# Disclosing respiratory coinfections: a broad-range panel assay for avian respiratory pathogens on a nanofluidic PCR platform.

Guillaume Croville, Charlotte Foret, Pauline Heuillard, Alexis Senet, Mattias Delpont, Mohammed Mouahid, Mariette Ducatez, Faouzi Kichou, Jean-Luc Guerin

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Guillaume Croville, Charlotte Foret, Pauline Heuillard, Alexis Senet, Mattias Delpont, et al. Disclosing respiratory coinfections: a broad-range panel assay for avian respiratory pathogens on a nanofluidic PCR platform. Avian Pathology, 2018, pp.1-8. 10.1080/03079457.2018.1430891. hal-02627147

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# Disclosing respiratory coinfections: a broad-range panel assay for avian respiratory pathogens on a nanofluidic PCR platform

Guillaume Croville, Charlotte Foret, Pauline Heuillard, Alexis Senet, Mattias Delpont, Mohammed Mouahid, Mariette F. Ducatez, Faouzi Kichou & Jean-Luc Guerin

To cite this article: Guillaume Croville, Charlotte Foret, Pauline Heuillard, Alexis Senet, Mattias Delpont, Mohammed Mouahid, Mariette F. Ducatez, Faouzi Kichou & Jean-Luc Guerin (2018): Disclosing respiratory coinfections: a broad-range panel assay for avian respiratory pathogens on a nanofluidic PCR platform, Avian Pathology, DOI: 10.1080/03079457.2018.1430891

To link to this article: https://doi.org/10.1080/03079457.2018.1430891

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# Disclosing respiratory coinfections: a broad-range panel assay for avian respiratory pathogens on a nanofluidic PCR platform

Guillaume Crovilleª, Charlotte Foretª, Pauline Heuillardª, Alexis Senetª, Mattias Delpontª, Mohammed Mouahidᵇ, Mariette F. Ducatezª, Faouzi Kichouᶜ and Jean-Luc Guerinª

ªIHAP, Université de Toulouse, ENVT, INRA, Toulouse, France; ᵇVeterinary Practice, Temara, Morocco; ᶜInstitut Agronomique et Vétérinaire Hassan II, Rabat, Morocco

## ABSTRACT

Respiratory syndromes (RS) are among the most significant pathological conditions in edible birds and are caused by complex coactions of pathogens and environmental factors. In poultry, low pathogenic avian influenza A viruses, metapneumoviruses, infectious bronchitis virus, infectious laryngotracheitis virus, *Mycoplasma* spp. *Escherichia coli* and/or *Ornithobacterium rhinotracheale* in turkeys are considered as key co-infectious agents of RS. *Aspergillus* sp., *Pasteurella multocida*, *Avibacterium paragallinarum* or *Chlamydia psittaci* may also be involved in respiratory outbreaks. An innovative quantitative PCR method, based on a nanofluidic technology, has the ability to screen up to 96 samples with 96 pathogen-specific PCR primers, at the same time, in one run of real-time quantitative PCR. This platform was used for the screening of avian respiratory pathogens: 15 respiratory agents, including viruses, bacteria and fungi potentially associated with respiratory infections of poultry, were targeted. Primers were designed and validated for SYBR green real-time quantitative PCR and subsequently validated on the Biomark high throughput PCR nanofluidic platform (Fluidigm®, San Francisco, CA, USA). As a clinical assessment, tracheal swabs were sampled from turkeys showing RS and submitted to this panel assay. Beside systematic detection of *E. coli*, avian metapneumovirus, *Mycoplasma gallisepticum* and *Mycoplasma synoviae* were frequently detected, with distinctive coinfection patterns between French and Moroccan flocks. This proof-of-concept study illustrates the potential of such panel assays for unveiling respiratory coinfection profiles in poultry.

## ARTICLE HISTORY

Received 23 October 2017
Accepted 14 January 2018

## KEYWORDS

Avian respiratory pathogens;
coinfections; high
throughput PCR; microfluidic
PCR

## Research highlights

* A panel assay targeting all significant poultry respiratory agents was developed.

* This panel assay is based on a high throughput nanofluidic PCR platform.

* Clinical samples from turkey flocks facing acute respiratory signs were screened.

* Viral and/or bacterial coinfections could be identified in all submitted flocks.

## Introduction

Respiratory syndromes (RS) are among the most frequent and significant pathological conditions in farm birds. In poultry species, they are also associated with egg-drop syndromes in layers and breeders, resulting in losses in production of both eggs and day-old-chicks. The control of RS relies on a massive metapathologic use of antibiotics, most of the time without any sound knowledge of pathogens involved (Hughes et al., 2008; Agunos et al., 2013). Routine diagnostic

procedures are based on classical bacteriology and molecular tests targeting a very limited number of viruses and mycoplasmas. A key challenge in the diagnosis and management of respiratory infections is disconnecting coinfections. So far, very few panel assays are available in veterinary medicine (Anderson et al., 2011; Lung et al., 2017). In human medicine, the increasing availability of panel assays has dramatically changed the knowledge of respiratory infectious agents, and subsequently may impact their therapeutic management with rational bases of antibiotic prescription. These panel assays are combinations of PCR reactions assembled within one single assay (implemented in one or several reaction wells), enabling the screening of a set of relevant pathogens.

The inherent limitations of culture-based detection methods have resulted in development of innovative pathogen detection and quantification methods. The objectives of these platforms are to speed up the detection process and to improve accuracy. The recent devices are nucleic-acid-based assays allowing amplification and detection of pathogens, which reduces detection times and biological sample requirements.

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In field samples, difficulties come from pathogen concentration which can be low, a large number of other interfering species and inhibitor factors complicating pathogen identification and quantification.

The identification of pathogens through genetic analysis techniques is becoming more conventional by the use of real-time quantitative PCR (RT-qPCR). To bypass low concentrations, amplification performed during RT-qPCR allows detection of a low number of DNA copies.

Miniaturizing the PCR process induces a reduction in sample and reagent volumes required and allows processing thousands of reactions in one PCR run. High throughput quantitative PCR becomes, therefore, affordable and conceivable as a routine test.

A commercial microfluidic-based PCR device, Biomark™ 48.48 or 96.96 Dynamic Array, has been developed by the Fluidigm Corporation (San Francisco, CA, USA). This platform has the specific capability to screen up to 96 samples with 96 pathogen-specific PCR primers on a 96.96 chip (9216 reactions) or to screen 48 samples with 48 pathogen-specific PCR primers on a 48.48 chip (2304 reactions), at the same time, in one RT-qPCR run. The main advantage of this microfluidic chip is the large number of reactions that can be run in parallel and the fact that this is not a multiplex test, which means that interference between PCR primers does not occur.

In this paper, we developed a panel assay for 15 avian respiratory pathogens on the Biomark platform. As a proof-of-concept, we used this panel assay to screen clinical samples from turkey flocks and evidenced unprecedented comprehensible pathogen profiles.

# Materials and methods

## PCR development and PCR primer validation

Vaccines or reference strains of viruses and bacteria were used as positive controls (Supplementary Table 2).

DNA and RNA were extracted using the Nucleospin RNA virus kit (Macherey-Nagel, Düren, Germany), as previously done by Cheval *et al.* (2011). RNA and DNA were extracted following the manufacturer's instructions and were then eluted in 50 µl RNase-free water before storage at -80°C, as recommended by the manufacturer's instructions; simultaneous viral RNA/DNA isolation can be performed by addition of Proteinase K solution.

## cDNA synthesis

For RNA viruses, cDNA synthesis was performed by use of RevertAid Reverse Transcriptase kit (Life Technologies, Carlsbad, CA, USA). Ten microlitres of RNA were mixed with 0.2 µg of random hexamer primers and the volume was completed to 11.5 µl with distilled water before a 5-min incubation step at 65°C. Then, on

ice, 4 µl of 5X reaction buffer was added to the mixture at the same time as 20 units RiboLock RNase Inhibitor, 2 µl of 10 mM dNTP Mix and 200 units RevertAid H Minus Reverse Transcriptase. The reverse transcription reaction was performed at 42°C for 60 min and terminated by heating at 70°C for 10 min. cDNA was stored at -20°C.

## RT-qPCR primer design and selection

The sets of primers were based on in-house designed primers or selected primers from literature. Primer design was done following these criteria: (i) 60°C melting temperature (Tm), (ii) primer length 15-20 nucleotides, (iii) 100-300 nucleotides amplicon size and (iv) guanine and cytosine content between 40% and 60%.

Primers selected from literature were chosen if these criteria were respected. The 60°C Tm was a necessary condition from the Biomark platform (whose Tm was set at 60°C).

## Primer validation

An *in silico* analysis was performed using BLASTN in order to check the specificity of the primer sets: a 100% identity towards the target and the expect value close to zero were expected.

Primers were then validated on a lightCycler 480 system (Roche, Basel, Switzerland), by using iTaq SYBR green kit (Biorad, Hercules, CA) and following the manufacturer's instructions. For each primer pair, five replicates were implemented in order to strengthen the validation. The amplification program consisted of a first 10 min step at 95°C followed by 45 cycles, including one 95°C step for 15 s and one 60°C step for 40 s. The quantification cycles (Cq) for the five replicates were expected to be in a short range of 0.2 Cq. Fluorescence curves and melting peaks were first analysed and the PCR products were loaded on an agarose gel, if necessary. Cross-reaction was intensively checked, with each primer pair being tested on all positive controls.

## Standard plasmid preparation

Plasmids used as quantification standards were prepared using the commercial kit Strataclone PCR Cloning kit (Agilent, Santa Clara, CA). Each validated PCR test led to the production of a plasmid to obtain standard controls directly from the PCR products. Colonies harbouring plasmids were picked and incubated at 37°C in 5 ml LB medium-Ampicillin (100 µg/ml) during 12-16 h before plasmid extraction by use of Nucleospin plasmid Quickpure kit (Macherey-Nagel, Düren, Germany). Quantification of plasmids was done with the Qubit fluorometer and the dsDNA broad range assay kit (Thermo Fisher Scientific, Waltham, MA, USA). Then, serial dilutions of plasmids were prepared in order to obtain a range of concentrations from 10⁶ to 10¹ plasmid copies for 2 µl,
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which is the sample volume used on the LightCycler 480 system. Plasmid dilutions were prepared with distilled water supplemented with 10 ng/µl salmon sperm DNA (Thermo Fisher Scientific).

**Standard curves, linearity, primer specificity.** Dilutions of sets of plasmids were tested on the LightCycler 480 from $10^1$ to $10^6$ plasmid copies for 2 µl: a linear curve with a 1.75-2.25 efficacy and reproducibility for the five replicates (Cq range <0.2) was required for validation of the plasmids and the primers. This test has been performed on the newly designed primers targeting the following bacteria *Bordetella avium*, *Chlamydia psittaci* and *Ornithobacterium rhinotracheale* (ORT). The primers selected in the literature targeting avian metapneumovirus (aMPV), avian influenza virus (M gene) and *Avibacterium paragallinarum* (Ap) were also submitted to that efficacy test.

**The Biomark platform: reaction details.** The nanofluidic chip used in this study, BioMark™ 96.96 Dynamic Array chips, the IFC Controller HX and the BioMark™ Real-Time PCR System are manufactured by Fluidigm Corporation. The IFC Controller HX utilizes pressure to control the valves in the chips and load samples, reagents and primer mix into the reaction chambers. The BioMark system can be used to thermal cycle these nanofluidic chips and capture the data in real time. The use of BioMark™ 96.96 Dynamic Array chips allows the real-time quantification of 9216 points at the same time.

A pre-amplification was first performed on cDNA using a mix of 66% Rgt kit PreAmp Master Mix (Fluidigm) and 34% of a 0.2 µM mix of all primers used in the study. A volume of 3.7 µl of this mix was added to 1.3 µl of each cDNA. PCR was performed with an initial 10 min step at 95°C, followed by 14 cycles of a two step amplification profile consisting of 15 s at 95° C for denaturation and 4 min at 60°C for annealing and extension. These products were submitted to a digestion with exonuclease (NEB, Ipswich, MA), 30 min at 37°C then 15 min at 80°C, then diluted by five in TE low EDTA (Life Technologies).

A sample was prepared using 66% of 2X TaqMan® Gene Expression Master Mix (Applied Biosystem, Foster City, CA), 7% of 20X DNA Binding Dye Sample Loading Reagent (Fluidigm), 7% of EvaGreen (Interchim, Montluçon, France) and 20% of TE 1X. A volume of 5 µl of this mix was added to 1.7 µl of the dilution of pre-amplified cDNA, and 5 µl of this sample mix was loaded into each sample loading well of the chip. Primers (1.7 µl of 20 µM each, forward and reverse for each gene) were mixed with 5 µl of 2X Assay Loading Reagent (Fluidigm), and 5 µl were loaded into each primer loading well of the chip. The BioMark™ 96.96 Dynamic Array chip was then loaded into the IFC Controller HX to mix primers and

samples. PCR was performed with an initial two-step erase and hot start phase consisting of 2 min at 50°C and 10 min at 95°C, followed by 35 cycles of a two-step amplification profile consisting of 15 s at 95°C for denaturation and 1 min at 60°C for annealing and extension. Images were captured at each cycle with the camera of the BioMark™ Real-Time PCR System. A melting phase was then performed from 60°C to 95°C with an image taken every 1°C. Expression data were analysed with Fluidigm's Real-Time PCR Analysis software and melting curves were analysed using Fluidigm's BioMark Melting-curve Analysis software.

Biomark runs were dedicated to primer validation; cDNA and control plasmids were used as samples and screened with the 19 primer pairs.

**Collection and screening of field samples.** A total of 178 meat turkeys from 17 distinct farms in France and Morocco were sampled following different criteria: flocks (i) showing respiratory signs for less than 5 days, (ii) with an intra-flock respiratory signs prevalence of at least 10% and (iii) antibiotic-free since the beginning of the respiratory signs and for at least one week. Tracheal swabs were collected from five to 10 affected turkeys. Swabs were then kept at 4°C and shipped within 24 h before storage at -80°C until further processing. Before collection of clinical samples, the attending veterinarian explained the protocol and received the informed consent of the owner of the birds.

DNA and RNA extraction, cDNA synthesis and real-time quantitative PCR were performed on the field samples, as described in the previous section.

One hundred and seventy-eight field samples were screened on the Biomark platform, using two 9216-microwell cell arrays. For this validation, all these samples were tested in quadruplicate with each of the 19 PCR primer pairs. In addition to samples, standard plasmids used as positive controls and no template controls were loaded on the Biomark plates.

**Cq value and Tm determination.** The amplification curves and melting peaks were displayed and analysed using Fluidigm's real-time PCR Analysis software (version 4.1.2). Concerning analysis settings, baseline correction was linear and the Cq threshold was automatically defined. Cq values and melting peak temperatures were, therefore, directly obtained from the software.

Results were exported as .csv files and formatted in a spreadsheet program in order to generate a synthetic and user-friendly table where, for each sample, the reaction results were displayed as positive or negative, taking into account the Cq and the melting peak values. If the Cq and the melting peak values of the four replicates were consistent, the mean of the four values was considered.
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# Results

## Primer validation on conventional real-time cycler

A set of primers were designed in silico and submitted to a first validation on a LC480 thermocycler (Table 1). Each cross-reaction test performed with the primers listed in Table 1 (Chen et al., 1996; Clermont et al., 2000; Fouchier et al., 2000; Kho et al., 2000; Boyce et al., 2002; Farsang et al., 2002; Register & Yersin, 2005; Chen et al., 2006; Jarquin et al., 2009; Mahmoudian et al., 2011; Johnson et al., 2012; Wang et al., 2012; Cecchinato et al., 2013) was negative. The plasmids corresponding to in-house designed primers and some corresponding to primers selected in the literature targeting aMPV, avian influenza virus and Ap were tested with their dedicated primers on a range of concentrations from 10¹ to 10⁶ copies per reaction. PCR primer efficiencies were directly obtained from the LightCycler 480 on the basis of the plasmid standard curves. Efficiency was found to be in the range of 1.75–2.25, corresponding to the standard of 75–125% efficiency; these values and limit of detection (LOD) are listed in Table 2.

## PCR primer validation on the Biomark platform

After validation on the LightCycler480 platform, the selected PCR primers were subsequently tested on the Biomark platform. Figure 1 provides an overview of the positive controls tested on the Biomark platform. Nineteen PCR primer pairs generated expected amplification curves whose Cq values were below 30. The melting peak temperatures of the positive controls were considered as standard values for validation of the specificity of the reaction. Therefore, the field samples Tm were validated if they were in a range of ±1°C from the reference values. Figure 2 shows an example of specific amplification curves and melting peaks obtained with aMPV primers on field samples. At this stage, a total of 19 PCR primer pairs were validated (Table 1) using standard plasmids and cDNA in order to check that cross-reactions did not occur between PCR primers and non-specific targets (data not shown).

## Field sample screening on the Biomark platform

As a proof-of-concept, 178 field samples, originating from 17 turkey flocks from France or Morocco facing

<table><caption>**Table 1.** List of primers selected from literature or designed.</caption><thead><tr><th>Pathogen</th><th>Targeted gene</th><th>Forward primer name<br>Reverse primer name</th><th>Forward primer (5'-3')<br>Reverse primer (5'-3')</th><th>Amplicon length<br>(bp)</th><th>Reference</th></tr></thead><tbody><tr><td>Influenza A virus</td><td>M</td><td>M52C<br>M253R</td><td>CTTCTAACCGAGGTCGAAACG<br>AGGGCATTTTGGACAAKACGTCTA</td><td>250</td><td>Fouchier et al. (2000)</td></tr><tr><td>Metapneumovirus subtypes<br>A & B</td><td>SH</td><td>SH-f<br>SH-r</td><td>TAGTTTTGATCTTCCTTGTTGC<br>GTAGTTGTGCTCAGCTCTGATA</td><td>200</td><td>Cecchinato et al. (2013)</td></tr><tr><td>Paramyxovirus-1 (NDV)</td><td>Fusion<br>(cleavage site)</td><td>FIP1<br>FIP2</td><td>TACTTTGCTCACCCCCCTT<br>CATCTTCCCAACTGCCACT</td><td>280</td><td>Kho et al. (2000)</td></tr><tr><td>Avian infectious bronchitis<br>virus</td><td>N</td><td>N791<br>N1129</td><td>GTGATGACAAGATGAATGAGGA<br>CAGCTGAGGTCAATGCTTTATC</td><td>380</td><td>Farsang et al. (2002)</td></tr><tr><td>Avian ILTV</td><td>UL15a</td><td>UL15aF<br>UL15aR</td><td>TTGCTGTGCTATTCGCGTG<br>GTAAATCGTTTAGTGCGGCAT</td><td>113</td><td>Mahmoudian et al. (2011)</td></tr><tr><td>M. gallisepticum</td><td>16S</td><td>MG14F<br>MG13R</td><td>GAGCTAATCTGTAAAGTTGGTC<br>GCTTCCTTGCGGTTAGCAAC</td><td>186</td><td>Jarquin et al. (2009)</td></tr><tr><td>M. synoviae</td><td>16S</td><td>MSLF<br>MSLR</td><td>GAGAAGCAAAATAGTGATATCA<br>CAGTCGTCTCCGAAGTTAACAA</td><td>214</td><td>Jarquin et al. (2009)</td></tr><tr><td>B. avium</td><td>recA</td><td>BaREC2f<br>BaREC2r</td><td>CGGAATCGTCGGGTAAAACG<br>TGGAAGCGTACTGGACATCG</td><td>200</td><td>In-house primers</td></tr><tr><td>ORT</td><td>gyrA</td><td>ORT101F<br>ORT101R</td><td>TGGGCAAGGGAACTTTGGTT<br>TGTCGGCAAGCATTTCCTCA</td><td>101</td><td>In-house primers</td></tr><tr><td>P. multocida</td><td>gyrB</td><td>gyrBPMF<br>gyrBPMR</td><td>GCCCTTCCGATAAATTGCAA<br>ATCGCGGCTAATGGTGCTT</td><td>100</td><td>Boyce et al. (2002)</td></tr><tr><td>R. anatipestifer</td><td>gyrB</td><td>gyrBP1<br>gyrBP2</td><td>AGAGCGAGAAGAAAAAACCT<br>CTCCCATAGCATAGAGAAGA</td><td>194</td><td>Wang et al. (2012)</td></tr><tr><td>C. psittaci</td><td>ompA</td><td>Cp2fbis<br>Cp2r</td><td>CTCGCCCTGTCTTACAGATTG<br>GCATCAAAAGTTGCTCGTGACC</td><td>74</td><td>In-house primers</td></tr><tr><td>Ap</td><td>hp1</td><td>HP1F<br>HP1R</td><td>TGAGGGTAGTCTTGACACGCGAAT<br>CAAGGTATCGATCGTCTCTCTACT</td><td>500</td><td>Chen et al. (1996)</td></tr><tr><td>E. coli<br>(four subtypes)</td><td>gadA</td><td>GadA.F<br>GadA.R</td><td>GCGTTGCGTAAATATGGTTTGCCGA<br>CGTCACAGGCTTCAATCATGCGTT</td><td>305</td><td>Chen et al. (2006)</td></tr><tr><td>E. coli<br>(four subtypes)</td><td>chuA</td><td>ChuA.1<br>ChuA.2</td><td>GACGAACCAACGGTCAGGAT<br>TGCCGCCAGTACCAAAGACA</td><td>279</td><td>Clermont et al. (2000)</td></tr><tr><td>E. coli<br>(four subtypes)</td><td>yjaA</td><td>YjaA.1<br>YjaA.2</td><td>TGAAGTGTCAAGGAGACGCTG<br>ATGGAGATGCGTTCCTCAAC</td><td>211</td><td>Clermont et al. (2000)</td></tr><tr><td>E. coli<br>(four subtypes)</td><td>TspE4C2</td><td>TspE4C2.1<br>TspE4C2.2</td><td>GAGTAATGTCGGGGCATTCA<br>CGCGCCAACAAAGTATTACG</td><td>152</td><td>Clermont et al. (2000)</td></tr><tr><td>16S RNA</td><td>16S rDNA</td><td>Univ 16S-3<br>Univ 16S-4</td><td>AGAGTTTGATCCTGGCTCAG<br>GCGGCTGCTGGCACG</td><td>300</td><td>Register and Yersin (2005)</td></tr><tr><td>A. fumigatus</td><td>18S rDNA</td><td>Asp-fw<br>Asp-rv</td><td>CTTGGATTTGCTGAAGACTAAC<br>CTAACTTTCGTTCCCTGATTAATG</td><td>76</td><td>Johnson et al. (2012)</td></tr></tbody></table>
<figure><img src="image_20.png" /><figcaption>**Table 2.** Limit of quantification (LOQ), LOD, efficacy and r² values for five PCR primer pairs.</figcaption></figure>

<table><thead><tr><th>Pathogen</th><th>LOQ<br>(copies/2 µl)</th><th>LOD<br>(copies/2 µl)</th><th>Efficacy</th><th>r²</th></tr></thead><tbody><tr><td>Avian metapneumovirus (A, B)</td><td>10<sup>6</sup>–10<sup>2</sup></td><td>50</td><td>1.92</td><td>0.997</td></tr><tr><td>Influenza virus (M)</td><td>10<sup>6</sup>–10<sup>2</sup></td><td>50</td><td>1.96</td><td>0.999</td></tr><tr><td>Ap</td><td>10<sup>5</sup>–10<sup>2</sup></td><td>50</td><td>1.86</td><td>0.996</td></tr><tr><td>C. psittaci</td><td>10<sup>6</sup>–10<sup>2</sup></td><td>50</td><td>1.96</td><td>0.999</td></tr><tr><td>B. avium</td><td>10<sup>5</sup>–10<sup>1</sup></td><td>5</td><td>2.02</td><td>0.995</td></tr></tbody></table>

acute respiratory signs, were screened using the Bio-mark respiratory panel. A synthetic report of screening results is presented in Table 3 and the comprehensive set of data is available as supplementary data (Supplementary Table 1).

### Screening for avian respiratory viruses

All samples, from both countries, tested negative for broad-influenza A assay targeting M gene. An estimated 57/178 samples tested positive for aMPV and 29/178 were found positive for Paramyxovirus-1. Further sequence analysis showed that these PMV-1 clustered in La Sota Clone 30 genotype, suggesting that they actually were vaccine viruses (data not shown). Surprisingly, three Moroccan turkeys tested positive for avian infectious laryngotracheitis virus (ILTV).

### Screening for avian respiratory bacteria

One hundred and twenty-eight/178 turkey swabs tested positive for ORT, 44/178 for *Mycoplasma gallisepticum*,

39 for *Mycoplasma synoviae*, 33 for *B. avium* and 3 for *Riemerella anatipestifer*.

Birds from Morocco tested positive only for *Pasteuria multocida* (41/88) and Ap (13/88), with only one bird testing positive for *C. psittaci*.

A specific screening was performed for *Escherichia coli* so as to define genotypes (Clermont *et al.*, 2000): *E. coli* affiliated to B2 genotype (clustering most avian pathogenic *E. coli*) was detected in as many as 102/178 birds, i.e. 16/17 flocks.

### Screening for avian respiratory fungi

All French and Moroccan turkeys tested positive for *Aspergillus fumigatus*.

### Comparative analysis of coinfection patterns

Coinfection profiles in French and Moroccan poultry flocks are displayed in Table 3. Coinfections could be identified in all submitted flocks. While aMPV, ORT and *E. coli* were widespread in turkeys from both countries and should be controlled at a global scale, *M. synoviae* seemed specifically prevalent in France and *P. multocida* in Morocco.

### Discussion

We developed a panel assay targeting all the significant poultry respiratory agents in our knowledge (Glisson, 1998; Kleven, 1998; Jones, 2010). A set of 19 primers was selected and validated on a nanofluidic high

<figure><img src="image_21.png" /><figcaption>**Figure 1.** BioMark specificity test.</figcaption></figure>

Notes: Each square represents a single real-time PCR reaction. Rows indicate the pathogen in the positive control and columns represent the specific primers set. Cq values for each reaction are indicated by a colour code: the corresponding colour scale is figured out in the legend on the right. The more the brightness, the lower the Cq value and the higher the DNA load. Near dark squares are interpreted as negative reactions.
<figure><img src="image_22.png" /></figure>

<figure><img src="image_23.png" /><figcaption>**Figure 2.** Biomark amplification and Tm curves.</figcaption></figure>

Notes: The curves on the top correspond to Eva green fluorescence generated by the amplification of DNA during PCR. Below, the melting peaks derived from the dissociation curves which are generated at the end of the reaction for the checking of the specificity of the reaction.

throughput PCR platform. This panel assay was validated on reference strains and then on a set of field samples as a clinical proof-of-concept. This panel assay was shown to be at least as sensitive and specific as real-time PCR and was able to provide in a single assay a comprehensive picture of viral and bacterial

coinfections. The benchmark between microfluidic and conventional real-time PCR platforms showed similar PCR detection thresholds and cross-reactivity. The main specific features of Fluidigm PCR are the dye (EvaGreen versus SYBR Green) and the volume of reaction (9 nl versus 5–25 µl). However, it has

<table><caption>**Table 3.** Synthetic report of screening performed on swabs sampled from French and Moroccan turkeys.</caption><thead><tr><th></th><th>Flock</th><th>M</th><th>aMPV</th><th>PMV-1</th><th>IBV</th><th>ILT</th><th>MG</th><th>MS</th><th>ORT</th><th>BA</th><th>PM</th><th>CP</th><th>RA</th><th>AP</th><th>Asp fum</th><th>E. coli B2 genotype</th></tr></thead><tbody><tr><td rowspan="10">French samples</td><td>FR1</td><td>—</td><td>3/12</td><td>8/12</td><td>1/12</td><td>—</td><td>—</td><td>—</td><td>12/12</td><td>3/12</td><td>—</td><td>—</td><td>—</td><td>—</td><td>12/12</td><td>9/12</td></tr><tr><td>FR2</td><td>—</td><td>7/8</td><td>—</td><td>—</td><td>1/8</td><td>2/8</td><td>3/8</td><td>8/8</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>8/8</td><td>7/8</td></tr><tr><td>FR3</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>9/9</td><td>8/9</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>9/9</td><td>1/9</td></tr><tr><td>FR4</td><td>—</td><td>1/12</td><td>—</td><td>—</td><td>—</td><td>—</td><td>5/12</td><td>9/12</td><td>4/12</td><td>—</td><td>—</td><td>—</td><td>—</td><td>12/12</td><td>6/12</td></tr><tr><td>FR5</td><td>—</td><td>8/11</td><td>5/11</td><td>—</td><td>—</td><td>5/11</td><td>11/11</td><td>11/11</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>11/11</td><td>9/11</td></tr><tr><td>FR6</td><td>—</td><td>—</td><td>2/15</td><td>—</td><td>—</td><td>3/15</td><td>1/15</td><td>4/15</td><td>—</td><td>—</td><td>—</td><td>2/15</td><td>—</td><td>15/15</td><td>7/15</td></tr><tr><td>FR7</td><td>—</td><td>10/10</td><td>—</td><td>—</td><td>—</td><td>4/10</td><td>5/10</td><td>6/10</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>10/10</td><td>6/10</td></tr><tr><td>FR8</td><td>—</td><td>1/11</td><td>—</td><td>—</td><td>11/11</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>11/11</td><td>11/11</td></tr><tr><td>FR9</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>2/2</td><td>—</td></tr><tr><td rowspan="8">Moroccan samples</td><td>MO1</td><td>—</td><td>11/15</td><td>2/15</td><td>—</td><td>1/15</td><td>1/15</td><td>—</td><td>14/15</td><td>—</td><td>10/15</td><td>—</td><td>1/15</td><td>—</td><td>15/15</td><td>9/15</td></tr><tr><td>MO2</td><td>—</td><td>1/15</td><td>5/15</td><td>—</td><td>—</td><td>13/15</td><td>5/15</td><td>12/15</td><td>1/15</td><td>14/15</td><td>—</td><td>—</td><td>—</td><td>13/15</td><td>9/15</td></tr><tr><td>MO3</td><td>—</td><td>6/15</td><td>—</td><td>—</td><td>2/15</td><td>13/15</td><td>—</td><td>14/15</td><td>—</td><td>11/15</td><td>1/15</td><td>—</td><td>—</td><td>15/15</td><td>12/15</td></tr><tr><td>MO4</td><td>—</td><td>1/9</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>3/9</td><td>5/9</td><td>1/9</td><td>—</td><td>—</td><td>—</td><td>8/9</td><td>1/9</td></tr><tr><td>MO5</td><td>—</td><td>3/10</td><td>2/10</td><td>—</td><td>—</td><td>3/10</td><td>—</td><td>10/10</td><td>7/10</td><td>4/10</td><td>—</td><td>—</td><td>—</td><td>9/10</td><td>2/10</td></tr><tr><td>MO6</td><td>—</td><td>4/18</td><td>5/18</td><td>—</td><td>—</td><td>—</td><td>—</td><td>17/18</td><td>—</td><td>1/18</td><td>—</td><td>—</td><td>—</td><td>18/18</td><td>11/18</td></tr><tr><td>MO7</td><td>—</td><td>1/5</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>5/5</td><td>1/5</td></tr><tr><td>MO8</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>1/1</td><td>1/1</td></tr></tbody></table>

Note: M: influenza A virus, M gene; aMPV: avian metapneumovirus; PMV-1: Paramyxovirus-1 (NDV); IBV: Avian infectious bronchitis virus; ILT: Avian infectious laryngotracheitis virus; MG: Mycoplasma gallisepticum; MS: Mycoplasma synoviae; ORT: Ornithobacterium rhinotracheale; BA: Bordetella avium; PM: Pasteuria multocida; CP: Chlamydia psittaci; RA: Riemerella anatipestifer; AP: Avibacterium paragallinarum; Asp fum: Aspergillus fumigatus.
<figure><img src="image_24.png" /></figure>

been previously shown that the results obtained on the Biomark platform show a very good concordance with conventional real-time PCR (Spurgeon *et al.*, 2008).

This respiratory panel assay is *not* based on a multi-plex approach: a uniplex real-time PCR test is performed in each well and may provide quantitative data based on a full range of standards. The loads of each pathogen were not further analysed here, but may be very helpful to the clinician to evaluate their respective pathological relevance.

The design of the platform is based on a systematic screening of each sample with all the primer pairs, which led necessarily to unexpected results: we had to exclude some PCR primers designed and validated in published reports, since they cross-reacted with other targets that had probably not been tested so extensively. Similarly, a contamination event during the process would be clearly identified as a whole line of samples (or primers) would generate inconsistent positive signals.

The main advantages of the Fluidigm Biomark platform are (i) its microfluidic format, allowing as many as 48–96 PCR assays per sample using as few as 5 µl of nucleic acids and (ii) its versatility, making easy any updating or addition of primers in case of emergence of viruses or variants or need for any further typing. Indeed, as a first attempt, the respiratory panel assay presented here is intentionally based on a limited number of broad range primers, designed to provide a general knowledge on the pattern of pathogens. Future versions of this respiratory panel shall detect specific variants, as well as virulence or antibiotic resistance markers.

Respiratory infections are the first indication for antibiotic treatments in food birds, most of the time without any supportive microbiological clinical data. They result from complex and versatile combinations of environmental and infectious factors and can hardly be elucidated only on the basis of clinical or necropsic signs. In human medicine, the recent introduction of panel assays has dramatically improved the knowledge on viruses involved in acute RS and is helpful in decision-making to define better treatment protocols (Jartti *et al.*, 2013; McCulloh *et al.*, 2014). In veterinary medicine, the main limit in routine diagnosis of respiratory diseases is the unavailability of such molecular tools allowing rapid, easy and affordable screening for a panel of pathogens, adapted for bovine, porcine or poultry species. This knowledge on pathogens, including their subtype and load, would be critical to define more accurate vaccine or therapeutic protocols and reduce the use of antibiotics. Molecular assays also make it possible to analyse samples deposited on neutralizing transport devices such as Flinders Technology Associates cards, allowing completely safe international shipments of nucleic acids for implementation of surveillance programs at a global scale (Awad *et al.*, 2014).

As a clinical proof-of-concept study, we screened tracheal samples from French and Moroccan poultry facing acute RS. As expected, coinfections were widely detected in most flocks, including viruses and bacteria in most cases (Sid *et al.*, 2015). *E. coli* was detected in almost all birds, the set of primers (Clermont *et al.*, 2000) allowing the discrimination of phylogroups and the identification of B2 strains, which are clustering most of avian pathogenic *E. coli* (Guabiraba & Schouler, 2015). ORT is also very much prevalent in both countries, which is in accordance with observations in the field and clinical laboratories.

This overview on coinfection patterns may be a relevant help for changing practices in administration of vaccines or antibiotics, for example, towards *M. gallisepticum* versus *P. multocida*.

All the data do not show the same relevance: the systematic detection of *A. fumigatus* was likely due to environmental contaminations from the air of poultry houses (Sowiak *et al.*, 2012), which questions the relevance of this target in this respiratory panel in the future.

The development of new molecular panel assays adapted to veterinary medicine will be one of the contributions towards a better understanding and control of respiratory coinfections in food birds, in the perspective of an evidence-based use of antibiotics.

## Acknowledgements

We thank the staff of the GenoToul platform of Genomics for excellent technical assistance with the experiments on Biomark. Guillaume Croville was a PhD candidate from the EPHE-SIEB doctoral school, France.

## Disclosure statement

No potential conflict of interest was reported by the authors.

## Funding

This project was funded by the French Institut Carnot de Santé Animale (ICSA) and was partly performed in the framework of a Hubert Curien Partnership (PHC) [grant PRAD/11-07/24193 PC, Campus France, entitled *Emerging diseases of turkeys in Morocco*. It was also partly performed in the framework of the LabCom VIRAL, associating ENVT, INRA and FILAVIE and funded by the French Agence Nationale de la Recherche [grant ANR-15-LCV1-0003-01].

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