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Published in final edited form as: Vet Parasitol. 2015 Feb 16;209(0):93–100. doi: 10.1016/j.vetpar.2015.02.003

Fine-scale temperature fluctuation and modulation of Dirofilaria immitis larval development in Aedes aegypti

Nicholas Ledesma a,*, Laura Harrington b
PMCID: PMC4390526  NIHMSID: NIHMS669441  PMID: 25747489

Abstract

We evaluated degree-day predictions of Dirofilaria immitis development (HDU) under constant and fluctuating temperature treatments of equal average daily temperature. Aedes aegypti mosquitoes were infected with D. immitis microfilariae and parasite development was recorded at set time points in dissected mosquitoes. Time to L3 development in Malpighian tubules and detection in mosquito heads was shorter for larvae experiencing a daily regime of 19±9°C than larvae at constant 19°C; larval development rate in Malpighian tubules was slower in fluctuating regimes maintained above the 14°C developmental threshold than larvae under constant temperatures. We showed that hourly temperature modeling more accurately predicted D. immitis development to infective L3 stage. Development time differed between fluctuating and constant temperature treatments spanning the 14°C development threshold, implicating a physiological basis for these discrepancies. We conclude that average daily temperature models underestimate L3 development—and consequently dog heartworm transmission risk—at colder temperatures, and spatio-temporal models of D. immitis transmission risk should use hourly temperature data when analyzing high daily temperature ranges spanning 14°C.

Keywords: heartworm development unit, Dirofilaria immitis, extrinsic incubation period, daily temperature range, degree-day, Aedes aegypti

INTRODUCTION

Temperature and extrinsic incubation period (EIP) are basic parameters in predictive models of vector-borne disease transmission risk and seasonality. Dirofilaria immitis EIP is defined by heartworm development units (HDUs), which are a degree-day calculation that factors average daily temperature above the D. immitis minimum temperature for development, 14°C:

∑Averagedailytemp-14°C=AccumulatedHDUs

Previous studies have shown that mosquito-ingested microfilariae mature to infective stage L3 larvae and migrate to the mosquito head and labium once 130 HDUs have been accumulated (Fortin and Slocombe 1981). This formula has been the basis for defining risk across geographic regions and peak periods of dog heartworm transmission in the United States and other countries (Knight and Lok 1998, Vezzani and Carbajo 2006, Medlock et al. 2007, Genchi et al. 2009, Cuervo and Fantozzi 2013).

Although HDU predictions have proven useful on a broad scale, investigations of other vector-borne disease systems suggest that the relationship between temperature fluctuation and pathogen incubation period is not linear (Cornel et al. 1993, Reisen et al. 1993, Arthurs et al. 2003, Paaijmans et al. 2009, 2010). The majority of supporting literature for this phenomenon focuses on extrinsic incubation dynamics of arboviruses and malaria, but Arthurs and others (2003) described altered development of the nematode Thripinema nicklewoodi under fluctuating temperature. When this parasite was held in its insect host at a fluctuating temperature regime with a baseline average temperature of 28.75°C, its development rate was similar to parasites held at a constant 20°C (Arthurs et al. 2003). Temperature fluctuation has been shown to modulate extrinsic incubation period and R0 of malaria as discussed in depth by Paaijmans et al. (2010). The authors implicate non-linear effects of temperature fluctuation for discrepancies between malaria transmission predictions and actual caseload in areas that do not meet degree-day developmental thresholds. Interactions between fluctuation amplitude and baseline average temperature produced non-linear changes in EIP and mosquito survival and, therefore, mosquito vectorial capacity for malaria (Paaijmans et al. 2009).

Using daily average to approximate temperature experienced by vectors and vector-borne pathogens ignores biological effects of fluctuating temperature as well as mathematical discrepancies apparent in prediction models scaled to finer resolutions. Assuming an environment of constant temperature is also unrealistic given that mosquitoes move between spatiotemporal microhabitats with distinct environmental conditions (Meyer et al. 1990). Microhabitats vary with the ecological niches of each mosquito species, and studies monitoring microhabitat conditions compared to average ambient conditions concluded that a mosquito can experience a “composite thermal environment” resulting in a different EIP than that calculated by average ambient daily temperature (Meyer et al. 1990).

Ours is the first study to examine the effects of daily temperature fluctuation on development and transmission of D. immitis, and, generally, there has been little investigation of accepted HDU model assumptions. Our hypothesis was that hourly calculations of HDU accumulation are more accurate predictors of D. immitis EIP, and can be expressed as follows:

∑Hourlytempobservation-14°C=AccumulatedHDUhrs

130 HDUs are equivalent to 3120 HDUhrs, and, at this fine scale, we hypothesized that fluctuations across threshold temperature would alter predictions of L3 development between hourly and daily calculations. This was predicted to result in infective stage D. immitis detection in mosquito heads/proboscises earlier in the threshold-spanning treatment as compared to a constant above-threshold temperature treatment. Infected mosquitoes were dissected to compare D. immitis development and differences in degree-day model predictions and transmission potential between treatments were analyzed.

Materials and Methods

Mosquito rearing

Liverpool strain Aedes aegypti were acquired as eggs from Cheri-Hill Kennel & Supply Inc. (Stanwood, MI, USA). Mosquitoes were maintained in an environmental chamber set at a temperature of 29°C, 90% RH and 10 h L: 10 h D photo-regime with 2 h periods of dusk and dawn. Adults were held in a 30-cm3 screened cage and provided with 10% sucrose ad lib.

Handling of microfilaremic blood

Microfilaremic and non-infected blood was supplied by Dr. Byron Blagburn (Auburn University, AL) and Cheri-Hill Kennel & Supply Inc. (Stanwood, MI) in overnight shipments of heparinized collection tubes. Microfilaremic blood was pooled together and used no later than 7 hrs after receiving shipments.

Determining microfilarial density

Blood microfilarial density was determined immediately prior to each infection. Microfilariae in 3 × 20 μl aliquots of blood were counted from the pooled blood sample. Counting was performed using a modified method based on Theis et al. (2000). Briefly, each 20 μl aliquot of infected blood was diluted in 40 μl of water and held at room temperature for 20 mins. Diluted aliquots of blood were each spread evenly over three microscope slides for scanning under a phase contrast microscope at 100X. Only moving microfilariae were counted. After determining the density of live microfilariae, heartworm-negative dog blood was added to attain the desired microfilarial density of 3500 microfilariae/ml.

Infecting mosquitoes

Cups holding an estimated 200 pupae were placed inside 7 L plastic containers secured with mesh until adult eclosion. Moistened sugar cubes were provided on tissue over the mesh lid. Sugar and water were removed 15–20 h before offering microfilaremic blood. On the day of infection, 7 L plastic containers of 3- to 5-day-old mosquitoes were chilled at 4°C for 12 min for immobilization. Females (100–200) were transferred into 7 L plastic containers; males were discarded. Microfilaremic blood was offered according to the methods of Lai et al. (2000) with the following modifications. Known densities of microfilariae in heparinized dog blood were added to glass feeders secured at the base with washed hog intestine (Syracuse Casing Company, Syracuse, NY, USA). Blood was warmed in the feeder apparatus using a circulating water bath set at 37°C (Harrington et al. 2001). Feeders were placed on mesh carton lids, and mosquitoes were allowed to feed on infected blood for 30–60 min. A plastic disposable 3 ml pipette was used to mix blood within the feeders every 4–7 min to prevent microfilariae from settling unevenly on the feeding membrane (Kartman 1953). A subset of blood-fed mosquitoes from the same cohort were kept in the same growth chamber for mortality comparison as controls. After blood feeding, chilled, immobilized mosquitoes were sorted to remove all but the fully engorged females.

Blood fed females were maintained in plastic containers and held at 90% RH and at constant or fluctuating temperature regimes (described above).

Monitoring D. immitis development

Three to five mosquitoes were frozen immediately after feeding and dissected to verify mean microfilariae ingested per mosquito. Mosquitoes were dissected at time points beginning before 130 accumulated HDUs and continued until the end of the experiment. At each time point, heads and abdomens of cold-immobilized females were dissected in separate drops of saline on glass microscope slides to be inspected visually for presence and staging of D. immitis larvae (Taylor 1960, Lai et al. 2000, Tiawsirisup 2007). Data were recorded per mosquito and included number, developmental stage, and mosquito body region/organ in which larvae were found.

Treatment conditions

We exposed D. immitis-infected Ae. aegypti to temperature regimes based on fluctuations recorded by weather monitoring stations from July–August, 2012 in US counties with high dog heartworm prevalence in the same year (CAPC, 2013)]. We also investigated effects of fluctuation above and below 14°C, the accepted minimum temperature for development of D. immitis in the mosquito (Fortin and Slocombe 1981). All mosquitoes experienced a 10 h L: 10 h D photo-regime with 2 h periods of dusk and dawn, temperature regimes were as follows: 19°C, 19±9°C, 22° C, 22±4°C, 26°, and 26±4°C.

Heartworm Development Unit prediction with real-world data

To illustrate the potential for error in HDU predictions of D. immitis transmission period in our own region, weather station data were gathered for transmission seasons in Ithaca, NY for the years 2012 and 2013. Accumulated development units over 30-day periods were determined by both standard HDU and our HDUhrs equations to compare the beginning and end of predicted transmission seasons (Figs 6 and 7).

Figure 6. 30-day accumulations of HDUs and HDUhrs/day for 2012 in Ithaca, NY.

Figure 6

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Bolded horizontal line indicates 130 HDUs, at which point L3 D. immitis are predicted to have matured and able to be transmitted.

Figure 7. 30-day accumulations of HDUs and HDUhrs/day for 2013 in Ithaca, NY.

Figure 7

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Bolded horizontal line indicates 130 HDUs, at which point L3 D. immitis are predicted to have matured and able to be transmitted.

Data Analysis

Number of D. immitis at each developmental stage was recorded as well as the time point of first detection of infective stage L3 larvae in mosquito heads. A Kaplan-Meier log-rank statistic was used to compare the rate of L3 detection in mosquito Malpighian tubules and heads over time points measured in HDU and HDUhrs/day. HDUhrs/day were calculated by dividing HDUhrs by 24 to convert to units directly comparable to HDUs. Rate of detection was compared between treatments of equal average daily temperature. Mosquito survival in days post treatment was also compared between infected and non-infected mosquitoes within each treatment using the Kaplan-Meier log-rank statistic.

Results

Time point of first detection of L3 D. immitis is presented for each treatment replicate in HDUhrs/day, HDU, and days post-infection (Table 1). HDUhrs/day and HDU measurements were equal for treatments maintained above 14°C, but they diverged when calculated for 19±9°C.

Table 1.

Infection date, temperature recordings, Dirofilaria immitis sample size, and timepoints of first detection of L3 Dirofilaria immitis in Malpighian tubules and heads are presented for each treatment replicate.

Time points for which HDUhrs/day=HDU are represented by “-“ in the HDU column. “x” marks cells with no observed larvae.

Treatment Infection date Avg Temperature (°C) (std dev) Worm count First L3 in Malpighian tubules Days post infection First L3 in heads Days post infection
HDUhrs/day1 HDU1 HDUhrs/day1 HDU1
19°C 10/2/13 19.22 (0.27) 251 125.25 - 24 x x x
8/6/13 19.09 (0.37) 212 131.36 - 26 131.36 - 26
19±9°C 10/2/13 19.34 (8.58) 104 127.60 101.81 19 127.60 101.81 19
8/6/13 19.04 (8.68) 172 116.00 86.96 17 122.76 91.96 18
22°C 8/21/13 21.7 (0.38) 180 122.23 - 16 138.33 - 18
22±4°C 8/21/13 20.79 (4.47) 170 122.29 - 18 146.38 - 19
5/29/13 21.91 (3.89) 422 135.45 - 17 134.04 - 17
26°C 10/9/13 25.40 (0.36) 153 130.60 - 12 137.68 - 12
8/21/13 25.37 (0.57) 38 100.61 - 9 x x x
26±4°C 10/9/13 26.03 (3.87) 183 130.67 - 11 130.67 - 11
5/29/13 26.11 (3.77) 363 118.11 - 10 132.19 - 11
8/21/13 25.42 (4.37) 195 126.38 - 11 126.38 - 11
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1

HDU refers to Heartworm Development Units

Kaplan-Meier analyses of L3 detection rate in mosquito heads and Malpighian tubules between treatments of the same average daily temperature are presented in Figs 1 and 2. HDUhrs/day and HDU were equal for all treatments of the same average daily temperature except 19±9°C and 19°C, therefore overall detection rate Kaplan-Meier analyses are shown in HDUhrs/day only(Figs 1 and 2). To highlight model discrepancies in analyzing 19±9°C and 19°C treatments, detection in these mosquito heads and Malpighian tubules was plotted on dual axes representing HDUhrs/day and HDU measurements of the same dissection time points (Figs 3 and 4). L3 D. immitis were detected in mosquito heads in 19±9°C treatments at earlier time points than 19°C (df=1, p<0.001) (Fig 1). Detection did not differ significantly in comparisons of other fluctuating and constant treatments.

Figure 1. Dirofilaria immitis L3 detection rate in mosquito heads is plotted against HDUhrs/day time points for constant (solid lines) and fluctuating (broken lines) temperature treatments.

Figure 1

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A reference line has been added to denote 130 HDUhrs/day, the point before which L3 D. immitis should not be detected.

*Treatment was significantly different from its counterpart of the same average daily temperature by the logrank test (df=1, p<0.001).

Figure 2. Dirofilaria immitis L3 detection rate in mosquito Malpighian tubules is plotted against HDUhrs/day time points for constant (solid lines) and fluctuating (broken lines) temperature treatments.

Figure 2

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A reference line has been added to denote 130 HDUhrs/day, the point before which L3 D. immitis should not be detected.

* Treatment was significantly different from its counterpart of the same average daily temperature by the logrank test (df=1, p<0.001).

Figure 3. Dirofilaria immitis L3 counts in mosquito heads against HDUhrs/day and HDU development times for 19±9°C and 19°C treatments.

Figure 3

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If HDU and HDUhrs/day were equivalent predictors of development, all bubbles would lie on the diagonal line of equality.

Figure 4. Dirofilaria immitis L3 counts in mosquito Malpighian tubules against HDUhrs/day and HDU development times for 19±9°C and 19°C treatments.

Figure 4

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If HDU and HDUhrs/day were equivalent predictors of development, all bubbles would lie on the diagonal line of equality.

Larval detection rates in Malpighian tubules were all significantly different between fluctuating and constant treatments of the same average daily temperature (df=1, p<0.001) (Fig 2). L3 D. immitis in Malpighian tubules were detected later in fluctuating than in constant treatments, except where L3 were detected earlier in 19±9°C than constant 19°C treatments (Fig 1).

Kaplan-Meier cumulative survival was analyzed between infected and control mosquitoes within temperature treatments. Infected mosquitoes had higher mortality rate than non-infected mosquitoes across all treatments (df=1, p<0.001) except constant 19°C (df=1, p=0.639) (Fig 5). The 19°C treatment provided few observations of L3 stage larvae, and therefore may not have suffered mortality from developing worms.

Figure 5. Cumulative survival of non-infected (broken lines) and infected (solid lines) mosquitoes.

Figure 5

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* Treatment was significantly different from its counterpart of the same average daily temperature by the logrank test (df=1, p<0.001).

Calculations of D. immitis transmission season in Ithaca, NY differed between hourly and daily temperature models. HDU calculation using average daily temperature predicted transmission seasons to span from June 18th–September 23rd, 2012 and June 27th–September 21st, 2013. Hourly calculations predicted the beginning of the same seasons seven days earlier in 2012 and two days earlier in 2013; the predicted end dates by hourly HDU modeling were two and three days later for 2012 and 2013, respectively. Standard HDU modeling also indicated that 2013 transmission temporarily stopped on August 23rd since larvae developing in the prior 30-day period would only have accumulated 129.8 HDUs, while hourly calculations of HDUs show that colder periods of that summer were not low enough to restrict D. immitis development and transmission.

Discussion

Spatiotemporal models of transmission risk define D. immitis development periods as time windows no longer than 30 days during which 130 HDUs can be accumulated (Knight and Lok 1998, Sacks et al. 2004). The underlying assumptions of the HDU approach are: 1) infected mosquito longevity in the field is approximately 30 days no matter what season of the year; 2) infective stage D. immitis at the beginning of each season develop from microfilariae ingested by the vector during the same uninterrupted development period (i.e., not carried over from overwintering mosquitoes or a long interruption of transmission season); and 3) development thresholds can be represented by average daily temperature (often calculated as maximum temperature + minimum temperature/2) or minimum daily temperature (Vezzani and Carbajo 2006, Genchi et al. 2011).

Our results suggest that modeling low resolution temperature data such as daily average or daily minimum temperature can underestimate D. immitis development rate and range of transmission. D. immitis development predictions were more accurate when calculated with hourly temperature observations rather than average daily temperature. Seemingly small discrepancies between average daily and hourly temperature accumulations compounded such that infective stage larvae experiencing 19×9°C were first detected in mosquito heads eight days earlier than D. immitis under constant 19°C (Table 1). The first L3 larvae detected in mosquito heads at 19×9°C had accumulated only 101.81 and 91.96 HDUs calculated by average daily temperature—much earlier than the standard 130 HDU model predictions; however, if calculated by hourly temperature above threshold, these larvae accumulated 127.60 and 122.76 HDUhrs/day. Average daily temperature HDU calculations underestimated D. immitis development under fluctuating conditions spanning the 14°C development threshold, and risk models based on minimum daily temperature would predict no D. immitis development under this regime’s minimum daily temperature of 10°C.

Analysis of D. immitis development in mosquito Malpighian tubules showed that 19±9°C larvae developed to L3 stage faster than larvae at 19°C, even when using an hourly calculated HDU scale (Fig 2). This suggests that there is a biological difference in development rate between these two treatments that cannot be accounted for by differences in degree-day models. Larvae in treatments that remained above the threshold temperature in their fluctuations exhibited a different trend: time to L3 development was longer than larvae under constant temperature (Fig 2). Differential responses to temperature patterns may serve to modulate development in natural populations at the beginning or end of transmission season. In our study, the developmental delay in larvae experiencing fluctuating temperature did not lead to significant differences in migration to mosquito heads, perhaps due to low sample size within the time period of developmental difference. Other amplitudes and baseline averages of temperature fluctuation could have a greater effect on L3 migration, as has been observed in studies of malaria extrinsic incubation period and climate (Paaijmans et al. 2009, 2010).

The extent to which the effects observed in our study are generalizable to wild populations of D. immitis and mosquito vectors requires further study. Aedes aegypti is not a common vector of D. immitis across most of the US, and natural history differences in overwintering, host-seeking, and habitat will affect each mosquito species’ relative importance in D. immitis transmission. In addition, susceptibility and vector competence of mosquitoes for D. immitis will vary within and between vector species and, potentially, between populations of D. immitis (Bradley et al. 1990, Tiawsirisup 2007, Ledesma and Harrington 2011). In our study, we only tested doses of 3,500 microfilaria/ml. The dynamics of typical microfilarial densities of infectious blood meals taken by wild mosquitoes are undescribed, and may vary with reservoir populations (stray dogs, owned dogs, or wild canids).

Actual temperature fluctuations experienced by vectors and their parasites would also depend not only on ambient air temperature, but on microhabitat conditions during periods of activity and rest (Meyer et al. 1990). Physiological differences between geographical isolates of D. immitis may contribute to developmental responses to temperature fluctuations of different amplitude or baseline average temperature than is typical of their location. Extrinsic incubation period developmental differences were observed by Ernst and Slocombe (1983) when rearing Georgia and Ontario D. immitis strains under low temperatures, and, in their preliminary trials, Georgia strain larvae exhibited higher mortality than Ontario strain larvae when exposed to 14°C, and Ontario larvae remained at L2 stage for a longer duration than Georgia strain when reared at a constant temperature of 26°C. Although their trials were focused on the effect of four to eight days of exposure to low temperatures during extrinsic incubation period, their conclusions support the hypothesis that temperature changes during extrinsic incubation period alter D. immitis development in ways beyond the standard HDU model.

Our transmission season models for years 2012 and 2013 in Ithaca, NY provide an example of the underestimation potential of standard HDUs as compared to hourly calculated HDUs when using the same weather station data. Although the greatest total disagreement between models for our region was nine days, discrepancies will be greater in cases where temperatures during the beginning and end of the transmission season hover just above and below threshold. Surveillance and prevention measures informed by underestimates of dog heartworm range and transmission period could be hindered in limiting emergence of the disease in naïve host populations of colder climates. Sacks and others (2004) constructed a model of dog heartworm prevalence that accurately identified areas of high and medium prevalence by incorporating climate data, coyote serology and carcass inspection, vegetation cover, and precipitation; however, actual prevalence in predicted low-prevalence areas was underestimated. Slocombe and others (1989) developed isolines circumscribing regions sharing the same start or end dates of heartworm transmission season as determined by HDU accumulation. Even with their careful accounting for mosquito and heartworm factors, some transmission occurred before predictive models had accumulated 130 HDUs. Consequently, isolines circumscribing at-risk regions underestimated transmission season by not taking into account temperature fluctuation around average daily temperatures at or below 14°C. Based on our results, the current isolines would have to be redrawn to contain a larger area due to more accurate start and end dates of potential transmission. Veterinarians, pet owners, and mosquito control programs would be better informed by these updates, and preventative measures could be enacted to protect companion animals in regions currently not considered at-risk.

We conclude that there are mathematical and biological reasons that make defining low-risk areas with average daily temperature models inappropriate. Furthermore, as climate change affects weather predictability and stability, the impact of fine resolution temperature fluctuation on vector-borne disease transmission becomes increasingly important. Weather station data usually include finer resolution temperature observations than daily averages, and new insights could be gained from incorporating these measures into degree-day algorithms predicting transmission risk. Natural history factors of key heartworm vectors could also be introduced into models where a particular species is known to predominate transmission season. Collectively, greater insight into the drivers of dog heartworm transmission risk, especially in the often-overlooked mosquito vector, will lead to more refined predictive models and fewer heartworm infections that could be avoided with up-to-date risk information.

  • We compare a degree-hour to a degree-day model of Dirofilaria immitis development.

  • D. immitis development in Aedes aegypti was observed under fluctuating temperature.

  • The standard degree-day model underestimated development in colder temperatures.

  • Our hourly temperature model accurately predicts D. immitis development.

  • Hourly temperature models can prevent underestimating heartworm risk around 19°C.

Acknowledgments

Our thanks for providing D. immitis microfilariae go to Dr. Byron Blagburn and to Cheri-Hill Kennels. Special thanks go to Sylvie Pitcher, Ethan Degner, and Roy Faiman for help in dissection and counting larvae. We also thank Dr. Dwight D. Bowman for his advice and guidance in differentiating larval developmental stages. This research was supported in part by NIH Training Grant T32RR018269 and Novartis Animal Health.

Footnotes

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