Development of a Molecular Assay for the Determination of Eimeria tenella Oocyst Viability

doi:10.21203/rs.3.rs-5018141/v1

Download PDF

Research Article

Development of a Molecular Assay for the Determination of Eimeria tenella Oocyst Viability

https://doi.org/10.21203/rs.3.rs-5018141/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Coccidiosis is a cosmopolitan disease with major impacts on the commercial poultry industry. The causative agents, Apicomplexan parasites of the genus Eimeria, infect epithelial cells of the intestine causing diarrhea, secondary infections, and negatively impacting meat or egg production. The infective parasite stage, the oocyst, is shed in feces and must sporulate over several days in the environment to reach infectivity. The number of viable, sporulated oocysts ingested is proportional to the severity of disease. The self-limiting and highly immunogenic nature of infection by Eimeria spp. make live vaccination an effective means of coccidiosis control. High prevalence of drug resistance and consumer demand for poultry products with no “human medically important antibiotics” or raised without antibiotics indicates an increasing role for vaccination in the control of coccidiosis going forward. Paramount to vaccine efficacy is the ability to administer precise numbers of viable oocysts to stimulate the development of immunity without causing disease. Unfortunately, no rapid and accurate method for determination of oocyst viability is presently available. Time-consuming and expensive live-infection trials are the current gold standard.

Work completed for this study demonstrated the development of a molecular assay for the determination of Eimeria tenella Tyzzer, 1929 oocyst viability. The assay used the quantification of specific biomolecules to assess changes in gene expression in response to heat stimulation that indicates viability of a sample of oocysts. Data showed strong predictive value for infectivity of an oocyst sample as confirmed by oocyst output (fecundity) in infection trials. Use of the assay would be low cost compared to the planning, resources, execution, and data collection required for infection trials. Additionally, the assay was shown to offer results in hours versus days for the live infection trials. Development of this first-generation assay paves the way for further development of assays for the determination of viability in mixed species samples (multivalent vaccines), for vaccine quality control at hatcheries, and with application in environmental monitoring (“early warning” programs) and on-farm diagnostics.

Coccidiosis

Viability

Live Vaccines

Eimeria

Coccidiosis, caused by apicomplexan parasites of the genus Eimeria, has long been a major biological threat to the poultry industry, where stocking densities and immunological homogeneity together form ideal conditions for rapid parasite amplification (Chapman and Jeffers 2014; Dalloul and Lillehoj 2006; Sharman et al. 2010). In 2006, the estimated worldwide cost of coccidiosis to the poultry industry, including production loss and disease control, was estimated to exceed USD $3 billion, and was estimated at USD $13.3 billion for the year 2016 (Blake et al. 2020). Widespread drug resistance has greatly reduced the utility of anticoccidial drugs (Abbas et al., 2011; Chapman et al., 2002, 2013).

The application of live, unattenuated vaccines has become an increasingly employed method of coccidiosis control (Chapman et al. 2002, 2013; Paganini 2005; Sharman et al. 2010). Administration of the infectious parasite stage (sporulated oocysts) leads to the establishment of biologically limited but immunostimulatory infection (Jordan et al. 2011; Sokale et al. 2021; Tewari and Maharan 2011). With proper flock management, subclinical infections established by vaccination leave the host with robust, species-specific protective immunity against future infection (Chapman et al. 2002; Long et al. 1986; Price 2012; Sharman et al. 2010). Unfortunately, the success of vaccination programs is currently limited by several obstacles, all of which contribute to the risk of failure and high cost of vaccines. Accurate dosage is paramount to vaccine success; the administration of too many infective parasites will negatively impact bird health while the administration of too few will fail to stimulate protective immunity (Blake et al. 2005; Dibner et al. 2003; Sharman et al. 2010; Tewari and Maharan 2011). Vaccine potency is not static and is subject to several variables (Augustine 1980; Jenkins et al. 2013; Price 2014). Each vaccine lot must be tested in live animals so infectivity and correct dosage can be confirmed (Dibner et al. 2003; Long et al. 1986; Sharman et al. 2010). Infection trials are time consuming, expensive, and error-prone (Bortoluzzi et al. 2018; Chapman et al. 2016; Scare et al. 2017). There is currently no validated, accessible, rapid, and accurate method to determine the percent viability of a sample of oocysts. Ultimately, the difficulty and expense of establishing oocyst viability impede the potential for vaccination to be the highly effective control strategy that it could be (Dibner et al. 2003; Long et al. 1986; Sharman et al. 2010). The development of a rapid in vitro assay for the determination of oocyst viability would reduce the need for the use of live animals in vaccine testing, extend vaccine shelf life, and allow for improvement of overall vaccine efficacy via the fine-tuning of the various constituent species. These outcomes have obvious benefits to animal welfare and food security.

Sporulated oocysts found in live coccidiosis vaccines are produced in vivo, collected from the feces of their hosts, and permitted to sporulate before inclusion in a live vaccine. Sporulation is the process by which the non-infectious diploid eimerian oocyst (a zygote that resulted from the fertilization of a macrogamete by a microgamete) develops into the infectious oocyst that holds eight haploid sporozoites (the sporozoite being the infectious unit). Once sporulation is complete, parasite energy metabolism and transcriptional activities are minimal compared to other lifecycle stages (Alloco et al. 1999; Schaap et al. 2005). The terms hypobiosis and hypobiotic are used herein to refer to this quiescent state. The oocyst wall, composed predominantly of glycoproteins and lipids (Stotish et al. 1978; Mai 2009), is environmentally resistant and can withstand many chemicals (Belli et al. 2006). In the case of galliform-infecting Eimeria spp., physical grinding in the gizzard and the actions of digestive enzymes are required for emergence of the sporozoites (Belli et al. 2006; López-Osorio et al. 2020). The environmentally resistant and hypobiotic nature of the sporulated oocyst allow it to remain viable in the external environment for extended periods of time (Jenkins et al. 2013; Perkins et al. 2000; Tewari and Maharan 2011).

The sporulated oocyst can be compared to the seed of a plant. Sporulated oocysts contain a mass of the storage polysaccharide amylopectin (Ryley et al. 1969), which is similar to what a seed would contain (Penfield 2017). Both the seed and the sporulated oocyst contain a complete set of genetic information required to continue its lifecycle, and both are protected by a rugged layer (Belli et al. 2006; Mai et al. 2009; Penfield 2017). A stark difference between seed and oocyst emerges when the exit from dormancy is considered. When favorable conditions for continuation of the lifecycle are encountered by a seed, it begins the process of germination, which includes the critical component of DNA repair (Hay and Whitehouse 2017; Waterworth et al. 2015, 2019; Wolny et al. 2018). However, the oocyst has no such opportunity. Transit time (time from ingestion to production of feces) for 26- to 31 day-old broiler chickens can be as short as 112 minutes (Kim et al. 2013). Eimeria tenella Tyzzer, 1929 which infects the ceca, near the end of the digestive tract, would therefore be expected to establish infection in under two hours; for Eimeria acervulina Tyzzer, 1929 parasitizing the duodenum, near the start of the digestive tract, infection would be established in far shorter time (Parry et al. 1992). Given the lack of opportunity for processes akin to germination, sporozoites within oocysts must retain some low level of metabolic activity to support ongoing genome maintenance and persist in a state from which they can quickly initiate infections.

Development of an in vitro assay to determine Eimeria spp. oocyst viability is challenging. The unique biology of these parasites, and their resilient oocysts, preclude the application of standard methods for viability assessment. Transcription and messenger RNA (mRNA) maturation are energy-consuming processes and require the coordination of multiple complex systems. Due to the complex nature of oocysts, an in vitro assay to determine oocyst viability must assess different viability measures than standard, such as active synthesis of mRNA that can only be produced by living, infectious parasites.

The objectives of the research described herein were to develop an oocyst viability assay that relies on the measurement of products of transcriptional activity, mRNAs, generated in response to heat stimulation. Although heat stimulation approximates only one aspect of the stimuli encountered by the parasite, it was predicted to be sufficient in eliciting a measurable transcriptional response, the magnitude of which could be further examined for its relationship with fecundity. The described assay is a “beta version” of a molecular assay for the measurement of precise viability of E. tenella oocysts in several hours (as opposed to the > 10 days required for standard infection trials; Bortoluzzi et al. 2018; Chapman et al. 2016; Scare et al. 2017).

Oocyst Propagation and Processing for Next-Gen Sequencing

Ten 27-day-old Ross 308 male broiler chickens were infected with 2,000 freshly propagated and sporulated E. tenella oocysts by oral gavage. Eight days post-infection, birds were killed, and ceca removed. Contents of ceca, primarily consisting of oocyst cores, were processed in a blender with approximately three times the volume of distilled water. The slurry was sieved to remove larger debris and then pelleted in a centrifuge for 10 minutes at 1500 × g. The supernatant was discarded, and the pellet was resuspended in six times the volume of saturated salt solution (sat. NaCl, aqueous). Oocysts were floated by centrifugation (15 minutes at 1,000 × g with slow brake). Supernatant was collected and diluted to 10 times the volume in distilled water. The pellet-resuspend-wash sequence was repeated two additional times before a second saturated salt float including 0.1% Tween 20 (0.1% v/v Tween 20 in sat. NaCl, aqueous) was conducted. The upper layer of the supernatant was collected and then subjected to three wash-centrifugation cycles with distilled water as described above. Oocysts were resuspended in 500 mL potassium dichromate solution (K₂Cr₂O₇; 2% w/v aqueous) and sporulated at room temperature (21^oC) with agitation on a rotary shaker. Following the completion of sporulation in 150 cm² sterile polystyrene vented-cap cell culture flaks (Corning Inc., Corning, NY, item# RK-01936-20) oocysts were stored at 21^oC to accelerate aging or under standard storage conditions, at 4^oC.

Transcriptome Sequencing

RNA was isolated from oocyst sub-samples stored at room temperature at four time points: 21-, 28-, 35-, and 42-days post collection from ceca. For each time point, RNA was isolated from two parallel aliquots of ~ 30 million oocysts, one that had been held at 41^oC for 90 minutes prior to RNA extraction (HS), and one that had been maintained at the temperature at which it was stored (steady state; SS). The HS and SS sub-samples at each time point were processed for RNA extraction in parallel using a Qiagen RNeasy mini kit as per manufacturer’s instructions with modifications as described. Oocysts were pelleted via centrifugation and then resuspended in 300 µL Buffer RLT with dithiothreitol (DTT; 40 mM). Oocysts were disrupted using ~ 1 g, 0.5 mm glass beads (BioSpec, Bartlesville, OK, catalog# 11079105) in a Precellys® bead mill homogenizer (Bertin Technologies, Montigny-le-Bretonneux, France) in 3, 30 second bursts at 6.0 m/s separated by 5 second pauses, followed by being placed on wet ice. Tubes were spun briefly to reduce frothing and 150 µL Buffer RLT (+ 40 mM DTT) was added to each. A 1000 µL pipette was used to stir the contents of each tube and transfer the liquid to QIAshredder columns (Qiagen, Hilden, Germany). Columns were spun for 2 minutes at maximum speed. Flow through was transferred to a new 1.5 mL tube and one volume of 70% EtOH was added to each sample, followed by mixing via pipetting and transferring to the RNeasy® spin column. Subsequent steps used Qiagen RNeasy® Mini Kit as per manufacturer’s instructions. RNA was eluted from columns in 44 µL nuclease-free water (NFW) and stored at -80^oC.

All samples were analyzed using an hsD5000 TapeStation assay by the Genomics Facility at the University of Guelph (Ontario, Canada). RNA from each time point and temperature treatment was submitted to Genome Quebec for library construction and sequencing via Illumina HiSeq400 SR50 (Illumina Inc., San Diego, California, USA). Samples were reanalyzed using an Agilent Bioanalyzer, and stranded libraries were prepared using NEBNext® Single Cell/Low Input cDNA Synthesis & Amplification Module with oligo dT primers. NEBNext_dual adaptors were used (Read one sequence: AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC; read two sequence: AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT). Library insert sizes ranged from 255 to 287 bp. The eight samples were run together in one sequencing lane, with 0.125 sequencing units per sample.

Identification of Putative Viability Assay Targets

One million quality-filtered reads (Q30) from each sample were assembled to a collection of 8,585 previously-published reference sequences of putative protein-coding genes in E. tenella (Houghton strain; Accession #PRJNA263385; Reid et al. 2014) using Geneious assembler (2023.2.3; 10% gaps allowed, maximum gap size = 3, word length = 24, index word length = 14, maximum mismatches per read = 5%, maximum ambiguity = 4; ignored reads repeated more than eight times). Abundance of each represented RNA was determined as reads per kilobase per million mapped reads (RPKM; Formula 1). Using Excel (Microsoft Corporation 2023). The increase in abundance that occurred with heat stimulation of these 54 putative viability targets (RPKM_HS / RPKM_SS) was subsequently calculated at 21-, 28-, and 35- days.

qPCR Primer Design

All 10 mRNA that were present in HS samples at 10 or more times the abundance of SS samples (RPKM_HS/RPKM_SS ≥ 10) in 42-day-old oocysts were considered as possible viability assay targets. From this list, three were removed from consideration due to having comparably low coverage in HS samples (RPKM < 200), which suggested they would not provide sufficient assay dynamic range. An additional four were removed from consideration due to being products of genes comprised of single exons, which prevented the design of amplification primers specific for mature rRNA (Bustin 2000). A total of three transcripts were identified as targets with increased abundance in HS samples. An additional mRNA target was considered for possible use as a reference or normalizer target.

The following parameters, suggested by the manufacturer of PowerUP SYBR (Thermo Fisher Scientific, Ottawa, ON), guided primer design for the four qPCR targets of interest: optimal primer length = 20 bp; optimal number of G’s or C’s allowed in the last five bases at the 3′ end = 2 (no more than three and at least two were required); GC content = 30 to 70%; no single-base runs of more than three; melt temperatures (T_m) = 61 to 62^oC; amplicon length = 50 to 150 bp. Primer T_ms were calculated via SantaLucia1998 algorithm within Geneious Prime (2020.2.5; salt correction: SantaLucia 1998, monovalent (Na⁺): 50 mM, divalent (Mg⁺⁺): 1.5 mM, dNTPs: 0.5 mM, oligo: 200 nM) and DNA Fold within Geneious Prime (2020.2.5) was used to ensure no major tendencies for secondary structures formation either within a single primer, self-self, between the primers of one primer set, or within the amplicon. At least one primer per pair was designed to span an intron removal site (exon/exon junction), and the sequences of introns were considered (reference sequences used in primer design are included in Table 1). Primer formation of self-dimers, hairpins, and cross-dimers was assessed using Beacon Designer™ Free Edition (Premier Biosoft) as described by Thornton and Basu (2015). Amplicons were checked for secondary structures using UNAFold (Markham and Zuker 2008) as described by Thornton and Basu (2015).

Table 1

Quantitative PCR primers used to amplify putative viability-reflecting qPCR targets (V-), a spike-in external mRNA control (Luc-1), and an internal genomic control (S1) in nucleic acid recovered from aged *Eimeria tenella* oocysts, with or without heat stimulation. For viability targets, reference sequences referred to mRNA within GCF000499545.2, associated with bioproject PRJNA263385. Genomic reference sequences used to consider intron sequences are indicated in parentheses. The spike-in external luciferase control RNA sequence was obtained from Promega (catalog number L4561)
Primer set name	Reference sequence	T_m (forward; ^oC)	T_m (reverse, ^oC)	Amplicon size (bp)
V-3985	XM_013373985.1 (ETH_00021280)	61.6	61.8	123
V-9639	XM_013379639.1 (ETH_00028575)	61.4	61.5	89
V-2879	XM_013372879.1 (ETH_00030955)	61.7	61.7	75
8585_2	XM_013378585.1 (HQ317455.1)	61.9	61.0	123
Luc-1	Luciferase (Promega)	61.3	60.7	127
S1	AY571629.1	61.2	61.1	76

Three primer pairs were designed for putative viability targets (V-2879, V-3985, and V-9639), and two pairs were designed to target XM_013378585.1 (primer sets 8585_1 and _2). An additional primer set was designed using the same parameters to target luciferase RNA (Promega, Madison, WI; catalog number L4561), which functioned as a “spike-in control” to allow data normalization for variations in RNA decay and efficiencies of RNA recovery and reverse transcription. A sixth primer set, S1, originally published by Kruth, Lane, and Barta (2024), targeted multi-copy nuclear RAPD-SCAR marker Tn-E03-1161 to support genomic quantification. Primers are summarized in Table 1. Additional documentation of viability primers, including specific primer sequences, can be found in Supplementary File 1.

Construction of Control Plasmid and qPCR Assay Validation

A control plasmid was designed that featured a single copy of each of the six qPCR targets, from 10 nucleotides upstream of the forward (F) primer anneal site through to 10 nucleotides downstream of the reverse (R) primer anneal site. A random, unique 10 bp spacer that lacked homology with qPCR amplicons was inserted between each target sequence. Two of the transcript-targeting primer sets targeted the same transcript, with the anneal site for 8585_1_R and 8585_2_F overlapping. In this case, the sequence representing the cDNA sequence spanning 10 nucleotides upstream of 8585_1_F to 10 nucleotides downstream of 8585_2_R was used. Several alterations were made to the sequence as described above to improve the feasibility of synthesis. Adenine at position 174 was changed to T (this substitution occurred within the amplicon produced from primer set V-0187). High AT content of the apicoplast genome made qPCR primer design challenging; replacement of the 10 bases up and downstream of the primer anneal locations with alternate apicoplast sequences was required.

The designed 2,062 nucleotide sequence was synthesized as a gBlock™ Gene Fragment by Integrated DNA Technologies (IDT; Coralville, Iowa). The gBlock™ Gene Fragment was received as 1000 ng of dry DNA, which was rehydrated with 40 µL TE (Tris-EDTA) buffer (Thermo Scientific™, Ottawa, ON) and was ligated into a pJET1.2/blunt vector using a CloneJET PCR Cloning Kit (Thermo Scientific™). OneShot™ TOP10 Chemically competent Escherichia. coli cells (Invitrogen, Burlington, ON) were transformed with the construct-containing plasmid. Plasmids were recovered from overnight growth in standard Luria broth using GeneJET Plasmid Midiprep Kit (Thermo Scientific™). All protocols were as per the manufacturer’s instructions.

To confirm that the sequence of the cloned SC plasmid had 100% identity with that of the designed gBlock™ SC sequence, recovered plasmid was submitted to the Molecular Biology Unit of the Laboratory Services Division, University of Guelph (Ontario, Canada) for Sanger sequencing using an Applied Biosystems 3730 DNA analyzer with ABI Prism® DNA Sequencing Analysis Software (Ver. 4.0, Applied Biosystems Inc., Foster City, California). Sequence identity between the plasmid insert and the designed gBlock™ SC sequence was confirmed by alignment using Multiple Align in Geneious Prime (2020.2.5). The pJET1.2 plasmid with synthetic control sequence is referred to as SC (synthetic control sequence-containing) plasmid from this point forward. The full plasmid insert sequence and a table detailing its components are included in Supplementary File 2.

Aged Oocyst Infection Trial

To generate the initial batch of oocysts for the aging trial, 40, 6-week-old Male Ross 308 broiler chickens were infected with 1,000 freshly propagated E. tenella (Guelph strain) oocysts each by oral gavage. Eight days after infection, birds were killed humanely, and their ceca collected. Oocysts were cleaned and processed as described above, with Tween 20 omitted. Oocysts were stored potassium dichromate (K₂Cr₂O₇) in vented-cap tissue-culture flasks either at 21^oC to accelerate aging or at 4^oC to replicate standard storage conditions, with manual agitation and replacement of evaporation volume with ddH₂O once per week. Flasks were covered with aluminum foil to prevent light exposure. These oocysts were referred to as Lot 1.

The aged oocyst infection trial was designed to test the infectivity of oocyst subsamples via two parallel mechanisms: fecundity (oocysts shed per oocyst ingested), and magnitude of specific transcriptional response in HS subsamples over SS subsamples as measured by qPCR. The trial included four time points: 2.5 months after Lot 1 oocysts were first collected, and every two months after that for three additional time points.

At each time point, a sample of 1.26 × 10⁷ oocysts was taken from each of the oocyst stocks involved in that time point (for time point 1, only Lot 1 stored at 21^oC, and Lot 1 stored at 4^oC). Oocyst samples were pelleted via centrifugation, washed with ddH₂O, and resuspended in ddH₂O, then divided into two aliquots of 6.30 × 10⁶ oocysts each. One was incubated at 41^oC for 90 minutes (HS), while the other was maintained at its original storage conditions (SS). After incubation, subsamples were pelleted via centrifugation and all supernatant removed. Pellets were weighed and stored at -80^oC for later RNA recovery.

On the same days that oocyst aliquots were taken, one to three cages of three to four dual-purpose male chickens, ranging from 12 to 14 days old, were infected with either 100 or 500 oocysts in sterile saline by oral gavage. At each time point, Lot 1 oocysts stored at either 4^oC or 21^oC were used, and at time points 2, 3, and 4, oocysts generated from infections established at prior time points and stored at 21^oC were additionally used. A control cage of three birds received only oral saline gavage was included at each time point. After time point 1, the specific combination of bird numbers, dose size, and oocyst sub stocks used was chosen by referencing fecundity data produced at the previous time point. The specific combinations of factors used at each timepoint are summarized in Supplementary File 3.

Feces from each cage were collected from 5 to 10 days post infection and stored in potassium dichromate at room temperature. On day 10, birds were killed humanely, and ceca removed and inspected to ensure no endogenous oocysts were present and the period of patency was completed. Two 5 mL feces subsamples were taken, upon which McMaster counts were performed to enumerate oocysts per mL feces (see Supplementary File 3). Fecundities were subsequently calculated using Formula 2. The remaining feces were pooled, processed, and stored at 21^oC as described above. Oocysts generated from infection at time point 1 were named Lot 2, those generated from the infection started at time point 2 were named Lot 3, etc.

RNA Recovery and Quantification of Putative Viability Targets in Time Point Samples

At the completion of the time point infection trial, the RNA extraction protocol described above was used with several modifications. Briefly, each isolation was performed on 6.30 × 10⁶ oocysts, and each RNA extraction used 155 µL Buffer RLT (+ 40 mM DTT) and 0.36 g 0.5 mm glass beads per 100 µL extraction volume (i.e., combined volume of RLT and oocysts) for the initial bead-breaking step, followed by the addition of 345 µL Buffer RLT (+ 40 mM DTT) that included 20 ng luciferase RNA (“spike-in”). Supplementary File 4 details the completed work to determine appropriate quantity of spike-in luciferase RNA. RNA was eluted in 31 µL NFW and eluent was subsequently re-eluted through the column to ensure maximum recovery. Concentration was determined via Qubit and RNA integrity number (RIN) was determined by the Genomics Facility at the University of Guelph using an hsD5000 TapeStation assay.

All RNA samples recovered during the live infection trial were reverse transcribed with SuperScript IV VILO Master Mix RT Master Mix Kit (Invitrogen), as per manufacturer’s instructions. This resulted in a 50% template dilution. Complementary DNA (cDNA) was further diluted to 20% concentration, for a final concentration of 10% of that of the originally recovered RNA. Quantitative PCR was performed with each primer set using 2× PowerUP SYBR Master Mix (Applied Biosystems™, Waltham, MA) as per manufacturer’s instructions, using 384 well plates, with single reaction volumes of 10 µL, primer concentration of 600 nM, and 2.5 µL of template cDNA or NFW for no-template controls (NTC) per reaction. Technical triplicates were used for each reaction, with two repeat plates used per experimental time point. Each primer combination was additionally run on a series of three, 100-fold dilutions of the control SC plasmid (ranging either from 2.76 × 10⁸ to 2.76 × 10⁴ copies per reaction, or from 2.76 × 10⁷ to 2.76 × 10³ copies per reaction). A QuantStudio 7 Pro system (Applied Biosystems™) was used for thermal cycling and data capture with the following program: 2 minutes at 50^oC, 2 minutes at 95^oC; followed by 40 cycles of: 15 seconds at 95^oC, 1 minute at 60^oC. The melt program used was: 95^oC for 15 seconds (ramp rate: 1.6^oC / second), 60^oC for 1 minute (1.6^oC / second), 95^oC for 15 seconds (ramp rate: 0.15^oC / second). Cover temperature was set to 105^oC.

Design and Analysis Software Version 2.6.0 (Applied Biosystems™) was used for preliminary analysis such as inspection of melt curves and triplicate wells, and to confirm absence of signal in no-template control wells. All further analysis was executed in Excel (Microsoft Corporation 2023). Data from time point samples was analyzed with a relative quantification approach as described by Taylor et al. (2019). Gene expression for each of the transcriptional targets was calculated in HS samples, normalized to Luc-1 and S1 and using time point-paired SS samples as controls. Plate-specific amplification efficiency, based on control plasmid standards, were used in standard normalized gene expression (NGE) calculations, as described by Taylor et al. (2019). To assess assay efficiency of RNA recovery and reverse transcription, C_q values generated from, S1, and Luc-1 primer sets were additionally interpreted as absolute target copy numbers via Formula 3.

[Formula 3] CN = 10^{[Cq – y intercept]/slope}

6.4.1 Oocyst Propagation and Processing for RNA Sequencing

A fresh stock of oocysts was generated for ageing and subsequent transcriptome sequencing for the identification of candidate targets for use in the viability assay. A total of 5.74 × 10⁸ oocysts were recovered for transcriptome sequencing. At seven days postcollection, 98% of oocysts had morphology consistent with completed sporulation, while the remaining 2% were arrested at the sporoblast stage. An additional stock of oocysts was generated for use in the infection trial with parallel quantification of candidate viability assay targets. For the infection trial, a total of 1.1 × 10⁸ oocysts were recovered (an average of 2.8 × 10⁶ oocysts from each infected bird) and these oocysts achieved 97% sporulation by seven days post-collection.

6.4.2 RNA Isolation and Next-Gen Sequencing

Transcriptome sequencing was used to identify transcripts that showed the greatest increases in abundance in HS versus parallel steady-state SS oocysts. For transcriptome sequencing, total RNA recovered from oocyst samples ranged from 0.79 to 3.33 µg, with a pattern of decreasing RNA recovered with increasing oocyst age. For all time points but one, RNA integrity (reflected by RIN) was greater in samples that had not been heat stimulated. Next-Gen sequencing generated 2.83 × 10⁷ to 4.08 × 10⁷ reads per sample. To identify candidate viability assay targets, reads from each sample were mapped to a set of existing transcriptome reference sequences generated from pooled RNA from several lifecycle stages (Reid et al. 2014) and the transcripts that showed the greatest increases in abundance in HS samples (versus SS samples from the same time point) were identified. Approximately one third of reads from each data set mapped to the 8,585 reference sequences and generated 5,983 to 6,577 contigs per sample. Four hundred and sixty of the reference sequences were not represented in any sample and 4,206 reference sequences were detected in all eight samples. Twenty-one mRNAs were detected in all HS samples and no SS samples. Next-Gen sequence assembly results are presented in Table 2.

Table 2

Summary of raw data and Illumina HiSeq read mapping generated from RNA recovered from *Eimeria tenella* oocysts aged from 21 to 42 days post-collection from ceca, with or without heat stimulation and of raw data and results of read mapping
Days elapsed^a	Incubation^b	RIN^c	ng/µL^d,e	Total µg^e	A_260/280^e	# Raw reads	# Mapped to reference sequences^f	# Contigs generated^f
21	21	5.8	75.79	3.33	2.09	34,074,225	321,793	6,373
21	41	1.7	29.74	1.31	2.03	36,426,590	329,954	6,126
28	21	6.2	50.20	2.21	2.24	37,795,467	335,612	5,983
28	41	N/A	25.41	1.12	2.37	34,674,356	313,448	6,188
35	21	6.1	20.45	0.90	2.25	28,278,349	334,920	6,166
35	41	6.2	26.49	1.17	2.11	35,367,774	324,937	6,233
42	21	6.3	17.92	0.79	2.10	36,281,441	328,718	6,273
42	41	N/A	21.15	0.93	2.08	40,830,160	320,380	6,577
^aDays elapsed = days since oocyst collection from ceca ^bIncubation = temperature treatment reported in ^oC; heat stimulated = 41^oC, steady state = 21^oC ^cRIN = RNA integrity number; reported from Bioanalyzer results generated by Genome Quebec ^dConcentration of recovered RNA (ng/µL) ^eReported from Nanodrop results generated by Genome Quebec ^fOf 1 million read subsets

Twenty-three mRNAs were identified that showed an increase in abundance greater than five-fold with heat stimulation at 42 elapsed days (see Fig. 1). Of this subset, 10 showed an increase greater than 10-fold (see Table 3). Of this smaller subset, seven had RPKM greater than 250 in HS samples. Of this smaller subset of seven, three possessed exon/exon junctions that could be spanned by a qPCR primer, making them strong target candidates: XM_013379639.1; XM_013372879.1; and XM_013373985.1.

Response to heat stimulation of the three putative viability targets at all four time points was examined via comparison of RPKM values, summarized in Fig. 2. An additional mRNA, XM_013378585.1, identified as glyceraldehyde-3-phosphate dehydrogenase (GAPDH), was of interest as a potential reference as it showed little variation in the magnitude of change in abundance in HS samples at all four time points (also shown in Fig. 2). Quantitative PCR primer sets were designed for all four of these transcripts of interest.

Table 3

Summary of Eimeria tenella mRNAs considered as qPCR viability assay targets
Accession (XM_0133)^a	RPKM^b in heat stimulated samples	Fold increase with heat stimulation	Notes
72771.1	442	17.4	RPKM_HS suggest insufficient dynamic range
72879.1	454	33.4	Primer set designed: V-2879
73344.1	3,224	91.8	No exon/exon junction for cDNA-specific primer
73985.1	262	13.7	Primer set designed: V-3985
73155.1	1,040	10.9	Low complexity around exon/exon junction prevented primer design
76904.1	114	28.7	RPKM_HS suggest insufficient dynamic range
77295.1	571	13.5	No exon/exon junction for cDNA-specific primer
78079.1	442	21.4	No exon/exon junction for cDNA-specific primer
79639.1	496	84.1	Primer set designed: V-9639
80648.1	189	51.5	RPKM_HS suggest insufficient dynamic range; no exon/exon junction
78585.1	110	2.5	Similar fold increase at 21, 27, and 34 days (see Fig. 2) Primer designed: 8585_2
^aOnly the last six digits of accession numbers are shown in the table, leader characters are shown in column header; reference sequences were from E. tenella Houghton strain; accession #PRJNA263385 ^bReads per kilobase per million mapped reads (RPKM) values were calculated using the total number of reads mapped to the reference sequences (320,380 for the heat stimulated subsample and 328,718 for steady state)

6.4.3 Time Point Infection Trial: Fecundity

Live infection trials were conducted to allow the use of fecundity as a proxy for viability of aged oocysts, providing a point against which the magnitude of increase in specific viability assay targets could be compared. Live infection trial data were variable (Supplementary File 5). A dose size of 100 oocysts per bird was used at the first two time points as it was expected to be low enough to avoid the “crowding effect” (see Williams 2001), and high enough to avoid sampling error. A dose size of 500 oocysts per bird was used in only one cage as a safeguard for producing sufficient oocysts for the subsequent time point. These doses did not generate sufficient data to make conclusions regarding the viability of specific oocyst samples. The results of infection trials are summarized in Fig. 3.

Lot 1 oocysts

At 68 elapsed days, there was a statistically significant difference (determined within Excel v. 2402; Two-sample t-test assuming equal variances) in fecundity of oocysts stored at 21^oC versus 4^oC in infections established with 100 oocysts (M = 93,448 and 168,200, respectively; t(4) = -2.83, p = .024). At day 131 this difference was not significant (M = 352 and 278, respectively; t(4) = 0.372 p = .718). Data were insufficient to make these comparisons for dose size = 500 at either 68 or 131 elapsed days. At 194 days, no patency was observed from administration of oocysts stored at 21^oC (regardless of dose size) and data was not sufficient to determine if the difference in fecundity of infections established with either 100 or 500 oocysts stored at 4^oC was significant (M = 15,596 and 8,839, respectively). The difference in patency between infections established with either 100 or 500 oocysts stored at 4^oC at 250 days was not significant (M = 7,132 and 8,614, respectively; t(4) = -0.40, p = .712).

Lot 2 and Lot 3 oocysts

Both lots were stored at 21^oC. At 63 days, Lot 2 oocysts had a mean fecundity of 10,416 for infections established with 100 oocysts; only one set of birds were infected with 500 oocysts, and fecundity was determined to be 1,154. At 63 days, Lot 3 oocysts established with 100 oocysts had mean fecundity of 9,976 and when established with 500 had an average fecundity of 23,440; this difference was not significant (t(2) = -0.68, p = .566). At day 119, Lot 2 oocysts produced an average of 12,377 oocysts from infections established with 100 oocysts and 4,548 for infections established with 500; this difference was not significant (t(4) = 0.632, p = .562). The difference in fecundity of infections established with 100 Lot 2 oocysts at day 63 versus day 119 was not significant (t(4) = -0.16, p = .879).

6.4.4 Time Point Infection Trial: RNA Recovery, Controls, and qPCR Performance

At the same time points at which aged oocyst infectivity was assessed via infection trials, RNA was recovered from parallel oocyst subsamples at either steady state or that had been heat-stimulated for qPCR determination of increase in abundance of putative viability targets in HS versus SS oocysts. Total amounts of RNA recovered from all oocyst time point samples ranged from 419 to 8,790 ng, with RIN values ranging from 1.6 to 6.6. Although the amount of recovered RNA varied considerably across samples, the amount of RNA recovered from SS samples ranged from 75–116% of that recovered from parallel HS samples. Recovered amounts of RNA and RNA quality metrics are reported in Supplementary File 6.

In qPCR that used luciferase cDNA as template, only the Luc-1 primer set generated a signal that resulted in C_q values below 32 (i.e. “positive”). Across all time point samples, the Luc-1 primer set produced C_q values that ranged from 16.90 to 21.11 (SD = 1.22). A negligible negative correlation (Pearson’s correlation coefficient = -0.20; Mukaka, 2012) was observed between total ng recovered RNA and the quantity of luciferase cDNA detected. Luciferase cDNA copy numbers, as calculated from C_q values, ranged from 5.36 × 10⁴ to 9.75 × 10⁵. There was a non-significant small negative correlation between total ng of recovered RNA and calculated Luc-1 copy number (r(20) = .196, p = .382).

The S1 primer set, which targeted the nuclear sequence Tn-E03-1161, generated Cq values that ranged from 20.02 to 23.49 (SD = 0.85). Copy numbers of the S1 target calculated from C_q values ranged from 7.60 × 10³ to 8.04 × 10⁴. Assuming the target for the S1 primer set (Tn-E03-1161) is present in the nuclear E. tenella genome with a CN of 10 (see Kruth, Lane, Barta 2024), the number of nuclear genome equivalents is approximately 0.19 to 1.97% of the estimated number of nuclear genomes that entered the RNA recovery protocol. There was a non-significant small negative correlation between total ng of recovered RNA and calculated Luc-1 copy number (r(20) = .196, p = .382). There was a non-significant medium negative correlation between ng of recovered RNA and S1 copy number, (r(20) = .312, p = .157).

Plasmid standards were used to assess plate-to-plate variation in primer efficiencies. Each primer set showed an average amplification efficiency (E) ranging from 98–101%. Standard deviations of efficiencies for any given set across all plates were ≤ 0.03 (Supplementary File 7). Ranges of C_q values generated with time point sample cDNA were within the linear range for all primer sets in the case of both SS and HS samples for Luc-1 and S1. For the viability qPCR primers, all C_q values reflecting HS oocysts were within the linear portion of the standard curve, which indicated high target abundance. All primer sets generated C_q values near or above the linear portion of the curve in SS samples, this indicated low target abundance (C_q values > 27.00 for CNs under ~ 276; see Supplementary File 7 and Table 2).

6.4.5 Time Point Infection Trial: Putative Viability Target Increases in Abundance in Response to Heat Stimulation

The normalized magnitude of increase of each of the prospective viability assay targets was determined to assess the suitability of viability target. Normalized fold changes for abundances of putative viability targets for each time point in Lot 1 oocysts stored at 21^oC are shown in Fig. 4a and 4b versus stored at 4^oC in Fig. 4c and 4d. Results for Lot 2 and Lot 3 are not shown. Calculated fold changes of all targets across all samples are reported in Supplementary File 7.

The magnitude of the difference in target transcript abundance in HS over SS samples was compared to numbers of oocysts shed in a series of parallel live infection trials to identify optimal viability assay targets. A strong correlation between fecundity and magnitude of increase of specific viability target abundance indicated that the qPCR assay performed at least as well as the infection trial in determining oocyst viability. The Pearson correlation between fecundity and normalized fold change of viability target candidate abundance with heat stimulation was calculated for all Lot 1 oocyst samples (reported in Table 4). Insufficient data was generated to assess correlations between qPCR target fold change and fecundity or oocyst age for Lot 2 and Lot 3 oocysts. Increase in relative abundance of targets V-2879, V-3985, and V-9639 showed significant very large positive relationships with fecundity for oocysts stored at 21^oC at both dose sizes. For oocysts stored at 4^oC, increase in relative abundance of targets V-2879, V-3985, and V-9639 showed medium to large positive relationships with fecundity for infections established with either dose size (although the magnitudes of relationship were smaller than with oocysts stored at 21^oC); only that for V-2879 with a dose size of 500 oocysts was significant. Relevant statistics are reported in Table 4.

Table 4

Correlation (r) between fecundity of Lot 1 *Eimeria tenella* oocysts and fold increase of viability assay transcriptional target abundance in response to heat stimulation.
Fecundity of oocysts	# Oocysts used to infect	V-2879	V-3985	V-9639
Stored at 21^oC	100	r(2) = .997, p = .003*	r(2) > .999, p < .001*	r(2) > .999, p < .001*
Stored at 21^oC	500	r(2) = .995, p = .005*	r(2) = .999, p < .001*	r(2) > .999, p < .001*
Stored at 4^oC	100	r(2) = .675, p = .325	r(2) = .435, p = .565	r(6) = .320, p = .680
Stored at 4^oC	500	r(2) = .953, p = .047*	r(2) = .833, p = .167	r(6) = .769, p = .232

Precise understanding of Eimeria spp. oocyst viability must be known so that optimal coccidiosis vaccine dosage may be administered (Chapman et al. 2002; Sharman et al. 2010). Live infection trials are the current gold-standard for testing oocyst viability (Long et al. 1986; Sharman et al. 2010). These trials are expensive, time-consuming, and generate data with limited precision that could increase the risk of vaccine failure or unreliable results (Jenkins et al. 2023; Bortoluzzi et al. 2018; Chapman et al. 2016; Scare et al. 2017). A viability assay such as the one demonstrated here would have value in ensuring optimal vaccine or infection dosage and could be adapted for use in assessing vaccine cycling that could allow early identification of a potential failure to be ameliorated by additional vaccine application (Snyder et al. 2021). Additionally, with many poultry research trials that use Eimeria spp. for enteric challenge, knowledge of the viability of these oocysts that are administered to the birds would improve the assessed accuracy of the challenge impact and, perhaps, negate the need for a pre-trial titration infection typically necessitated to adjust challenge dose prior to the main trial. Information garnered from application of such an assay could also be informative to the optimization of vaccine programs, husbandry practices, and oocyst storage protocols.

The groundwork for the development of a robust molecular assay for measuring viability of E. tenella oocysts is described. The assay used measurements of the increased abundance of several specific transcripts in response to heat stimulation as proxies for viability. Putative viability target abundances were measured in parallel HS and SS oocyst subsamples by qPCR, normalising C_q values to spiked-in luciferase RNA and the genomic Tn-E03-1161 marker. The most promising target, XM_01339639.1, showed a normalized fold change of over 129 in high viability HS vs SS oocysts (whereas fold changes for the other putative viability targets were below 4.87), and a strong correlation with fecundity (r(14) = .513, p = .042; calculated from infection trial data points). The viability assay concept is outlined in Fig. 5.

Transcriptome sequencing was completed for the purpose of identifying RNAs that have increased abundances after a 90-minute heat stimulation. An increase in temperature is one of the first stimuli the parasite would receive upon being ingested by the host and was therefore predicted to elicit an increase in expression of at least several genes, although the specific identities of such genes were not known before these studies. The NGS data confirmed this prediction, identifying 23 mRNAs that showed at least a five-fold increase in abundance in 42-day old HS oocysts (versus SS).

An ideal viability assay target should have both a large increase in abundance in HS samples relative to SS samples and should have sufficient absolute abundance in HS samples to provide a wide dynamic range; for example, a target that is present at a copy number of 100 in steady state samples and 1,000 in heat stimulated ones would offer greater assay dynamic range than one that increases from one to 10. Candidate targets must also contain at least one intron that can be spanned by a qPCR primer to ensure amplification of only transcriptomic targets and must have sequence characteristics that support the design of robust qPCR primers. The three mRNAs that met these criteria were: XM_013373985.1, a putative partial 60S ribosomal mRNA L19 (Reid et al. 2014); XM_013379639.1, which encoded a putative partial translationally controlled tumor protein (TCTP) mRNA (Zheng 2018); and XM_013372879.1, a putative partial mago nashi mRNA (Reid et al. 2014). A fourth target, XM_013378585.1, showed modest, but consistent increase in abundance at all time points examined, which made it potentially useful for qPCR data normalization. This transcript was identified as glyceraldehyde-3-phosphate dehydrogenase, a glycolytic enzyme also implicated in several non-metabolic functions and which has been considered a “housekeeping gene” (Jezewski et al. 2022; Wang et al. 2013).

NGS read mapping was used to determine the increase in abundance in HS versus SS samples of each of the four transcripts of interest at 21, 28, 35, and 42 days after collection (in oocysts stored at room temperature). The three viability target candidates all showed an increase in abundance in HS samples across the three-week period. This increase likely reflected the decay of total RNA that resulted from heat stimulation. The lower average RIN values observed with HS samples versus SS samples supported this hypothesis.

Increased abundance of the four targets of interest with heat simulation was assessed by qPCR at ~ nine-week intervals in oocysts stored at either room temperature or 4^oC. Parallel live infection trials were used to generate fecundity data. As observed in the preliminary NGS data, XM_013378585.1 showed minimal response to heat stimulation at all time points examined by qPCR, however a slight trend in greater magnitude of increase in abundance at later timepoints should be examined if it is to be further considered as a normalizing target. All three candidate viability targets had significant large positive relationships with fecundity for oocysts stored at room temperature (Table 4). The standout viability target was XM_013379639.1, which not only showed the greatest increase in abundance with heat stimulation, but also offered the widest dynamic range. For all three candidate viability targets, relationship with fecundity of infections resulting from oocysts stored at 4^oC was lower than those stored at 21^oC, and only one relationship was significant (Table 4). Two factors may have contributed to these lower correlations: 1) crowding effect impacting fecundity in the most viable oocysts; and 2) a greater “baseline” abundance of these transcripts in oocysts that have more recently completed sporulation and were stored at 4^oC. Higher viability oocysts were likely leading to infection fecundity that was lowered by the crowding effect (Williams 2001) – this would have been more pronounced in infections established with higher oocyst doses, and in oocysts stored at 4^oC versus those of the same age stored at room temperature due to higher viability. The baseline abundance of these putative viability targets in SS oocysts was likely greater in those stored at 4^oC at the earliest time point than in any other oocysts. Transcripts contributing to the higher baseline abundance may have been generated during sporulation and would decay over time; they would decay more quickly in oocysts stored at room temperature, meaning the “elevated baseline abundance” issue was less impactful in those stored at room temperature.

XM_013379639.1 was putatively identified to encode a partial translationally controlled tumor protein (Reid et al. 2014). The function of this protein in Eimeria spp. has not been described. In multicellular eukaryotes it is involved in regulation of growth and development and its cytoplasmic expression in T. gondii is required for timely intracellular development (Zheng 2018). The mRNA sequence is highly conserved among other coccidian species (Supplementary File 8) and could be exploited for adaptation of the assay for use with other Eimeria spp. included in live coccidiosis vaccines.

Normalization of qPCR data was achieved with two additional qPCR targets. A luciferase RNA spike in was mixed into the RNA extraction buffer and was subject to the same handling as E. tenella RNA. Luciferase RNA was quantified using the Luc-1 primer set, which allowed for normalization for differing RNA recovery and reverse transcription efficiencies. The S1 primer set targeted the genomic Tn-E03-1161 sequence. By omitting a DNase treatment step following RNA isolation, carry through DNA could be quantified, allowing for normalization for the number of oocysts that went into the assay and for varying efficiencies of oocyst disruption. The average fold change in abundance of all four qPCR transcriptional targets in non-viable oocysts with heat stimulation was 1.07 (SD = 0.13), which indicated virtually no change in abundance of these targets in dead oocysts (despite varying efficiencies of RNA recovery). The lack of changes in target abundance in non-viable oocysts suggested that the qPCR data normalization strategy was appropriate. Similar normalization strategies have been validated in other challenging systems (Atwan 2020; Bower et al. 2007).

Calculated copy numbers of luciferase cDNA per qPCR well (based on absolute interpretation of C_q values) suggested a low overall efficiency of RNA recovery and reverse transcription (0.03–0.61%). Although comparable efficiencies have been reported for commercial kits (Levesque-Sergerie et al. 2007), the challenging nature of recovering RNA from oocysts and the thrifty biology of sporulated oocysts likely contribute to low overall efficiency. Recovered RNA also showed overall low integrity, as reflected by RIN values. It is possible that the RNA integrity number may not be an appropriate measure of actual RNA quality in apicomplexan parasites, given their non-canonical rRNAs and fragmented mitochondrial rRNAs (Kruth, Lane, Barta 2024; Feagin et al. 2012). Regardless, the quality of recovered RNA was likely moderate, due to damage incurred during the violent RNA recovery process and reflecting the hypobiotic nature of the oocysts. Importantly, the low abundance and apparent low quality of recovered RNA did not prevent the quantification of the targets of interest by qPCR.

A “crowding effect”, in which an inverse relationship between infectious dose and parasite fecundity, has been well-documented with Eimeria spp. (Brackett and Bliznick 1952; Doran and Augustine 1973; Horton-Smith 1947; Johnston et al. 2001). Limited availability of host cells has been suggested as the primary underlying factor for the crowding effect; however, the relatively low-infectious doses at which the effect is observed indicate that more factors may be at play (Brackett and Bliznick 1952; Johnston et al. 2001). A 2001 study determined the dose at which maximum fecundity would be observed in seven-day old male broilers infected with high-viability E. tenella oocysts was a mere 72 oocysts (Williams 2001). Signs of such crowding effect were present in the current data, with no infection established with 500 oocysts having statistically equivalent fecundity to parallel infections established with 100 oocysts from the same stock (Supplementary File 4). As oocyst viability began to wane and effective dose decreased, the impacts of crowding on fecundity would have shifted, further obfuscating the data. Improving infection trial protocols to address the crowding effect would likely generate fecundity data that correlates even more strongly with the magnitude of increase of the most promising assay target, XM_013379639.1. Storage of oocysts at 21^oC (room temperature) was an effective strategy for the acceleration of rate of viability loss (versus standard conditions; 4^oC). Similar storage conditions should be used going forward. The use of even warmer conditions could also be considered as an additional strategy for further accelerating rate of viability loss for the purpose of ongoing assay development.

Transcript XM_013379639.1 is a promising target for the molecular viability assay described here. The overall assay concept, including strategies for oocyst disruption and data normalization are supported, with the presented results aligning with what is known of the biology of the parasite. Ongoing development of the assay should seek to determine where in the ~ 35 to ~ 77-day range changes in abundance of the viability target (XM_013379639.1) begin to reflect viability. Measurements of abundance of putative viability targets during and following the completion of sporulation could be used to determine if transcripts generated during sporulation contribute to higher baseline target abundance in more recently sporulated (and refrigerated) samples. Additional spike-in RNA and qPCR could help identify specific protocol steps with greatest impacts to efficiency for the improvement of assay efficiency. Finally, the use of hydrolysis-probe based qPCR chemistry (versus the SYBR chemistry used here) should be considered. This would allow for the V-9639 viability primers to be used in the same quantitation reaction as the reference target primers, reducing the number of qPCR wells required to run the assay from 24 to six (assuming three qPCR technical replicates are run for each of the SS and HS samples). This would improve accuracy by limiting technical variation, reduce the amount of parasite material needed to run the assay, and reduce the cost of consumables.

Infection trial fecundity data will always be subject to wide variation. This natural variability conveniently highlights the need for a better strategy for assessing oocyst viability, but also makes it nearly impossible to unequivocally demonstrate the accuracy of such an assay. The fecundity data was of poor quality primarily due to inappropriate experimental group sizes. Future infection trials for examination of fecundity would benefit from several modifications, including using individual birds instead of small groups for infection trial data points, and infecting more animals per oocyst subsample (Nolan et al. 2015). Using a wider range of dose sizes (e.g., 20, 50, 100, and 200) would allow determination of “peak fecundity”, which would be a more accurate representation of viability than would fecundity from any one dose. Synchronization of infections could be achieved by feed withdrawal for 12 hours prior to administering oocysts with return of feed shortly after (see Shamshirgaran et al. 2023). An additional mode of assessment of oocyst viability could be added to generate further support of results generated by infection trials, such as the use of qPCR to quantify merogonic stages in tissue samples at specific infection time points (Nolan et al. 2015). Finally, conducting a single time-point infection trial in which high viability (freshly sporulated) and non-viable oocysts are mixed to generate samples with specific known percentage viability; this could aid in improving quality of fecundity data while minimizing the amount of time required for repetitive infection trials.

This research developed and assessed a “beta version” of a proposed qPCR-based assay for the determination of the viability of E. tenella oocysts. The assay used the increase in abundance of several mRNAs with heat stimulation as proxies for viability, with XM_01339639.1 identified as the best-suited target. Fecundity established via live infection trials was used as a second proxy, to demonstrate the accuracy of the first.

By way of assay development, the work presented in this study had several tangential beneficial outcomes: 1) identification of a potentially useful gene (XM_013378585.1) for normalization of transcriptome and gene expression data in E. tenella (and possibly other coccidia); and 2) the generation of several NGS data sets that could help to study specific genes and pathways that are important in the early stages of the endogenous lifecycle as well as those that are expressed in hypobiotic oocysts.

A major hurdle to advance this assay will be the generation of robust fecundity data to confirm assay accuracy – this will require numerous large scale infection trials over several courses of ageing of oocysts to the point of viability loss. Additionally, to optimize the assay, more work is required on the qPCR strategy used, including adaptation for use with hydrolysis-probe based qPCR chemistry (versus the SYBR chemistry used in the current version). Ongoing assay development should aim to reduce the amount of parasite material needed, reduce the time and consumables needed to run the assay, and reduce technical variation.

The work described here forms the groundwork for a viability assay that can help to make effective and efficient immunological control of coccidiosis a reality. Since the assay target, XM_01339639.1, is highly conserved in Eimeria spp. infecting poultry, an optimized version of this assay could be further adapted for use with other Eimeria spp. that are commercially relevant. Such an assay would ensure optimal vaccine efficacy, would extend vaccine shelf life by offering a cost-effective alternative to the timeconsuming live-infection trials currently used in viability determination.

Acknowledgments

Thank you to Julie Cobean, Larsen Iorgovitz, Dr. Cassia Michel, Neil Morley, Jessica Rotolo, Dr. Ryan Snyder, and Fiorella Vialard for their provided technical assistance in infection trials and early assay development. The work presented in this manuscript is adapted from the doctoral dissertation of PSK (see Kruth, 2024). Drs. Rebecca Shapiro, Kayla Price, and Billy Hargis are thanked for their editorial contributions. Staff at the Central Animal Facilities Isolation Unit, University of Guelph provided additional assistance with animal welfare and health monitoring.

Ethics Approval

All animal usage was in compliance with regulations outlined by the Canadian Council on Animal Care (2017) and was reviewed and approved by the Animal Care Committee of the University of Guelph, Canada (Animal Use Protocol #3414). Consent to participate and consent to publish: not applicable.

Competing Interests

The authors have no competing interests to declare.

Author contributions

All authors contributed to the study conception and design. Concept development was by John R Barta, Jennifer Brisbin, and Perryn S Kruth. Material preparation and infection trial data collection were performed by John R Barta, Alexandre N Léveillé, Julia Whale, and Perryn S Kruth. Laboratory procedures, including, but not limited to: nucleic acid collection, molecular cloning, and qPCR was performed by Perryn S Kruth. NextGen RNA Seq data processing and assembly was performed by John R Barta and Perryn S Kruth. The manuscript was written by Perryn S Kruth (based on their dissertation), with editorial contributions by all authors.

Funding

This research was supported by: The Natural Sciences and Engineering Research Council of Canada (NSERC, grant to JRB #400566); The Ontario Ministry of Agriculture Food and Rural Affairs (OMAFRA) Ontario Agri-Food Innovation Alliance Tier 2 Research Grant (to JRB, UG-T2-2021-102010); Ontario Genomics, the Agricultural Adaptation Council, and Genome Canada provided funding (via Ontario Regional Priorities Partnership Program) to John R Barta, Perryn S Kruth, and Jennifer Brisbin. Perryn S Kruth was supported by the NSERC Postgraduate Scholarships – Doctoral (PGS-D) program, and the Ontario Veterinary College (Graduate Scholarship).

Data availability

Raw NGS RNA-Seq data are available via Mendeley Data for 21 day-old sporulated oocysts (Kruth, Barta 2024a), 28-day old sporulated oocysts (Kruth, Barta 2024b), 35-day old sporulated oocysts (Kruth, Barta 2024c), and 42-day old sporulated oocysts (Kruth, Barta 2024d).

Clinical Trial Number:

Not applicable.

Abbas RZ, Iqbal Z, Blake D, Khan MN, Saleemi MK (2011) Anticoccidial drug resistance in fowl coccidia: The state of play revisited. J World's Poult Sci 67:337–349. https://doi.org/10.1017/S004393391100033X
Alloco JT, Profous-Juchelka H, Myers RW, Nare B, Schmats DM (1999) Biosynthesis and catabolism of mannitol is developmentally regulated in the protozoan parasite Eimeria tenella. J Parasitol 85:167–173
Atwan ZW (2020) GAPDH spike RNA as an alternative for housekeeping genes in relative gene expression assay using real-time PCR. Bull Natl Res Cent 44:1–8. https://doi.org/10.1186/s42269-020-00284-1
Augustine PC (1980) Effects of storage time and temperature on amylopectin levels and oocyst production of Eimeria meleagrimitis oocysts. Parasitology 81:519–524. https://doi.org/10.1017/S0031182000061904
Belli SI, Smith NC, Ferguson DJP (2006) The coccidian oocyst: A tough nut to crack! Trends Parasitol 22:416–423. https://doi.org/10.1016/j.pt.2006.07.004
Blake DP, Hesketh P, Archer A, Carroll F, Shirley MW, Smith AL (2005) The influence of immunizing dose size and schedule on immunity to subsequent challenge with antigenically distinct strains of Eimeria maxima. Avian Pathol 34:489–494. https://doi.org/10.1080/03079450500368292
Blake DP, Knox J, Dehaeck B, Huntington B, Rathinam T, Ravipati V, Ayoade S, Gilbert W, Adebambo AO, Jatau ID, Raman M, Parker D, Rushton J, Tomley FM (2020) Re-calculating the cost of coccidiosis in chickens. Vet Res 51:1–14. https://doi.org/10.1186/s13567-020-00837-2
Bortoluzzi C, Paras KL, Applegate TJ, Verocai GG (2018) Comparison between McMaster and Mini-FLOTAC methods for the enumeration of Eimeria maxima oocysts in poultry excreta. Vet Parasitol 254:21–25. https://doi.org/10.1016/j.vetpar.2018.02.039
Bower NI, Moser RJ, Hill JR, Lehnert SA (2007) Universal reference method for real-time PCR gene expression analysis of preimplantation embryos. Biotechniques 42:199–206. https://doi.org/10.2144/000112314
Brackett S, Bliznick A (1952) The reproductive potential of five species of coccidia of the chicken as demonstrated by oocyst production. J Parasitol 38:133–139
Bustin SA (2000) Absolute quantification of mrna using real-time reverse transcription polymerase chain reaction assays. J Mol Endocrinol 25:169–193. https://doi.org/10.1677/jme.0.0250169
Canadian Council on Animal Care (2020) Guide to the care and use of experimental animals, Volume 1, 2nd edn. Available at: https://ccac.ca/Documents/Standards/Guidelines/Experimental_Animals_Vol1.pdf
Chapman HD, Barta JR, Blake D, Gruber A, Jenkins M, Smith NC, Suo X, Tomley FM (2013) A selective review of advances in coccidiosis research. Adv Parasitol 83:93–171. https://doi.org/10.1016/B978-0-12-407705-8.00002-1
Chapman HD, Barta J, Hafeez MA, Matsler P, Rathinam T, Raccoursier M (2016) The epizootiology of Eimeria infections in commercial broiler chickens where anticoccidial drug programs were employed in six successive flocks to control coccidiosis. Poult Sci 95:1774–1778. https://doi.org/10.3382/ps/pew091
Chapman HD, Cherry TE, Danforth HD, Richards G, Shirley MW, Williams RB (2002) Sustainable coccidiosis control in poultry production: The role of live vaccines. Int J Parasitol 32:617–629. https://doi.org/10.1016/S0020-7519(01)00362-9
Chapman HD, Jeffers TK (2014) Vaccination of chickens against coccidiosis ameliorates drug resistance in commercial poultry production. Int J Parasitol: Drugs Drug Resist 4:214–217. https://doi.org/10.1016/j.ijpddr.2014.10.002
Dalloul RA, Lillehoj HS (2006) Poultry coccidiosis: Recent advancements in control measures and vaccine development. Expert Rev Vaccines 5:143–163. https://doi.org/10.1586/14760584.5.1.143
Dibner J, Kitchell ML, Pfannenstiel MA, Knight C (2003) Importance of oocyst viability testing for coccidiosis vaccines. World Poult 17:11–12
Doran DJ, Augustine PC (1973) Comparative development of Eimeria tenella from sporozoites to oocysts in primary kidney cell cultures from gallinaceous birds. J Protozool 20:658–661
Feagin JE, Isabel M, Lee JC, Coe KJ, Sands BH (2012) The fragmented mitochondrial ribosomal RNAs of Plasmodium falciparum. PLoS One. 7:e38320. https://doi.org/10.1371/journal.pone.0038320
Hay FR, Whitehouse KJ (2017) Rethinking the approach to viability monitoring in seed genebanks. Conserv Physiol 5:1–13. https://doi.org/10.1093/conphys/cox009
Horton-Smith C (1947) Coccidiosis, some factors influencing its epidemiology. Vet Rec 59:645
Jenkins MC, O’Brien CN, Parker C, Tucker M, Khan A (2023) Relationship between Eimeria oocyst infectivity for chickens and in vitro excystation of E. acervulina, E. maxima, and E. tenella oocyst during long-term storage. Poult Sci 102:103–133. https://doi.org/10.1016/j.psj.2023.103133
Jenkins MC, Parker C, O’Brien C, Miska K, Fetterer R (2013) Differing susceptibilities of Eimeria acervulina, Eimeria maxima, and Eimeria tenella oocysts to desiccation. J Parasitol 99:899–902. https://doi.org/10.1645/13-192.1
Jezewski AJ, Guggisberg AM, Hodge DM, Ghebremichael N, John GN, McLellan LK, John ARO (2022) GAPDH mediates drug resistance and metabolism in Plasmodium falciparum malaria parasites. PLoS Pathog 18:1–21. https://doi.org/10.1371/journal.ppat.1010803
Johnston WT, Shirley MW, Smith AL, Gravenor MB (2001) Modelling host cell availability and the crowding effect in Eimeria infections. Int J Parasitol 31:1070–1081. https://doi.org/10.1016/S0020-7519(01)00234-X
Jordan A, Caldwell DJ, Klein J, Coppedge J, Pohl S, Fitz-Coy S, Lee JT (2011) Eimeria tenella oocyst shedding and output in cecal or fecal contents following experimental challenge in broilers. Poul Sci 90:990–995. https://doi.org/10.3382/ps.2010-01228
Kim JH, Seo S, Kim CH, Kim JW, Lee BB, Lee GI, Shin HS, Kim MC, Kil DY (2013) Effect of dietary supplementation of crude glycerol or tallow on intestinal transit time and utilization of energy and nutrients in diets fed to broiler chickens. Livest Sci 154:165–168. https://doi.org/10.1016/j.livsci.2013.03.005
Kruth PS, Lane T, and Barta JR (2024). Organellar genome dynamics of exogenous stages of Eimeria tenella. Parasit Vectors - In submission (Ref: Submission ID 28281cb7-af8d-4019-93c9-11e0d8c9d143)
Kruth PS (2024) Molecular Investigation of Exogenous Stages of Eimeria tenella: Expression of fragmented mitochondrial rDNA, organellar genome dynamics, and development of a transcriptional activity-based assay for measuring oocyst viability. Dissertation, University of Guelph
Kruth PS, Barta JR (2024a) Eimeria tenella 21 day old sporozoites - coding transcriptome. Mendeley Data V1. doi: 10.17632/7fjtft7dzn.1
Kruth PS, Barta JR (2024b) Eimeria tenella 28 day old sporozoites - coding transcriptome. Mendeley Data V1. doi: 10.17632/5h8ksc3xpd.1
Kruth PS, Barta JR (2024c) Eimeria tenella 35 day old sporozoites - coding transcriptome. Mendeley Data V1. doi: 10.17632/gsm7sd9gh7.1
Kruth PS, Barta JR (2024d) Eimeria tenella 42 day old sporozoites - coding transcriptome. Mendeley Data V1. doi: 10.17632/7m26pw6wvk.1
Long PL, Johnson J, McKenzie ME, Perry E, Crane MSJ, Murray PK (1986) Immunisation of young broiler chickens with low level infections of Eimeria tenella, E. acervulina or E. maxima. Avian Pathol 15:271–278. https://doi.org/10.1080/03079458608436287
López-Osorio S, Chaparro-Gutiérrez JJ, Gómez-Osorio LM (2020) Overview of poultry Eimeria life cycle and host-parasite interactions. Front Vet Sci 7:1–8. https://doi.org/10.3389/fvets.2020.00384
Mai K, Sharman PA, Walker RA, Katrib M, de Souza D, McConville MJ, Wallach MG, Belli SI, Ferguson DJP, Smith NC (2009) Oocyst wall formation and composition in coccidian parasites. Mem Inst Oswaldo Cruz 104:281–289. https://doi.org/10.1590/S0074-02762009000200022
Markham NR, Zuker M (2008) UNAFold. In Keith JM (ed.), Bioinformatics: Methods in molecular biology. Humana Press, Totowa, New Jersey. pp 3–31. doi:10.1007/978-1-60327-429-6_1
Nolan MJ, Tomley FM, Kaiser P, Blake DP (2015) Quantitative real-time PCR (qPCR) for Eimeria tenella replication - Implications for experimental refinement and animal welfare. Parasitol Int 64:464–470. https://doi.org/10.1016/j.parint.2015.06.010
Paganini F (2005) Alternatives to drugs in poultry feed and their impact on food safety. XIth European Symposium on the Quality of Eggs and Egg Products. [Conference paper]. Available at https://www.cabidigitallibrary.org/doi/full/10.5555/20073161041
Parry S, Barratt MEJ, Jones S, McKee S, Murray JD (1992) Modelling coccidial infection in chickens: Emphasis on vaccination by in-feed delivery of oocysts. J Theor Biol 157:407–425. https://doi.org/10.1016/S0022-5193(05)80661-7
Penfield S (2017) Seed dormancy and germination. Curr Biol 27:R874-R878. https://doi.org/10.1016/j.cub.2017.05.050
Perkins FO, Barta JR, Clopton RE, Peirce MA, Upton SJ (2000) Phylum Apicomplexa. In Lee J, Leedale G, Bradbury P (eds.) An illustrated guide to the protozoa. Allen Press, Inc., Lawrence, Kansas, pp 190–201
Price KR (2012) Use of live vaccines for coccidiosis control in replacement layer pullets. J Appl Poult Res 21:679–692. https://doi.org/10.3382/japr.2011-00486
Price KR (2014) Live Eimeria vaccine use in commercial pullet rearing: Environmental influences on vaccination success. Dissertation, University of Guelph
Reid AJ, Blake DP, Ansari HR, Billington K, Browne HP, Bryant J, et al. (2014) Genomic analysis of the causative agents of coccidiosis in domestic chickens. Genome Res 24:1676–1685. https://doi.org/10.1101/gr.168955.113
Ryley JF, Bentley M, Manners DJ, Roger JS (1969) Amylopectin, the storage polysaccharide of the coccidia Eimeria brunetti and E. tenella. J Parasitol 55:839–845
Scare JA, Slusarewicz P, Noel ML, Wielgus KM, Nielsen MK (2017) Evaluation of accuracy and precision of a smartphone based automated parasite egg counting system in comparison to the McMaster and Mini-FLOTAC methods. Vet Parasitol 247:85–92. https://doi.org/10.1016/j.vetpar.2017.10.005
Schaap D, Arts G, Van Poppel NFJ, Vermeulen AN (2005) De novo ribosome biosynthesis is transcriptionally regulated in Eimeria tenella, dependent on its life cycle stage. Mol Biochem Parasitol 139:239–248. https://doi.org/10.1016/j.molbiopara.2004.11.011
Shamshirgaran MA, Golchin M, Salehi M, Kheirandish R (2023) Evaluation the efficacy of oral immunization of broiler chickens with a recombinant Lactobacillus casei vaccine vector expressing the carboxy-terminal fragment of α-toxin from Clostridium perfringens. BMC Vet Res 19:1–9. https://doi.org/10.1186/s12917-023-03566-8
Sharman PA, Smith NC, Wallach MG, Katrib M (2010) Chasing the golden egg: Vaccination against poultry coccidiosis. Parasit Immunol 32:590–598. https://doi.org/10.1111/j.1365-3024.2010.01209.x
Snyder RP, Guerin MT, Hargis BM, Imai R, Kruth PS, Page G, Rejman E, Barta JR (2021) Exploiting digital droplet PCR and Next Generation Sequencing technologies to determine the relative abundance of individual Eimeria species in a DNA sample. Vet Parasitol 296:109443. https://doi.org/10.1016/j.vetpar.2021.109443
Sokale AO, Williams CJ, Hoerr FJ, Collins KEC, Peebles ED (2021) Effects of administration of an in ovo coccidiosis vaccine at different embryonic ages on vaccine cycling and performance of broiler chickens. Poult Sci 100:100914. https://doi.org/10.1016/j.psj.2020.11.078
Stotish RL, Wang CC, Meyenhofer M (1978) Structure and composition of the oocyst wall of Eimeria tenella. J Parasitol 64:1074–1081
Taylor SC, Nadeau K, Abbasi M, Lachance C, Nguyen M, Fenrich J (2019) The ultimate qPCR experiment: Producing publication quality, reproducible data the first time. Trends Biotechnol 37:761–774. https://doi.org/10.1016/j.tibtech.2018.12.002
Tewari AK, Maharan B (2011) Control of poultry coccidiosis: Changing trends. J Parasit Dis 35:10–17. https://doi.org/10.1007/s12639-011-0034-7
Thornton B, Basu C (2015) Rapid and simple method of qPCR primer design. Methods Mol Biol 1275:173–179. https://doi.org/10.1007/978-1-4939-2365-6_13
Wang C, Han C, Li T, Yang D, Shen X, Fan Y, Xu Y, Zheng W, Fei C, Zhang L, Xue F (2013) Nuclear translocation and accumulation of glyceraldehyde-3-phosphate dehydrogenase involved in diclazuril-induced apoptosis in Eimeria tenella. Vet Res 44:1–9. https://doi.org/10.1186/1297-9716-44-29
Waterworth WM, Bray CM, West CE (2015) The importance of safeguarding genome integrity in germination and seed longevity. J Exp Bot 66:3549–3558. https://doi.org/10.1093/jxb/erv080
Waterworth WM, Bray CM, West CE (2019) Seeds and the art of genome maintenance. Front Plant Sci 10:1–11. https://doi.org/10.3389/fpls.2019.00706
Williams RB (2001) Quantification of the crowding effect during infections with the seven Eimeria species of the domesticated fowl: Its importance for experimental designs and the production of oocyst stocks. Int J Parasitol 31:1056–1069. https://doi.org/10.1016/S0020-7519(01)00235-1
Wolny E, Betekhtin A, Rojek M, Braszewska-Zalewska A, Lusinska J, Hasterok R (2018) Germination and the early stages of seedling development in Brachypodium distachyon. Int J Mol Sci 19:2916. https://doi.org/10.3390/ijms19102916
Zheng J, Chen Y, Li Z, Cao S, Zhang Z, Jia H (2018) Translationally controlled tumor protein is required for the fast growth of Toxoplasma gondii and maintenance of its intracellular development. FASEB J 32:906–919. http://doi.org/10.1096/fj.201700994R

No competing interests reported.

Download PDF

Editorial decision: Revision requested
08 Oct, 2024
Reviews received at journal
29 Sep, 2024
Reviewers agreed at journal
23 Sep, 2024
Reviewers agreed at journal
21 Sep, 2024
Reviewers agreed at journal
16 Sep, 2024
Reviewers agreed at journal
16 Sep, 2024
Reviewers agreed at journal
16 Sep, 2024
Reviewers agreed at journal
16 Sep, 2024
Reviewers invited by journal
15 Sep, 2024
Editor assigned by journal
09 Sep, 2024
Submission checks completed at journal
08 Sep, 2024
First submitted to journal
02 Sep, 2024

You are reading this latest preprint version

Development of a Molecular Assay for the Determination of Eimeria tenella Oocyst Viability

Status:

Version 1

Abstract

Figures

Introduction

Methods

qPCR Primer Design

Results

Discussion

Conclusions

Declarations

Acknowledgments

Ethics Approval

Competing Interests

Author contributions

Funding

Data availability

Clinical Trial Number:

References

Additional Declarations

Supplementary Files

Status:

Version 1