and submit your revised manuscript within 60 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. Please note that revised manuscripts received after the 60-day due date may require evaluation and peer review similar to newly submitted manuscripts.

Thank you again for your submission. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Kenneth D Vernick

Associate Editor

PLOS Pathogens

David Sacks

Section Editor

PLOS Pathogens

Kasturi Haldar

Editor-in-Chief

PLOS Pathogens

orcid.org/0000-0001-5065-158X

Michael Malim

Editor-in-Chief

PLOS Pathogens

orcid.org/0000-0002-7699-2064

***********************

Reviewer's Responses to Questions

Part I - Summary

Please use this section to discuss strengths/weaknesses of study, novelty/significance, general execution and scholarship.

Reviewer #1: The manuscript by Volohonsky et al describes using new advances in microscopy to address the kinetics of Plasmodium ookinete midgut invasion, revisiting questions from ~15 years ago that were never fully addressed. Overall, the manuscript is well-executed and clearly written, while providing new insight into the some of the specific differences in invasion kinetics between different mosquito vectors. However, in its current form, I believe that there are some missed opportunities to improve the introduction and discussion, and would like additional clarification of live imaging methods given the amount of movement over time. I also don’t completely agree with the data interpretation of the TEP1 knockdown and believe that other alternatives should be explored/described in a revised manuscript in addition to other comments.

Reviewer #2: This paper uses imaging tools and an experimental setup involving the use of transgenic mosquito and malaria strains to track, in real time and in vivo, the invasion dynamics of the malaria parasite as it colonises the mosquito midgut, an essential step in completing its life cycle in the mosquito.

These tools will be valuable for other researchers in the field allowing quantitative and qualitative assessment of this process and how it is affected by experimental perturbation.

Given that invasion dynamics vary greatly, not just between parasite:vector combinations, but within vector species, understanding the nature of this process, the pathways involved and their genetic determinants is important.

I therefore think the article has interest for the field, however I think in terms of the conclusions on some of the biology of the process the data is too preliminary and this needs addressing.

Reviewer #3: This manuscript describes the traversal of malaria ookinetes across the midgut of two anopheline species and tests the effect of knocking down Tep1 on this migration. This study is by an accomplished group, the approach to the research question is novel, the amount of work is impressive, and the data significantly increase our understanding of the mechanics of midgut invasion. However, the manuscript is difficult to read, some of the methodologies are difficult to understand, and some of the conclusions appear to be overstated or not supported by rigorous statistics. In general, I have a favorable view of this manuscript, but significant revisions are necessary.

**********

Part II – Major Issues: Key Experiments Required for Acceptance

Please use this section to detail the key new experiments or modifications of existing experiments that should be absolutely required to validate study conclusions.

Generally, there should be no more than 3 such required experiments or major modifications for a "Major Revision" recommendation. If more than 3 experiments are necessary to validate the study conclusions, then you are encouraged to recommend "Reject".

Reviewer #1: - The introduction could be improved to provide more background regarding our current understanding of ookinete invasion, harnessing several papers in the early 2000s that were thoroughly summarized by Baton and Ranford-Cartwright (2005). Although this reference is cited, I think it is a missed opportunity that wasn’t further discussed to illustrate some of the current gaps in knowledge that are addressed in part through the current manuscript. At one point, it was a more prevalent debate as to whether ookinetes took an intra- or inter-cellular route of invasion.

-Similar to the above comment, I think the discussion should also be expanded to place the results of manuscript in greater context of the previous work. Additional references such as Baton and Ranford-Cartwright (2004), Baton and Ranford-Cartwright (2012), and potentially others would improve the discussion. I also think that these data challenge the “time-bomb” model and should be discussed.

-I was pleased to see some of the video links in Table S1 and S2. I didn’t watch all of the links, but am concerned by the about of movement during the time course imaging experiments. In my mind this limits the amount of analysis that can be concluded from these imaging experiments, including any kinetics experiments. How were these data examined in the presence of these movements? How can things like ookinete speed then be determined in these experiments? This seems like a pretty big hurdle in the analysis and interpretation of the data.

-Throughout the manuscript, there are several mentions that TEP1 or mosquito complement impair ookinete invasion. While I do not refute the data provided in several figures of the manuscript, I don’t believe that one can justify that this is entirely direct based on the data provided or other known aspects of previous work from your group, it’s better to leave this open-ended. As a result, I think direct language like “TEP1 inhibits midgut invasion” should be tempered. To me, it seems that these effects are probably a mixture of direct roles of recognition at the basal lamina and indirect roles in the gut given the increased invasion phenotype and TEP1 levels. Loss of TEP1 could significantly influence the composition of the midgut microbiota, where the dysbiosis could potentially help ookinete invasion. I don’t believe that this has been adequately examined. This idea is supported in part as mentioned by Dong et al (2009) for TEP1, and a recent paper by Mitri et al (2020) https://www.frontiersin.org/articles/10.3389/fmicb.2020.00306/full where loss of APL1 influenced the abundance of specific bacterial taxa in the gut. This alternative at minimum should be integrated into the revised manuscript.

-The temporal aspects of ookinete invasion success are interesting. I was intrigued by the discussion of the later timepoint (Lines 177-193) and found this very similar to the temporal aspects of TEP recognition discussed in a recent preprint by Kwon et al (https://www.biorxiv.org/content/10.1101/801480v1) where they examined the role of the BL as a physical barrier for immune recognition. The degradation patterns and repair of the BL are very similar and should be integrated in the manuscript.

Reviewer #2: Specific, substantial areas to address are the following:

Lines 188-196 Speculation on Tep1 depletion and two waves. This is to explain two timepoints but there is nothing to back it up, even Tep1 staining, measurement of Tep levels etc

Line 220 re: differences in speed of motility at lamina and in epithelia in different mosquitoes - why does it point to ‘cellular organisation’ as being the determinant of this. To me this sounds like a difference in cytoskeleton or receptor:ligand combinations is expected. But couldn’t it be some soluble, humeral factor or more general physiological trait? After all, the differences in speed observed in the blood bolus fraction are not expected to be caused by differences in cellular organisation, are they?

Line 229 -232 The parasites with the score between 0 - 0.45 were defined as extracellular, 0.45-0.55 - as intercellular, and higher than 0.55 - as intracellular.

Is this arbitrary - what is the basis for choosing these values? Particularly the intercellular…if, as suggested this is an important category it would be good to have some validation that these are really intercellular

Line 293 “while some dextran filled cells contained a parasite, most midgut cells that we observed to host a parasite were dextran-negative, indicating that ookinete invasion damaged and killed only a small proportion of midgut cells” this, to me, seems to be an important finding but I am surprised it is not given more context. This is not my field but I was under the impression that prevailing wisdom was this ‘time bomb’ theory where nearly all cells through which the parasite passes are extruded and apoptose. How do these results weigh up against that? Is there any way to quantify the number of invaded cells relative to the number of cells that get extruded? i.e. is this parasite-induced extrusion occurring in a minority or the majority of cell invasion events? What is a ‘small proportion’?

Line 310 “ “pioneer” parasites that first reach the basal side of the midgut were rapidly eliminated by the mosquito immune system, and that colonization of the mosquito midgut was initiated at later stages of the infection” again, this would be an important finding but I am not convinced there is enough proof of that in the data reported here in this manuscript.

It seems to me more like a case of back-fitting hypotheses to fit temporal or special observations. That is to say, it is a good place to start investigation of these hypotheses, facilitated by this excellent set of tools, but to accept or reject these would require further experimental corroboration.

Reviewer #3: 1. Lines 138-141: It is unclear how the investigators fitted the cellular layer relative to the nuclei, and how they devised this methodology. This is important because much of the data rely on accurately measuring the location of the midgut lumen, the cell layer, and the basal lamina. More explanation is needed.

2. Lines 143-160, fig 2e: Notably absent here is any type of statistical analysis that validates the conclusions. Were the trials paired (species and KD treatment) so that comparisons can be made? Moreover, the stated conclusion is “an additional role of TEP1 in inhibition of ookinete midgut invasion.” But the number of parasites in the luminal side of A. gambiae and A. gambiae-TEP1KD mosquitoes does not appear markedly different. Instead, the number of parasites in the cell layer and basal lamina are higher in KD mosquitoes. So, this could be interpreted as TEP1 killing the parasites during cellular traversal and not by preventing invasion. This is where a multivariable statistical analysis would pinpoint where the differences are and would allow for more strongly supported conclusions. Lines 261-263, “we hardly detected any dead parasites in AgTEP1KD mosquitoes, suggesting that TEP1 may be involved in killing parasites within the cellular layer”: the author’s words support the statement I made regarding lines 143-160, fig 2e.

3. Lines 184-187, fig 3a: The conclusion is that Tep1 eliminates the decrease in the basally located ookinetes and increases the proportion of parasites within the cellular layer. Again, this is unsupported by statistics. The only statistical test that could be used here is that in the basal lamina there is a significant bimodal effect that is not present (statistically speaking) in KD mosquitoes. But the trend is very much the same, and the reason for non-significance in KD mosquitoes appears to be the higher variance, which means the interpretation could be a type 2 error. In that sense, I do not believe the conclusions that ensue the rest of the paragraph are supported.

4. Section that begins in line 223, fig 4: It is unclear how the investigators arrived at the math used for figure 4 (and figure 4b is difficult to interpret). This is critical because the math is used to determine parasite location. Perhaps adding the axes (luminal, basal, lateral) to figure 4b plus additional text would make this clearer?

**********

Part III – Minor Issues: Editorial and Data Presentation Modifications

Please use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity.

Reviewer #1: - I am curious with the new microscopy methods and other calculations of ookinete speed provided in the manuscript, can the authors provide any information on how long it takes for ookinetes to traverse the midgut? Even an estimate of minutes vs hours would be informative.

-For the data presented in Figures 4 and 5, it is not entirely clear what is meant by “extracellular”. Is this considered the midgut lumen? Please clarify.

-Data presented in Figures S8 and S9 is more or less glossed over in the manuscript text. It is curious as to why the intensity of parasite fluorescence is lower in intensity in the TEP1 kd. Could this be an effects of “weaker parasites” surviving when they would ordinarily be killed?

-Lines 362-363: Why would TEP1 kd increase midgut fragility?

Reviewer #2: Line 76 needs citations

Line 88 given that the above statement mentions that APL1,LRIM1 and TEP1 all circulate in hemolymph it is not obvious why crossing 'between' epithelial cells to reach basal lamina would mean they 'thus avoid' TEP1

Line 119 state the promoter

Line 146 is there a difference in number of ookinetes between Ag and As though? Apparently not, looking at left and mid panels of Fig 2e. So difference between species is noteable at ookinete to oocyst transition? is this discussed.

Line 152 are these differences significant? P-values and test used?

There appears to be significantly different expression patterns of GFP (Fig S1) between Ag and As, with the latter being very heterogeneous, including large numbers of cells that do not express the marker? Can this confound/bias the results in terms of cells counted/viewed? – I note this is addressed later, somewhat. But could the presence and absence of expression represent different cell types – if so couldn’t this be problematic in drawing general conclusions across the whole midgut epithelium, for As at least?

Line 202 “guid” needs explanation

Line 258 states “Differences in distribution were observed for live and dead parasites within the cellular layer” but the legend for Figure S7 states “No correlation was found between the position of the parasite and the level of fluorescence intensity.” When indeed the figure does seem to back up the main text in that it shows an enrichment of black parasite foci that correlate with the midgut epithelial stack. Connecting this point to the point above about surety of calling ‘intercellular’ parasites, I find it curious that there is not difference between the %dead in the intercellular and intracellular classes, indeed they have identical values. Perhaps some of this is confusion is me getting mixed up with ‘position score’ (relating to inter, intra, extra etc.) and height in stack i.e. basal lamina, epithelial or bolus. Either way, if I’m confused so will some readers be, so I would suggest trying to make this a bit clearer.

Fig 4d is a graph and table of identical I presume. I would leave the graph and label y-axis as “%intercellular parasites”

Line 259 “More dead parasites were found to be located extracellular or intercellular (compare Fig 5c and Fig 4d)” it seems strange to make reader compare values in two different figures to reach a conclusion but if I’ve followed correctly, for all parasites in Ag there is a 27:56.7 ratio of inter:intra whereas for ‘dead only’ it is 1:1 (45.5:45.5). Presumably this is significant?

I am confused about the sample sizes in Fig 5. In panel b there are 31 mosquitoes looked at. Panel c says 41, which I presume refers to the number of mosquitoes. Were they separate experiments?

Line 287 should this be “one dextran filled cell …with a parasite” or is this one of 20 cells found “in” the midgut had dextran? I must say it’s not clear to me how one efficiently recovers or visualises single cells in a cavity as voluminous as the midgut lumen without a large error.

Line 298 “indicating that parasites refrain from entering an invaded cell.” Are there alternative explanations for this observation other than they are prevented from entering - what if two parasites entering the cell ‘burst’ it, or triggered a very rapid apoptosis that meant they were just not observed?

Reviewer #3: 1. Lines 110-112: Was a “new function” of Tep1 really discovered, or did we simply learn more about how Tep1 functions? What is presented seem like a more accurate pinpointing of how Tep1 functions.

2. One of the major conclusions of the study is that “the route of ookinete invasion for the same parasite is species-specific and shaped by…”. This could be true, but wouldn’t it be more likely that the difference in invasion efficiency between the two species leads to the phenotypes observed here? Plasmodium berghei does not share an evolutionary history with either A. gambiae or A. stephensi, so it seems unlikely that different invasion strategies evolved.

3. Is it necessary to abbreviate A. gambiae to Ag, A. stephensi to As and P. berghei to Pb in an online only, open access journal? It makes for a clumsy read.

4. Whenever possible it is best to make definitive statements instead of ambiguous ones. For example, lines 101-103 convey the different rates of development without stating which rate is faster. The answer is known, so why not tell the reader? Another example in the same paragraph: line 108 speaks of “unexpected differences” without providing a clue as to what they are.

5. Line 35: would it be best to use “shaped in part” instead of “shaped”? Undoubtedly there are factors that play a larger role than Tep1.

6. The supplementary figures are presented out of order, making it a more cumbersome read.

**********

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Decision Letter 1

David Sacks, Kenneth D Vernick

23 Jun 2020

Dear Prof. Levashina,

We are pleased to inform you that your manuscript 'Kinetics of Plasmodium midgut invasion in Anopheles mosquitoes' has been provisionally accepted for publication in PLOS Pathogens.

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Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Pathogens.

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David Sacks

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Kasturi Haldar

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***********************************************************

Please note that new text added in response to reviewer comments generated a small error that should be corrected. At line 167, it is stated that "Furthermore, depletion of another mosquito complement-like factor APL1 resulted in altered midgut microbiome...". APL1 is a leucine-rich repeat protein, not complement-like.

Reviewer Comments (if any, and for reference):

Acceptance letter

David Sacks, Kenneth D Vernick

7 Aug 2020

Dear Prof. Levashina,

We are delighted to inform you that your manuscript, "Kinetics of Plasmodium midgut invasion in Anopheles mosquitoes," has been formally accepted for publication in PLOS Pathogens.

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. P. berghei infection intensities in the transgenic A. stephensi and A. gambiae mosquitoes expressing GFP in the midut cells.

    a. GFP fluorescence in the midgut cells of A. stephensi G12::GFP line (upper) and A. gambiae dmActin5c::dsx-eGFP line (lower) 24 h after blood feeding. Enlarged are representative 20-fold magnification images showing GFP fluorescence in enterocytes (scale bar—50 μm). b. P. berghei infection intensities in A. stephensi and A. gambiae. Oocysts were counted in dissected midguts 7 days post infection. The results of two independent experiments are shown. Prevalence indicates the percentage of infected mosquito midguts in each experiment. Horizontal lines depict median number of oocysts per midgut. Statistical differences between infections of As and Ag were evaluated by a nonparametric t test, *** indicate P < 0.0005.

    (TIF)

    S2 Fig. Parasite numbers used for analyses in A. stephensi, A. gambiae, and A. gambiae depleted for TEP1 (A. gambiaeTEP1KD).

    Each dot represents a single midgut. Similar numbers of parasites were analyzed in all mosquitoes at the indicated time points (h) after infection (hpi), where n is the number of analyzed midguts.

    (TIF)

    S3 Fig. Parasite distribution in A. stephensi, A. gambiae, and A. gambiae depleted for TEP1 (A. gambiaeTEP1KD) at different infection levels.

    Localization of parasites in the blood meal (blue), cell layer (green) and basal lamina (red) in the midguts grouped by the infection level. Low infection (up to 15 parasites), intermediate (16–35 parasites) and high (more than 35 parasites per image) are compared. Each dot represents the proportion of parasites at a given position in a single midgut. n is the number of analyzed images.

    (TIF)

    S4 Fig. Temporal dynamics of parasite distribution in A. stephensi, A. gambiae, and A. gambiae depleted for TEP1 (A. gambiaeTEP1KD).

    Proportion of parasites found in the blood meal (blue), cellar layer (green) and basal lamina (red) at the indicated time points (h) after infection (hpi). N is the number of analyzed images. All analyzed images contained at least ten parasites.

    (TIF)

    S5 Fig. Parasite distribution within the cell layer in A. stephensi, A. gambiae, and A. gambiae depleted for TEP1 (A. gambiaeTEP1KD).

    Scatter plots depict the score for each parasite at indicated times after infection. Parasites are considered extracellular when the score s < 0.45, intercellular for the score 0.45 < s < 0.55 (red box) and intracellular if the score s > 0.55. n is the number of parasites analyzed at each time interval.

    (TIF)

    S6 Fig. Parasite positions within the cell layer in A. stephensi, A. gambiae, and A. gambiae depleted for TEP1 (A. gambiaeTEP1KD).

    Scatter plots depict the proportion of parasites at each position within the cell layer: extracellular (blue), intercellular (red) and intracellular (green) at different time intervals after infection. Each dot represents a single image which contained at least 6 parasites in the cellular layer. n is the number of analyzed images.

    (TIF)

    S7 Fig. Intensity of parasite fluorescence versus position score in A. stephensi, A. gambiae, and A. gambiae depleted for TEP1 (A. gambiaeTEP1KD).

    Each dot represents a parasite. n is the number of parasites depicted. No correlation was found between the position of the parasite and the level of fluorescence intensity when intensity is greater than zero.

    (TIF)

    S8 Fig. Intensity of parasite fluorescence in A. stephensi (As), A. gambiae (Ag), and A. gambiae depleted for TEP1 (AgTEP1KD).

    Bar graphs depict the distribution of parasite fluorescence intensity at different positions: blood meal (blue), cell layer (green) and basal lamina (red). Parasites from all time points were pooled to calculate the average normalized intensity. Parasite intensity is normalized for each image, intensity ranges between 0.0 and 1.0, where 1.0 is the maximum intensity observed. Statistical significance of differences within each group was tested by one-way ANOVA, and differences supported by P < 0.0001 were considered significant.

    (TIF)

    S9 Fig

    Parasite fluorescence intensity in A. stephensi (As), A. gambiae (Ag), and A. gambiae depleted for TEP1 (AgTEP1KD) at different times after infection and at different positions: blood meal (blue), cell layer (green) and basal lamina (red). Each circle represents a parasite. n is the number of analyzed parasites. Statistical analysis was performed by non-parametrical Mann Whitney test. Only images with more than 10 parasites were analyzed.

    (TIF)

    S10 Fig. Quantification of dead parasites in A. gambiae.

    The proportion of parasites that are considered dead in each image at indicated time intervals after infection. Each dot represents one image, n is the number of analyzed images. All midguts were used for analysis.

    (TIF)

    S11 Fig. Distribution of dead parasites within the cell layer in A. gambiae.

    Scatter plots depict the score for each parasite at indicated times after infection. Parasites are considered extracellular when the score s < 0.45, intercellular for the score 0.45 < s < 0.55 (red box) and intracellular if the score s > 0.55. n is the number of parasites analyzed at each time interval.

    (TIF)

    S12 Fig. Localization of dead parasites in A. gambiae within the cell layer.

    Scatter plots depict the proportion of parasites at each position within the cell layer: extracellular (blue), intercellular (red) and intracellular (green) at different time intervals after infection. Each dot represents a single image, n is the number of analyzed images.

    (TIF)

    S1 Table. Time-lapse records of ookinete invasion of A. stephensi midguts.

    (PDF)

    S2 Table. Time-lapse records of ookinete invasion of A. gambiae midguts.

    (PDF)

    S3 Table. Kruskal-Wallis test of differences in ookinete localization between A. gambiae (Ag) and A. gambiae with silenced TEP1 (AgTEP1KD) at the indicated time points (h) post infection (hpi).

    (PDF)

    S4 Table. Kruskal-Wallis test of differences in parasite localization in A. stephensi (As), A. gambiae (Ag) and A. gambiae silenced for TEP1 (AgTEP1KD) between the indicated time points (h) after infection (hpi).

    (PDF)

    S5 Table. Kruskal-Wallis test of differences in parasite localization between A. stephensi (As), A. gambiae (Ag) and A. gambiae silenced for TEP1 (AgTEP1KD) at the indicated time points (h) after infection (hpi).

    (PDF)

    S6 Table. Kruskal-Wallis test of differences in parasite fluorescence intensities in A. stephensi (As), A. gambiae (Ag) and A. gambiae silenced for TEP1 (AgTEP1KD) between the indicated time points (h) after infection (hpi).

    (PDF)

    S7 Table. Kruskal-Wallis test of differences in parasite fluorescence intensities between A. stephensi (As), A. gambiae (Ag) and A. gambiae with silenced TEP1 (AgTEP1KD) at all time points.

    (PDF)

    S8 Table. Kruskal-Wallis test of differences in parasite fluorescence intensities between A. stephensi (As), A. gambiae (Ag) and A. gambiae silenced for TEP1 (AgTEP1KD) at the indicated time points (h) after infection (hpi).

    (PDF)

    S9 Table. Kruskal-Wallis analyses of parasite fluorescence intensities in A. stephensi (As), A. gambiae (Ag) and A. gambiae silenced for TEP1 (AgTEP1KD), in different locations: blood meal (BM), cell layer (CL) and basal lamina (BL) at the indicated time points (h) after infection (hpi).

    (PDF)

    S10 Table. Number of dextran-positive cells in A. gambiae and A. stephensi mosquitoes at 18–25 h post infection.

    (PDF)

    S11 Table. Summary of phenotypes A. stephensi (As), A. gambiae (Ag) and A. gambiae depleted for TEP1 (AgTEP1KD).

    (PDF)

    S1 Data. Summary of all data used to generate the Figure graphs.

    (XLSX)

    Attachment

    Submitted filename: Rebuttal letter.docx

    Data Availability Statement

    All relevant data are within the manuscript and its Supporting Information files.


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