1 a Method for the Unbiased Quantification of Reassortment in Segmented Viruses

bioRxiv preprint doi: https://doi.org/10.1101/708982; this version posted July 22, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

1 A method for the unbiased quantification of reassortment in segmented viruses

3 Megan R. Hockmana, Kara Phippsa, Anice C. Lowena

5 aDepartment of Microbiology and Immunology, Emory University School of Medicine, Atlanta, Georgia,

6 United States of America

10 Highlights

11 • Genetic tagging of viruses can be achieved without altering fitness

12 • High-resolution melt can detect single nucleotide differences in viruses

13 • Unbiased reassortment of influenza A virus and mammalian orthoreovirus can be

14 quantified

17 Abstract

18 The diversification of segmented viruses via reassortment is important to understand due to the

19 contributions of reassortment to viral evolution and emergence. Methods for the quantification of

20 reassortment have been described, but are often cumbersome and best suited for the analysis of

21 reassortment between highly divergent parental strains. While it is useful to understand the potential of

22 divergent parents to reassort, outcomes of such heterologous reassortment are driven by differential

23 selection acting on the progeny and are typically strain specific. To quantify reassortment, a system free

24 of differential selection is needed. We have generated such a system for influenza A virus and for

25 mammalian orthoreovirus by constructing well-matched parental viruses carrying small genetic tags. The

26 method utilizes high-resolution melt technology for the identification of reassortant viruses. Ease of

27 sample preparation and data analysis enables streamlined genotyping of a large number of virus clones.

28 The method described here thereby allows quantification of the efficiency of unbiased reassortment and

29 can be applied to diverse segmented viruses.

31 Keywords

32 Reassortment, reovirus, influenza virus, viral genetics

34 Introduction

35 Virus genome organization varies widely across different families. Segmented genomes, which are

36 comprised of distinct RNA or DNA molecules, have been documented in eleven virus families to date.

37 Segment numbers vary, as do replication strategies. Each genome segment encodes a different protein or

38 proteins which are involved in establishing a productive infection. During infection, cells can be co-

39 infected by multiple parent viruses. In segmented viruses, co-infection events have the potential to give

40 rise to many different progeny genotypes, fueling evolution.

42 Viruses with segmented genomes undergo a type of genetic recombination termed reassortment.

43 Reassortment occurs when two or more parent viruses co-infecting a single cell exchange whole gene

44 segments, which are then packaged together to yield progeny viruses with novel genotypes. This mode of

45 generating diversity is unique to segmented viruses, and contrasts with classical recombination, in which

46 a chimeric product is formed from the breaking and rejoining of nucleic acid strands. Reassortment events

47 most often yield attenuated progeny due to incompatibilities between nucleic acids and/or proteins

48 derived from heterologous parents1-5. There is, however, the potential for the coupling of compatible,

49 beneficial alleles and the subsequent emergence of novel pathogens, as was observed in the 2009

50 influenza A virus (IAV) pandemic6, 7.

52 To date, reassortment has been investigated in several viruses, including IAV and mammalian

53 orthoreovirus, using a variety of methods. Measurement of reassortment is often complicated by fitness

54 differences among progeny viruses or a lack of sensitive quantification methods. In the former case,

55 difficulties arise due to selection. When reassortment yields progeny of variable fitness, those with the

56 most beneficial segment combinations will be amplified more rapidly. Preferential propagation of

57 parental genotypes results in under-estimation of the frequency of reassortment. Similarly, preferential

58 amplification of certain reassortant viruses results in under-estimation of population diversity. To avoid

59 these issues, it is preferable to quantify reassortment between viruses of more similar genotypes. This

60 can be challenging, however, as most detection methods rely on parental viruses being significantly

61 different genetically. Detection of reassortment in genetically similar viruses requires sensitive molecular

62 technologies, which were not available until relatively recently8.

64 The earliest method to identify reassortants utilized polyacrylamide gel electrophoresis9-11. This method

65 depends on all segments of each parental genome having different electrophoretic mobility. For this to

66 be the case, each segment must differ significantly in length and/or sequence. The requirement for

67 significant differences for detection necessitates that parent viruses are divergent which can impact the

68 fitness of reassortant progeny and reduce observed rates of reassortment. Additionally, there is a practical

69 limitation on the number of samples that can feasibly be analyzed using this approach.

71 As an alternative approach, temperature-sensitive (ts) mutants have been used to quantify

72 reassortment12, 13. In this system, a single segment confers temperature-sensitivity in each parental virus

73 and pairs of viruses used for co-infection carry ts mutations in differing segments. Temperature sensitivity

74 is abrogated if these segments are exchanged for wild type segments from the opposite parent in a

75 reassortment event. Culture of progeny viruses at the nonpermissive temperature results in selection of

76 wild type reassortants. Titration of progeny viruses at the nonpermissive temperature therefore allows

77 quantification of the frequency of exchange of the ts segments. This approach makes it possible to detect

78 reassortment between identical parents (with the exception of the ts lesions), thus avoiding the

79 confounding effects of protein or segment incompatibilities. However, it does not yield the frequency of

80 reassortment between all virus segments but rather only the two ts segments12, 14.

82 PCR-based methods can also be used to differentiate parental segments that differ sufficiently to allow

83 the design of specific primers15-17. Amplicons can be detected using gel electrophoresis with ethidium

84 bromide staining, or by determining Ct values in quantitative PCR. These methods, however, may be

85 limited when parental genomes are too similar to allow unique primer design for all segments.

87 Alternatively, whole or partial genome sequencing of clonal virus populations offers a very flexible

88 approach to identify reassortants18. With sequencing as a read-out, the need for primer design does not

89 constrain the parental viruses that can be examined in combination. Traditionally, the costs of sequencing

90 approaches have prohibited their use on a larger scale. In recent years, however, the price of sequencing

91 has decreased and the technology has improved.

93 To address the shortcomings of prior methodologies and enable robust quantification of reassortment,

94 we present here two methodological innovations. First, to eliminate selection bias, we generated well

95 matched pairs of parental viruses that differ only by one or a handful of synonymous mutations in each

96 genome segment. These introduced synonymous changes act as genetic markers to indicate the parental

97 origin of each segment. Second, to streamline the detection of reassortant viruses, we applied high

98 resolution melt analysis, a post-PCR method originally developed to differentiate single nucleotide

99 polymorphisms in eukaryotic genomes8. Because this method is sensitive enough to detect single

100 nucleotide differences, it allows for the quantification of reassortment between highly similar parental

101 viruses. We have applied these approaches to both IAV and mammalian orthoreovirus.

102

103 Materials and Methods

104 Cell lines and cell culture media

105 293T cells from the American Type Culture Collective (ATCC) were maintained in Dulbecco’s Modified

106 Eagle Medium (DMEM; Gibco) supplemented with 10% fetal bovine serum (FBS; Atlanta Biologicals).

107 Madin-Darby Canine Kidney (MDCK) cells (from Dr. Peter Palese, Icahn School of Medicine at Mount Sinai)

108 were maintained in Minimal Essential Medium (MEM; Gibco) supplemented with 10% FBS and 100U/100

109 μg/mL penicillin/streptomycin (Corning). Baby hamster kidney cells stably expressing T7 RNA polymerase

110 (BHK-T7) cells19 were maintained in DMEM supplemented with 5% FBS, 2 mM L-Glutamine (Corning),

111 100U/100 μg/mL penicillin/streptomycin and 1 mg/mL G418 (Gibco). Spinner-adapted L929 cells (gift from

112 Bernardo Mainou) were grown in Joklik’s modified MEM supplemented with 5% FBS, 2 mM L-Glutamine,

113 100U/100 μg/mL penicillin/streptomycin and 0.25 mg/mL amphotericin B (Sigma), termed SMEM.

114

115 Design of wild-type and variant viruses

116 To allow quantitative analysis of reassortment, we designed parental viruses that are i) highly

117 homologous, so that reassortment does not give rise to genetic or protein incompatibilities, and ii)

118 genetically distinct in all segments to allow tracking of genetic exchange. For both IAV and mammalian

119 orthoreovius, a variant virus was generated from the wild-type strain using reverse genetics. The wild type

120 virus strains used were influenza A/Panama/2007/99 (H3N2) (Pan/99) virus and Type 3 Dearing (T3D)

121 mammalian orthoreovirus. To generate variant (var) viruses, silent mutations were added to the first 1kb

122 of each wild-type virus coding sequence, as shown in Table 1. We have made multiple versions of the

123 Pan/99var virus20, 21; the Pan/99var virus described here is Pan/99var15. The mutations made were A to

124 G/G to A or C to T/T to C, which have the greatest impact on melting properties8. The melting properties

125 of a short amplicon (65-110 base pairs) containing a mutation of this nature is typically altered sufficiently

126 to allow robust detection by high resolution melt analysis8, 22. To avoid introducing attenuating mutations,

127 sites of natural variation were targeted where sequence data was available. For IAV, isolates from the

128 same lineage within a 10 year time frame were selected from the NCBI GenBank database, and 20-30

129 sequences were aligned. Sites within the first 1000 bp relative to the 3’ end of the vRNA that displayed

130 high nucleotide diversity were targeted for introduction of variant mutations. Point mutations were

131 introduced into plasmid-encoded viral cDNAs using QuikChange mutagenesis (Agilent) according to the

132 manufacturer’s protocol.

133 To distinguish infected cells by flow cytometry, sequences encoding a 6xHIS or an HA epitope tag were

134 added to the N-terminus of the IAV hemagglutinin protein, connected by a GGGGS linker sequence23. The

135 6xHIS tag was added to the Pan/99wt virus and the HA tag was added to the Pan/99var15 virus. The linker

136 sequence provides flexibility so that the epitope tags do not interfere with HA protein folding. To ensure

137 the tags were retained on the mature HA proteins, they were inserted after the signal sequence. It was

138 not possible to add an epitope tag to reovirus, as this has been demonstrated in the literature and in our

139 hands to cause growth defects (data not shown)24.

140

141 Generation of virus stocks

142 Influenza A viruses were generated by reverse genetics from viral cDNA25, 26. Eight pPOL1 reverse genetics

143 plasmids encoding the eight viral cDNAs were combined with four pCAGGS protein expression vectors

144 encoding PB2, PB1, PA, and NP proteins. These plasmids were co-transfected into 293T cells using

145 XtremeGene (Sigma-Aldrich) transfection reagent according to the manufacturer’s recommended

146 procedure. At 16-24 h post transfection, the 293T cells were resuspended in growth medium and injected

147 into the allantoic cavity of 9-11 day old embryonated chicken eggs (Hy-Line). Eggs were incubated 40 h in

148 a humidified 33°C incubator. Incubation at 33°C was used because we have observed improved growth of

149 the Pan/99 strain at this temperature, compared to 37°C 27. After chilling eggs overnight at 4°C, allantoic

150 fluid was harvested, clarified of cell debris and aliquoted for storage at -80°C.

151 Mammalian orthoreoviruses were generated from viral cDNA cloned into the pT7 plasmid in BHK-T7

152 cells28. Plasmids containing each of the 10 viral cDNA’s and pCAG FAST P10 plasmid were transfected into

153 BHK-T7 cells using TransIT-LT1 (Mirus)29. Cells were fed with an additional 500 μL SMEM on day 2. BHK-T7

154 cells were incubated at 37°C for a total of 5 days, after which virus was harvested with 3 freeze-thaw

155 cycles at -80°C. Plaque assays were performed using viral lysates as previously described30. Reoviruses

156 were amplified for two passages in L929 cells30. Purified virus stocks were made from second passage L929

157 lysates. Purification was performed as described previously using Vertrel XF extraction and a CsCl density

158 gradient31. The band at 1.36 g/cm3 was collected and dialyzed exhaustively against virus storage buffer

159 (15mM NaCl, 15mM MgCl2, 10mM Tris-HCl [pH 7.4]). The resultant purified material was stored in glass

160 vials at 4°C for up to six months.

161

162 Viral growth in guinea pigs

163 All animal experiments were approved by the Emory Institutional Animal Care and Use Committee under

164 protocol number PROTO201700595, following the Guide for the Care and Use of Laboratory Animals32.

165 Guinea pigs were inoculated intranasally with 103 PFU of Pan99/wt or Pan99/var15 as described

166 previously33. Nasal washes were collected on days 1, 2, 3, 4, and 5 post inoculation33. Virus titers in nasal

167 washes were determined by plaque assay in MDCK cells.

168

169 Primers

170 Reverse Transcription

171 For IAV, reverse transcription was performed using universal primers that anneal to the 3’ end of all eight

172 IAV vRNA’s (GCGCGCAGC[A/G]AAAGCAGG) 34. Due to a lack of universally homologous sequences in

173 reovirus, random hexamer primers (Thermo) were used in place of virus-specific primers.

174

175 High-resolution melt

176 Primers for quantitative PCR followed by high-resolution melt analysis were designed to flank the

177 polymorphisms introduced into variant viruses. These primers were designed such that the amplicon size

178 would be 65-110 nucleotides and annealing temperatures were 58-62°C. Primer sequences for IAV and

179 reovirus are listed in Table 2. Primer mixes were made by combining 5 μL of the 100 μM forward primer

180 stock and 5μL of the 100 μM reverse primer stock with 240 μL molecular biology grade water for a final

181 concentration of 4 μM.

182

183 Synchronized co-infection

184 IAV

185 Co-infections were performed with wild-type and variant (wt/var) viruses mixed at a 1:1 ratio and then

186 diluted in PBS such that the total PFU/mL would give the desired multiplicity of infection. MDCK cells

187 seeded at a density of 4x105 cells/well in 6-well dishes 24 h prior were placed on ice, washed three times

188 with 1X PBS, and inoculated with 200 μL of virus mixture in PBS. Dishes were moved to 4°C and rocked

189 every 10 min for 45 min. After this attachment period, cells were put back on ice and washed 3 times with

190 cold PBS. A 2 mL volume of warm virus medium (1X MEM with 100U/100 μg/mL penicillin/streptomycin,

191 0.3% bovine serum albumin [Sigma]) was added to each well, and plates were put into a 33°C incubator.

192 At 3 h post infection (i.e. 3 h after warming), medium was removed and replaced with 2 mL warm virus

193 medium supplemented with 20 mM NH4Cl and 50mM HEPES to prevent acidification of the endocytic

194 compartment and thus prevent multiple cycles of infection. At 12 h post infection, supernatants were

195 collected and stored at -80⁰C. Cells were harvested and prepared for analysis by flow cytometry.

196 Reovirus

197 Co-infections were similar to those for IAV, with a few modifications. L929 cells were seeded in 6-well

198 dishes at a density of 5x105 cells/well 24 h prior to infection. The virus inoculum was prepared in OPTI-

199 MEM (Gibco), and cells were incubated in SMEM at 37°C. Rather than ammonium chloride, E64D protease

200 inhibitor (Sigma) was added at a final concentration of 4 μM at 4 h post infection to block secondary

201 infection. At 24 h post infection, three replicate wells of reovirus-infected cells at each MOI were

202 harvested for flow cytometry, and the remaining three replicates were freeze-thawed 3 times at -80°C to

203 release virus, and lysates stored at -80°C for future analysis.

204

205 Flow cytometry to quantify infected cells

206 IAV

207 Cells were harvested by the addition of 200 μL trypsin (Corning) and, once cells were detached, 800 μL

208 FACS buffer (1X PBS with 2% FBS). Cells were transferred to 1.5 mL tubes on ice, and pelleted by spinning

209 at 1500 rpm for 3 minutes in a Beckman Coulter Microfuge 22R tabletop centrifuge. Supernatant was

210 removed, and cells were washed two more times with 1 mL FACS buffer and 200 μL FACS buffer,

211 respectively, pelleting and removing supernatant between washes. After washes, cells were resuspended

212 in 50 μL stain buffer (FACS buffer containing Qiagen Penta-HIS Alexa Fluor 647 #35370 at a final

213 concentration of 5 μg/mL and Sigma-Aldrich Monoclonal Anti-HA-FITC, Clone HA-7 #H7411 at a final

214 concentration of 7 μg/mL) on ice in the dark for 35-45 minutes. Cells were washed twice with 200 μL of

215 FACS buffer and resuspended in FACS buffer for analysis.

216

217 Reovirus

218 Cells were trypsinized and washed two times with FACS buffer, as above. Fixation, permeabilization, and

219 staining were performed according to the BD Cytofix/Cytoperm protocol including a 15-minute block step

220 with BD rat anti-mouse CD16/CD32 Fc block. To stain infected cells, a mouse monoclonal anti-σ3 antibody

221 (clone 10C1) at a concentration of 1 μg/mL was added for 30 minutes at 4⁰C. After two washes, an

222 AlexaFluor-647 conjugated donkey anti-mouse secondary antibody (Invitrogen) was added at a 1:1000

223 dilution.

224

225 In both virus systems, data was collected on a BD LSR II Flow cytometer running FacsDiva software. A

226 minimum of 50,000 events was collected for each sample. Subsequent data analysis was performed using

227 FlowJo (v10.1), gating for single cells. The threshold for positivity was determined based on a mock-

228 infected control population stained with the relevant antibodies.

229

230 Viral genotyping

231 Collection of clonal isolates

232 For both reovirus and IAV, samples stored at -80⁰C were thawed and plaque assays were performed as

233 previously described30. Individual, well-isolated plaques were picked by aspirating the agar plug using a 1

234 mL pipette and deposited into 160 μL PBS in a 96-well assay block with 1 ml capacity wells (Costar 3958).

235 From each sample, 21 plaques were picked for IAV, while 32 were picked for reovirus. Additionally, a single

236 wild-type and a single variant plaque were included as controls for each series of 21 or 32 plaque picks.

237 Assay blocks containing plaque isolates can be sealed and stored at -20⁰C or used directly for RNA

238 extraction.

239

240 RNA extraction

241 RNA was extracted directly from agar plugs. Frozen assay blocks were thawed in a 37⁰C water bath and

242 spun down at 2000 rpm for 2 min in a Heraeus Megafuge 16 tabletop centrifuge equipped with Thermo

243 M-20 swinging bucket plate rotor. The Zymo Quick-RNA Viral Kit extraction protocol was followed using

244 96-well plates. Filter and collection plates were provided with the kit. No DNA/RNA Shield was used.

245 Samples were eluted in 40 μL nuclease-free water into MicroAmp Optical 96-well reaction plates (Applied

246 Biosystems). RNA can be covered and stored at -80°C or used directly for reverse transcription.

247

248 Reverse Transcription

249 Working on ice, a 12.8 μL volume of each viral RNA sample was combined with Maxima RT buffer at a final

250 concentration of 1X, dNTP’s at a final concentration of 0.5 mM, either IAV primer at a final concentration

251 of 0.3 μM or random hexamers (Thermo SO142) at a final concentration of 5 μM for reovirus, 100 U

252 Maxima RT (Thermo), and 28 U RiboLock RNAse inhibitor (Thermo). Total reaction volume was 20 μl.

253 Samples were capped, mixed by vortexing, and spun down briefly. Reactions were incubated at 55⁰C for

254 30 minutes and 85⁰C for 10 minutes in a BioRad T100 thermocycler. cDNA can then be stored at -20⁰C or

255 used directly for qPCR and high-resolution melt analysis.

256

257 qPCR and high-resolution melt analysis

258 Viral cDNA was used as a template in qPCR reactions. Separate reactions were set up with primers

259 targeting each of the viral gene segments. First, master mixes were made by combining appropriate

260 primer mixes (see Table 2) with BioRad Precision Melt Supermix at volumes sufficient for the number of

261 samples plus 15% extra. For each well, 0.5 μL of a 4 μM primer mixture containing both the forward and

262 reverse primers was added to 2.5 μL Supermix. A 3 μl volume of this master mix was loaded into a 384

263 well plate (BioRad HSP3805) using a multichannel pipette according to the layouts in Figure 2. A 2 μl

264 volume of cDNA diluted 1:4 (IAV) or 1:5 (reovirus) in molecular biology grade water (Invitrogen) was added

265 to the 384 well plate. Plates were centrifuged at 2600 rpm in a Heraeus Megafuge 16 tabletop centrifuge

266 equipped with Thermo M-20 swinging bucket plate rotor for 3 minutes to collect liquid in the bottom of

267 wells and remove bubbles. qPCR and melt analysis were performed using a BioRad CFX384 Real-Time PCR

268 Detection System. Amplicons were generated by initial denaturation at 95°C for 2 min, then 40 cycles of

269 95°C for 10 s and 60°C for 30 s. Melting properties of PCR amplicons were examined by heating from 67°C

270 to 90°C in 0.2°C increments. Successful amplification of targets was verified in CFX Manager software

271 (BioRad). Melt curves were analyzed using Precision Melt Analysis software (BioRad) to determine viral

272 genotypes.

273

274 Results

275 Marker mutations in variant viruses do not cause fitness defects

276 To quantify reassortment in the absence of selection bias, it is important to ensure that the parent viruses

277 do not differ in fitness. If one virus is fitter, that parental genotype and segments from it are likely to

278 predominate in the progeny virus population due to uneven amplification. This outcome may be of

279 interest in some contexts, but obscures quantitative analysis of reassortment itself. For IAV, fitness of wild

280 type and variant viruses was assessed in a guinea pig model. Groups of four guinea pigs were inoculated

281 intranasally with Pan/99wt or Pan/99var15 virus and nasal washes were performed daily to monitor viral

282 load. The two viruses showed very similar growth, indicating minimal phenotypic impact of the changes

283 introduced into the viral genomes (Figure 3). For mammalian orthoreovirus, single-cycle growth in L929

284 cells was evaluated to compare the fitness of the variant and wild type viruses. Again in this system, the

285 variant strain was not attenuated relative to the wild-type counterpart (Figure 3). The highly homologous

286 genotypes and comparable fitness of parental viruses are expected to result in similar fitness of

287 reassortant progeny, allowing for an unbiased assessment of reassortment frequency.

288

289 Flow cytometry allows quantification of the proportion of cells infected

290 Owing to the presence of non-plaque forming particles in virus populations and routine experimental

291 error, calculation of MOI based on plaque forming units does not always allow an accurate estimation of

292 the proportion of a cell population that is infected. Flow cytometry analysis targeting viral antigens allows

293 a more direct method to monitor infection levels.

294 In the case of IAV, the addition of different epitope tags to wt and var HA proteins allowed quantification

295 of single- and co-infected cells within the population. Four distinct populations were observed

296 representing uninfected, wild-type virus infected (expressing 6x HIS tag), variant virus infected (expressing

297 HA tag), or wild type plus variant co-infected cells (Figure 4). Assessment of the proportion of cells in a

298 population that are co-infected is useful, as co-infected cells are the only ones capable of producing

299 reassortant progeny.

300 Since insertion of epitope tags was not feasible in the reovirus system, flow cytometry of reovirus-infected

301 cells was used to evaluate the proportion of cells that were infected, but no direct measurement of co-

302 infected cells was made. Infected cells were detected using a primary antibody against viral structural

303 protein σ3 (10C1), and compared to an uninfected, stained control. Infected cells cluster within two

304 groups with low and high antigen expression, respectively (Figure 4). To estimate the percentage of

305 infected cells that are co-infected, Poisson statistics can be used, assuming an equal proportion of wild-

306 type and variant viruses were present in the initial infection.

307

308 High-resolution melt analysis allows determination of viral genotypes

309 High-resolution melt analysis allows detection of the nucleotide changes that differentiate wt and var

310 viruses, and can therefore be used for rapid assignment of wt or var genotypes to all segments present in

311 clonal virus isolates. To this end, qPCR was performed with the cDNA of each viral isolate split into eight

312 (IAV) or ten (reovirus) separate duplicate reactions, each containing primers targeting a different segment.

313 Following qPCR, samples with Ct values below 35 were used for melt analysis. The included wt and var

314 controls were used as references and clusters based on similarity of Tm and melt curve shape were

315 generated within BioRad High Precision Melt software (Figure 5). The distinct melt curves of wt and var

316 amplicons indicate that the silent mutations introduced were sufficient for identification of the parental

o 317 origins of each segment (Figure 5). In practice, we find that a minimum Tm difference of 0.15 C is needed

318 to consistently differentiate between wt and var amplicons. Applying this approach to each segment in

319 turn allows the full genotype of each clonal plaque pick to be determined.

320 Full genotypes are depicted in reassortment tables where each column is a separate genome segment,

321 and rows represent clonal isolates (Figure 6). Occasionally, high resolution melt analysis yielded unclear

322 results, with a given amplicon clustering neither with wt nor var controls. Such results were recorded as

323 indeterminate (white boxes in Figure 6). Viral isolates were excluded from analysis if there were more

324 than two segments omitted due to unclear melt curves. If more than 20% of replicates were omitted from

325 analysis, data collection was repeated starting from plaque picks.

326 Following assembly of genotype tables, the percent reassortment observed in each sample is calculated

327 as 100 times the number of reassortant clones identified divided by the total number of clones genotyped.

328 To evaluate the relationship between infection and reassortment, the calculated percent reassortment

329 can be visualized as a function of the percent infected cells as calculated by flow cytometry (Figure 7). For

330 this quantitative assessment of reassortment to be meaningful, it is important that co-infections be

331 performed under single cycle conditions. As noted in the Materials and Methods section, this was

332 achieved for IAV using addition of ammonium chloride to cell culture medium at 3 h post-infection, and

333 for reovirus using E64D protease inhibitor added at 4 h post-infection. Blocking secondary spread of

334 progeny virus ensures that detected frequencies of reassortant viruses reflect the efficiency of

335 reassortment, rather than the efficiency of amplification. In contexts where infection cannot be limited to

336 a single cycle, such as in vivo, analysis of genotypic diversity (as described below) is more appropriate than

337 a simple readout of percent reassortment.

338

339 Diversity analysis quantifies richness and evenness of reassortant population

340 A sample in which a single reassortant genotype is detected repeatedly would have high percent

341 reassortment despite having low genotypic diversity. When using a wt/var co-infection system, this

342 situation is unlikely to arise due to selection, but can nevertheless occur under conditions where

343 stochastic effects are strong (e.g. owing to within host bottlenecks in vivo). Here, the percent

344 reassortment readout is not highly relevant and a more sophisticated analysis of genotypic diversity is

345 needed.

2 346 To quantify the diversity of genotypes present, Simpson’s index (given by D = sum(pi ), where pi is the

347 proportional abundance of each genotype) was used (Figure 7). This approach accounts for both the raw

348 number of species (richness) and variation in the abundance of each (evenness), and is sensitive to the

349 abundance of dominant species. To determine effective diversity, the Simpson index value of each sample

350 was converted to a corresponding Hill number, N2 = 1/D. The Hill number N2 is equivalent to the number

351 of equally abundant species needed to generate the observed diversity in a sample community, and is

352 particularly useful because it scales linearly (i.e., a virus population with N2 = 10 species is twice as diverse

353 as one with N2 = 5). Hill’s N2 therefore allows a more intuitive comparison between populations and is

354 suitable for statistical analysis by basic linear regression methods35.

355

356 Discussion

357 Here we outline a conceptually simple approach to accurately quantify reassortment between co-infecting

358 segmented viruses in the absence of selection bias. Our strategy utilizes reverse genetics derived parental

359 viruses designed to allow both unbiased reassortment and streamlined genotyping. This approach

360 overcomes limitations of previous methods in which quantitative analysis of reassortment was impeded

361 by fitness differences among progeny viruses. The genotyping technology employed furthermore

362 improves upon more cumbersome procedures involving gel electrophoresis or temperature-sensitive

363 mutants. This method is useful for fundamental studies of reassortment and other interactions within

364 virus populations.

365 High resolution melt analysis can also be applied to viral genotyping in systems where highly divergent

366 parental viruses are allowed to reassort. Although fitness differences among progeny viruses will obscure

367 the quantitative assessment of reassortment in such an experiment, monitoring the combined outcomes

368 of reassortment and selection is often highly relevant for assessing the public health risks posed by

369 reassortment of parental strains of interest22, 36-38. Highly divergent parental sequences are likely to exhibit

370 detectable differences in melting properties, conducive to HRM analysis. It is important to note, however,

371 that reciprocal changes within the region targeted for amplification and melt analysis will nullify

372 differences in melting properties and therefore prohibit detection. Short regions with fewer single

373 nucleotide polymorphisms are less likely to contain reciprocal changes, and should be selected for

374 amplification. In addition, regions of high homology must border the target region, as the same HRM

375 primer set must be used for each parent. In practice for IAV, when considering reassortment between

376 strains of differing subtypes, we found that HRM can be successfully applied to genotype the six non-HA,

377 non-NA segments. The low sequence identity across HA and NA subtypes precluded common primer

378 design and an alternative genotyping approach was used for these segments22.

379 Whole genome sequencing of clonal viral isolates is an alternative to the HRM approach that has been

380 used recently to identify reassortant viruses39. Next generation sequencing (NGS) allows parallel

381 sequencing of all viral gene segments, which greatly reduces effort compared to classical Sanger

382 sequencing. In addition, because viral genomes are typically small, the costs of NGS can be reduced by

383 combining the barcoded cDNA derived from multiple isolates into a single sequencing lane. NGS can be

384 applied to any pairing of parental viruses and may be more feasible than HRM where parental viruses are

385 highly divergent and identical HRM primers cannot be generated for all segments. However, in

386 experiments using matched parental viruses, such as the wt/var system, the HRM approach simplifies data

387 collection. Whole genome sequencing requires additional preparation steps including the pre-

388 amplification of cDNA, fragmentation, and library generation. Additionally, customized bioinformatics

389 approaches are necessary for NGS data analysis, but not required in the HRM approach.

390 Segmented viruses utilize a variety of replication strategies which may impact their potential to undergo

391 reassortment. For this reason, quantification of reassortment not only informs studies of viral

392 diversification and evolution, but can also offer insight into fundamental aspects of the virus life cycle. For

393 example, members of the Cystoviridae such as phi6 bacteriophage use genome packaging as an integral

394 part of the assembly mechanism40. Successful assembly can only occur if a full complement of three gene

395 segments is incorporated into a virion. In co-infections between highly divergent parents, an inability to

396 package any of the three segments results in attenuation, which has the potential to limit emergence of

397 reassortant viruses. Conversely, only ~1% of eight-segmented influenza A viruses replicate a full

398 complement of segments within the infected cell, so co-infection is often necessary for successful

399 completion of the viral life cycle41. As co-infected cells are the only ones capable of yielding reassortant

400 progeny, a requirement for co-infection increases the likelihood that reassortment will occur. Progeny

401 resulting from the co-infection of a cell with two viruses bearing incomplete genomes are necessarily

402 reassortant. The rigidity of packaging mechanisms and the prevalence of incomplete genomes in other

403 virus families, such as the Reoviridae, remains incompletely understood, as does the frequency of

404 reassortment in these systems. Utilization of the strategy outlined herein for monitoring reassortment

405 may open up further avenues of study with respect to segmented virus replication mechanisms and

406 population dynamics.

407 408

409 Acknowledgements

410 This work was funded in part by the NIH/NIAID Centers of Excellence for Influenza Research and

411 Surveillance (CEIRS) contract HHSN272201400004C and R01 AI 125258. We thank Bernardo Mainou and

412 Nathan Jacobs for helpful discussion.

413

414

415 Figure Legends

416 Figure 1. Design of variant mutations. Genome segments are indicated by blue (wt) and red (var) bars.

417 The single nucleotide polymorphism is indicated by a star in the variant segment. Vertical lines indicate

418 the 1 kb region (beginning at the start codon) in which the polymorphism was introduced, and the borders

419 of the amplicon used in qPCR and subsequent high resolution melt analysis. Arrows indicate the

420 directionality of the primers used during qPCR. Criteria used in the selection of the variant mutation

421 position are indicated in the box on the lower right.

422

423 Figure 2. Example 384-well plate layouts for high-resolution melt analysis. A) Example plate layout for

424 the analysis of IAV reassortment. Each plate holds 21 unknown samples (indicated by numbers at the top

425 and bottom of each schematic plate), wt and var positive controls (bottom right) and a negative control

426 in which water was loaded in place of cDNA (bottom right). Each of the 8 segments are analyzed in

427 duplicate for each sample, in rows as indicated at the left with segment designations. B) Example plate

428 layout for the analysis of reovirus reassortment. Each plate holds 16 samples (indicated by numbers to

429 the left), and wt and var positive controls (right side of the diagram). Each of the 10 segments are analyzed

430 in duplicated, indicated by segment identification across the top and in wells for positive controls. Since

431 32 isolates are analyzed for reovirus reassortment, two plates must be used.

432

433 Figure 3. Single nucleotide changes do not detectably alter variant virus growth. (A) Pan/99 IAV wild-

434 type and variant multi-cycle growth were analyzed in guinea pigs (N=4 Pan/99wt, N=3 Pan/99var15) over

435 the course of 5 days. (B) T3D mammalian orthoreovirus wild-type and variant virus growth were analyzed

436 under single-cycle conditions in L929 cells over the course of 36 h (N=3 for both viruses). Error bars

437 represent standard deviation.

438

439 Figure 4. Flow cytometry allows for the quantification of infected and co-infected cells in a population.

440 (A) Uninfected cells (left) were used to determine the appropriate gate locations for IAV infected cells

441 (right). Populations of cells infected by a single virus are indicated by the top left- and bottom rightmost

442 gates. Co-infected cells expressing both the HA and 6xHIS epitope tags are shown in the top rightmost

443 gate. (B) Uninfected cells (left) were used to determine the appropriate gate location for reovirus infected

444 cells (right). The population shift indicates 98.6% infected cells divided between two populations,

445 representing high and low levels of viral antigen expression.

446

447 Figure 5. Melt curves allow the determination of parental segment origin. Melt curves on the left

448 indicating relative fluorescent units (RFU) as a function of temperature were used to generate the

449 difference curves on the right, which enabled differentiation of wt and var segments in the clusters. Wild-

450 type (blue) and variant (red) controls were used to determine the parental origins of each segment. Melt

451 curves of two representative segments from IAV (A) and reovirus (B) are shown.

452

453 Figure 6. Reassortment tables provide visual representation of progeny virus genotypes. Each co-

454 infection was performed in triplicate, and 21 (IAV) or 32 (reovirus) plaques were genotyped from each

455 replicate. Blocks of genotypes numbered 1, 2 and 3 represent each replicate co-infection. Each row

456 corresponds to a separate plaque isolate, and each column represents a gene segment (IAV segment

457 order: PB2, PB1, PA, HA, NP, NA, M, NS; Reovirus segment order: L1, L2, L3, M1, M2, M3, S1, S2, S3, S4).

458 Representative data from co-infections performed at a single MOI of both IAV (A) and reovirus (B) are

459 shown. An MOI of 0.6 is shown for IAV, and an MOI of 3.16 is shown for reovirus. The calculated percent

460 reassortment (%R) and the diversity (ED) as measured by Simpson’s index are indicated for each replicate.

461

462 Figure 7. Comparison of infection levels and reassortment. Quantification of infected cells by flow

463 cytometry can be combined with reassortment quantification to give insight into the dependence of

464 reassortment on effective viral dose. (A) Percent reassortment as a function of the percentage of cells in

465 the population infected with Pan/99 IAV, as detected by HA expression in flow cytometry. (B) The effective

466 diversity of Pan/99 isolates after co-infections in A549 cells was determined. Diversity is shown as a

467 function of % infected cells, expressed as % HA-positive (expressing HA-labelled HA protein, 6xHIS-labelled

468 HA protein, or both). Diversity increases more than five-fold from the lowest % infection to the highest.

469

470 References 471 472 473 1. McDonald, S. M.; Aguayo, D.; Gonzalez-Nilo, F. D.; Patton, J. T., Shared and group-specific 474 features of the rotavirus RNA polymerase reveal potential determinants of gene reassortment restriction. 475 J Virol 2009, 83 (12), 6135-48. 476 2. White, M. C.; Lowen, A. C., Implications of segment mismatch for influenza A virus evolution. J 477 Gen Virol 2018, 99 (1), 3-16. 478 3. Villa, M.; Lassig, M., Fitness cost of reassortment in human influenza. PLoS Pathog 2017, 13 (11), 479 e1006685. 480 4. Lubeck, M. D.; Palese, P.; Schulman, J. L., Nonrandom association of parental genes in influenza 481 A virus recombinants. Virology 1979, 95 (1), 269-74. 482 5. Nibert, M. L.; Margraf, R. L.; Coombs, K. M., Nonrandom segregation of parental alleles in reovirus 483 reassortants. J Virol 1996, 70 (10), 7295-300. 484 6. Smith, G. J.; Vijaykrishna, D.; Bahl, J.; Lycett, S. J.; Worobey, M.; Pybus, O. G.; Ma, S. K.; Cheung, 485 C. L.; Raghwani, J.; Bhatt, S.; Peiris, J. S.; Guan, Y.; Rambaut, A., Origins and evolutionary genomics of 486 the 2009 swine-origin H1N1 influenza A epidemic. Nature 2009, 459 (7250), 1122-5. 487 7. Garten, R. J.; Davis, C. T.; Russell, C. A.; Shu, B.; Lindstrom, S.; Balish, A.; Sessions, W. M.; Xu, 488 X.; Skepner, E.; Deyde, V.; Okomo-Adhiambo, M.; Gubareva, L.; Barnes, J.; Smith, C. B.; Emery, S. L.; 489 Hillman, M. J.; Rivailler, P.; Smagala, J.; de Graaf, M.; Burke, D. F.; Fouchier, R. A.; Pappas, C.; Alpuche- 490 Aranda, C. M.; Lopez-Gatell, H.; Olivera, H.; Lopez, I.; Myers, C. A.; Faix, D.; Blair, P. J.; Yu, C.; Keene, 491 K. M.; Dotson, P. D., Jr.; Boxrud, D.; Sambol, A. R.; Abid, S. H.; St George, K.; Bannerman, T.; Moore, A. 492 L.; Stringer, D. J.; Blevins, P.; Demmler-Harrison, G. J.; Ginsberg, M.; Kriner, P.; Waterman, S.; Smole, 493 S.; Guevara, H. F.; Belongia, E. A.; Clark, P. A.; Beatrice, S. T.; Donis, R.; Katz, J.; Finelli, L.; Bridges, C. 494 B.; Shaw, M.; Jernigan, D. B.; Uyeki, T. M.; Smith, D. J.; Klimov, A. I.; Cox, N. J., Antigenic and genetic 495 characteristics of swine-origin 2009 A(H1N1) influenza viruses circulating in humans. Science 2009, 325 496 (5937), 197-201. 497 8. Wittwer, C. T.; Reed, G. H.; Gundry, C. N.; Vandersteen, J. G.; Pryor, R. J., High-resolution 498 genotyping by amplicon melting analysis using LCGreen. Clin Chem 2003, 49 (6 Pt 1), 853-60. 499 9. Palese, P.; Schulman, J. L., Differences in RNA patterns of influenza A viruses. J Virol 1976, 17 (3), 500 876-84. 501 10. Ramig, R. F.; Cross, R. K.; Fields, B. N., Genome RNAs and polypeptides of reovirus serotypes 1, 2, 502 and 3. J Virol 1977, 22 (3), 726-33. 503 11. Rodger, S. M.; Holmes, I. H., Comparison of the Genomes of Simian, Bovine, and Human 504 Rotaviruses by Gel-Electrophoresis and Detection of Genomic Variation among Bovine Isolates. Journal of 505 Virology 1979, 30 (3), 839-846. 506 12. Fields, B. N., Temperature-sensitive mutants of reovirus type 3 features of genetic recombination. 507 Virology 1971, 46 (1), 142-8. 508 13. Kendal, A. P.; Cox, N. J.; Galphin, J. C.; Maassab, H. F., Comparative studies of wild-type and cold- 509 mutant (temperature-sensitive) influenza viruses: independent segregation of temperature-sensitivity of 510 virus replication from temperature-sensitivity of virion transcriptase activity during recombination of 511 mutant A/Ann Arbor/6/60 with wild-type H3N2 strains. J Gen Virol 1979, 44 (2), 443-56. 512 14. Fields, B. N.; Joklik, W. K., Isolation and preliminary genetic and biochemical characterization of 513 temperature-sensitive mutants of reovirus. Virology 1969, 37 (3), 335-42. 514 15. Jackson, S.; Van Hoeven, N.; Chen, L. M.; Maines, T. R.; Cox, N. J.; Katz, J. M.; Donis, R. O., 515 Reassortment between avian H5N1 and human H3N2 influenza viruses in ferrets: a public health risk 516 assessment. J Virol 2009, 83 (16), 8131-40.

517 16. Dlugolenski, D.; Jones, L.; Tompkins, S. M.; Crameri, G.; Wang, L. F.; Tripp, R. A., Bat cells from 518 Pteropus alecto are susceptible to influenza A virus infection and reassortment. Influenza Other Respir 519 Viruses 2013, 7 (6), 900-3. 520 17. Stincarelli, M.; Arvia, R.; De Marco, M. A.; Clausi, V.; Corcioli, F.; Cotti, C.; Delogu, M.; Donatelli, 521 I.; Azzi, A.; Giannecchini, S., Reassortment ability of the 2009 pandemic H1N1 influenza virus with 522 circulating human and avian influenza viruses: public health risk implications. Virus Res 2013, 175 (2), 151- 523 4. 524 18. Dung, T. T. N.; Duy, P. T.; Sessions, O. M.; Sangumathi, U. K.; Phat, V. V.; Tam, P. T. T.; To, N. T. 525 N.; Phuc, T. M.; Hong Chau, T. T.; Chau, N. N. M.; Minh, N. N.; Thwaites, G. E.; Rabaa, M. A.; Baker, S., 526 A universal genome sequencing method for rotavirus A from human fecal samples which identifies 527 segment reassortment and multi-genotype mixed infection. BMC Genomics 2017, 18 (1), 324. 528 19. Buchholz, U. J.; Finke, S.; Conzelmann, K. K., Generation of bovine respiratory syncytial virus 529 (BRSV) from cDNA: BRSV NS2 is not essential for virus replication in tissue culture, and the human RSV 530 leader region acts as a functional BRSV genome promoter. J Virol 1999, 73 (1), 251-9. 531 20. Marshall, N.; Priyamvada, L.; Ende, Z.; Steel, J.; Lowen, A. C., Influenza virus reassortment occurs 532 with high frequency in the absence of segment mismatch. PLoS Pathog 2013, 9 (6), e1003421. 533 21. Tao, H.; Li, L.; White, M. C.; Steel, J.; Lowen, A. C., Influenza A Virus Coinfection through 534 Transmission Can Support High Levels of Reassortment. J Virol 2015, 89 (16), 8453-61. 535 22. Phipps, K. L.; Marshall, N.; Tao, H.; Danzy, S.; Onuoha, N.; Steel, J.; Lowen, A. C., Seasonal H3N2 536 and 2009 Pandemic H1N1 Influenza A Viruses Reassort Efficiently but Produce Attenuated Progeny. J Virol 537 2017, 91 (17). 538 23. Li, Z. N.; Mueller, S. N.; Ye, L.; Bu, Z.; Yang, C.; Ahmed, R.; Steinhauer, D. A., Chimeric influenza 539 virus hemagglutinin proteins containing large domains of the Bacillus anthracis protective antigen: protein 540 characterization, incorporation into infectious influenza viruses, and antigenicity. J Virol 2005, 79 (15), 541 10003-12. 542 24. Brochu-Lafontaine, V.; Lemay, G., Addition of exogenous polypeptides on the mammalian reovirus 543 outer capsid using reverse genetics. J Virol Methods 2012, 179 (2), 342-50. 544 25. White, M. C.; Steel, J.; Lowen, A. C., Heterologous Packaging Signals on Segment 4, but Not 545 Segment 6 or Segment 8, Limit Influenza A Virus Reassortment. J Virol 2017, 91 (11). 546 26. Fodor, E.; Devenish, L.; Engelhardt, O. G.; Palese, P.; Brownlee, G. G.; Garcia-Sastre, A., Rescue 547 of influenza A virus from recombinant DNA. J Virol 1999, 73 (11), 9679-82. 548 27. Steel, J.; Lowen, A. C.; Mubareka, S.; Palese, P., Transmission of influenza virus in a mammalian 549 host is increased by PB2 amino acids 627K or 627E/701N. PLoS Pathog 2009, 5 (1), e1000252. 550 28. Boehme, K. W.; Ikizler, M.; Kobayashi, T.; Dermody, T. S., Reverse genetics for mammalian 551 reovirus. Methods 2011, 55 (2), 109-13. 552 29. Kanai, Y.; Komoto, S.; Kawagishi, T.; Nouda, R.; Nagasawa, N.; Onishi, M.; Matsuura, Y.; 553 Taniguchi, K.; Kobayashi, T., Entirely plasmid-based reverse genetics system for rotaviruses. Proc Natl Acad 554 Sci U S A 2017, 114 (9), 2349-2354. 555 30. Virgin, H. W. t.; Bassel-Duby, R.; Fields, B. N.; Tyler, K. L., Antibody protects against lethal infection 556 with the neurally spreading reovirus type 3 (Dearing). J Virol 1988, 62 (12), 4594-604. 557 31. Furlong, D. B.; Nibert, M. L.; Fields, B. N., Sigma 1 protein of mammalian reoviruses extends from 558 the surfaces of viral particles. J Virol 1988, 62 (1), 246-56. 559 32. Guide for the Care and Use of Laboratory Animals. 8 ed.; The National Academies Press: 560 Washington, D.C., 2011. 561 33. Lowen, A. C.; Mubareka, S.; Tumpey, T. M.; Garcia-Sastre, A.; Palese, P., The guinea pig as a 562 transmission model for human influenza viruses. Proc Natl Acad Sci U S A 2006, 103 (26), 9988-92.

563 34. Zhou, B.; Donnelly, M. E.; Scholes, D. T.; St George, K.; Hatta, M.; Kawaoka, Y.; Wentworth, D. 564 E., Single-reaction genomic amplification accelerates sequencing and vaccine production for classical and 565 Swine origin human influenza a viruses. J Virol 2009, 83 (19), 10309-13. 566 35. Jost, L., Entropy and diversity. Oikos 2006, 113 (2), 363-375. 567 36. Scholtissek, C.; Rohde, W.; Von Hoyningen, V.; Rott, R., On the origin of the human influenza 568 virus subtypes H2N2 and H3N2. Virology 1978, 87 (1), 13-20. 569 37. Li, K. S.; Guan, Y.; Wang, J.; Smith, G. J.; Xu, K. M.; Duan, L.; Rahardjo, A. P.; Puthavathana, P.; 570 Buranathai, C.; Nguyen, T. D.; Estoepangestie, A. T.; Chaisingh, A.; Auewarakul, P.; Long, H. T.; Hanh, 571 N. T.; Webby, R. J.; Poon, L. L.; Chen, H.; Shortridge, K. F.; Yuen, K. Y.; Webster, R. G.; Peiris, J. S., Genesis 572 of a highly pathogenic and potentially pandemic H5N1 influenza virus in eastern Asia. Nature 2004, 430 573 (6996), 209-13. 574 38. Nelson, M. I.; Viboud, C.; Simonsen, L.; Bennett, R. T.; Griesemer, S. B.; St George, K.; Taylor, 575 J.; Spiro, D. J.; Sengamalay, N. A.; Ghedin, E.; Taubenberger, J. K.; Holmes, E. C., Multiple reassortment 576 events in the evolutionary history of H1N1 influenza A virus since 1918. PLoS Pathog 2008, 4 (2), 577 e1000012. 578 39. Zhang, X.; Sun, H.; Cunningham, F. L.; Li, L.; Hanson-Dorr, K.; Hopken, M. W.; Cooley, J.; Long, 579 L. P.; Baroch, J. A.; Li, T.; Schmit, B. S.; Lin, X.; Olivier, A. K.; Jarman, R. G.; DeLiberto, T. J.; Wan, X. F., 580 Tissue tropisms opt for transmissible reassortants during avian and swine influenza A virus co-infection in 581 swine. PLoS Pathog 2018, 14 (12), e1007417. 582 40. Qiao, X.; Qiao, J.; Mindich, L., Stoichiometric packaging of the three genomic segments of double- 583 stranded RNA bacteriophage phi6. Proc Natl Acad Sci U S A 1997, 94 (8), 4074-9. 584 41. Jacobs, N. T.; Onuoha, N. O.; Antia, A.; Antia, R.; Steel, J.; Lowen, A. C., Incomplete influenza A 585 virus genomes are abundant but readily complemented during spatially structured viral spread. bioRxiv 586 2019. 587

588 Table 1: Point mutations used to generate variant viruses

T3D Mammalian Orthoreovirus Pan/99 Influenza A Virus

Segment Polymorphism Segment Polymorphism(s)*

L1 C612T PB2 C354T C360T

L2 C853T PB1 A540G

L3 G481A PA A342G G333A

M1 C919T HA T308C C311A C314T A646T C467G T470A

M2 A650G NP C537T T538A C539G

M3 T702C NA C418G T421A A424C

S1 G312A M G586A

S2 A438G NS C329T C335T A341G

S3 T318C

S4 C383T

589 * Note, although a single nucleotide tide change is sufficient to support HRM genotyping, the Pan/99var15

590 virus contains multiple changes in a number of segments owing to use of alternative genotyping

591 approaches during development of the IAV system.

592

593

594 Table 2: Primers used to generate amplicons for high-resolution melt analysis

T3D Mammalian Orthoreovirus Segment Forward Primer Reverse Primer

L1 570F 624R AAGGTGCCCGATCTGGTAAT GCATAATTGCCCTTTATGGTG

L2 832F 906R GCAACCCGTTACACGCTTAG TAACACCCCCAACCGATATG

L3 451F 539R TCAGAAGCCGATGTCTACCA TGATACCCATGACCACTGCT

M1 839F 923R TTGATGCATTTGCCTTACCA CATCGGCCACATCCACTAC

M2 606F 659R AGAGTGGCTCAAACGTTGCT TCACTACCGACTGCATTGGA

M3 643F 720R GGGATAATGAAGGCTGCTGA ACCGCCCCTCGTTATAGATT

S1 278F 329R GAGCCCTCCAAACAGTTGTC AAGTTGTCCCACTCGAGCAC

S2 415F 488R CTAGCGCGTGATCCAAGATT GTAGGAAATCGGGCCAAAAC

S3 266F 334R GGGATATCCTTCAGACTCGTG CTCATGGTGGATGCTTGATG

S4 323F 391R GGGTATGCTGTCCTTCGTTG ACCTCCCTCAGTACGCACAC

Pan99 IAV Segment Forward Primer Reverse Primer

PB2 322F 414R

TGGAATAGAAATGGACCTGTGA GGTTCCATGTTTTAACCTTTCG

PB1 508F 596R

AGGCTAATAGATTTCCTCAAGGATG ACTCTCCTTTTTCTTTGAAAGTGTG

PA 307F 398R

TGCAACACTACTGGAGCTGAG CTCCTTGTCACTCCAATTTCG

HA 251F 313R

CCTTGATGGAGAAAACTGCAC CAACAAAAAGGTCCCATTCC

NP 482F 571R

CAACATACCAGAGGACAAGAGC ACCTTCTAGGGAGGGTCGAG

NA 386F 461R

TCATGCGATCCTGACAAGTG TGTCATTTGAATGCCTGTTG

M 563F 662R

GTTTTGGCCAGCACTACAGC CCATTTGCCTGGCCTGACTA

NS 252F 342R

ACCTGCTTCGCGATACATAAC AGGGGTCCTTCCACTTTTTG

595

596

Var mutation in first 1kb

F Primer AUG

R Primer • Site of natural variation • A óG or T ó C mutation Amplicon 60-100 bp • Synonymous

Figure 1 bioRxiv preprint doi: https://doi.org/10.1101/708982; this version posted July 22, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

A Plate Layout for IAV

1 2 3 4 5 6 7 8 9 10 11 12 PB2 PB1 PA HA NP NA M NS PB2 PB1 PA HA NP NA M NS 13 14 15 16 17 18 19 20 21 WT VAR Water

B Plate Layout for reovirus L1 L2 L3 M1 M2 M3 S1 S2 S3 S4 VAR WT 1 S3 L1 S3 L1 2 3 S4 L2 S4 L2 4 5 L3 L3 6 7 M1 M1 8 9 M2 M2 10 11 M3 M3 12 13 S1 S1 14 15 S2 S2 16

Figure 2 bioRxiv preprint doi: https://doi.org/10.1101/708982; this version posted July 22, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

A B

Figure 3 bioRxiv preprint doi: https://doi.org/10.1101/708982; this version posted July 22, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

A Pan/99var15 A A - - Co-Infected FITC FITC - - Comp Comp Pan/99wt

Comp-APC-A Comp-APC-A B

Uninfecte d A A - -

FSC FSC T3Dwt

APC-A APC-A

Figure 4 bioRxiv preprint doi: https://doi.org/10.1101/708982; this version posted July 22, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

A Normalized Melt Curve Difference Curve Difference RFU Normalized RFU

B Difference RFU Normalized RFU

Temperature Temperature

Figure 5 bioRxiv preprint doi: https://doi.org/10.1101/708982; this version posted July 22, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

A influenza B reovirus 1 1 %R 66.7 %R 53.3 ED 7.8 ED 6.5

2 2 %R 65.0 %R 60.7 ED 10.3 ED 6.9

3 3

%R 75.0 %R 58.6 ED 11.7 ED 8.2

Figure 6 bioRxiv preprint doi: https://doi.org/10.1101/708982; this version posted July 22, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

A B

Figure 7