Diagnostic investigation of avian reovirus field variants circulating in broiler chickens in Pennsylvania of United States between 2017 and 2022.

Avian reovirus (ARV) has been continuously affecting the poultry industry in Pennsylvania (PA) in recent years. This report provides our diagnostic investigation on monitoring ARV field variants from broiler chickens in Pennsylvania. Genomic characterization findings of 72 ARV field isolates obtained from broiler cases during the last 6 years indicated that six distinct cluster variant strains (genotype I-VI), which were genetically diverse and distant from the vaccine and vaccine-related field strains, continuously circulated in PA poultry. Most of the variants clustered within genotype V (24/72, 33.3%), followed by genotype II (16/72, 22.2%), genotype IV (13/72, 18.1%), genotype III (13/72, 18.1%), genotype VI (05/72, 6.94%), and genotype I (1/72, 1.38%). The amino acid identity between 72 field variants and the vaccine strains (1133, 1733, 2408, 2177) varied from 45.3% to 99.7%, while the difference in amino acid counts ranged from 1-164. Among the field variants, the amino acid identity and count difference ranged from 43.3% to 100% and 0 to 170, respectively. Variants within genotype V had maximum amino acid identity (94.7-100%), whereas none of the variants within genotypes II and VI were alike. These findings indicate the continuing occurrence of multiple ARV genotypes in the environment.

Identification, 16S rRNA-based characterization, and antimicrobial profile of Gallibacterium isolates from broiler and layer chickens.

Gallibacterium spp., particularly G. anatis, have received much attention as poultry pathogens in recent years. We report here the presence and antimicrobial resistance profile of 69 Gallibacterium isolates obtained from 2,204 diagnostic submissions of broiler and layer chickens in 2019-2021. Gallibacterium-positive chickens had lesions primarily in the respiratory tract, reproductive tract, and related serosal surfaces. Gallibacterium spp. were initially identified based on their typical cultural characteristics on blood agar. The isolates were confirmed by a genus-specific PCR spanning 16S-23S rRNA and MALDI-TOF mass spectrometry. Phylogenetic analysis based on 16S rRNA gene sequence revealed distinct clades. Of the 69 isolates, 68 clustered with the reference strains of G. anatis and 1 with Gallibacterium genomospecies 1 and 2. Antimicrobial susceptibility testing of 58 of the 69 isolates by a MIC method showed variable responses to antimicrobials. The isolates were all susceptible to enrofloxacin, ceftiofur, florfenicol, and gentamicin. There was a high level of susceptibility to trimethoprim-sulfamethoxazole (98.0%), streptomycin (98.0%), amoxicillin (84.0%), sulfadimethoxine (71.0%), and neomycin (71.0%). All of the isolates were resistant to tylosin. There was resistance to penicillin (98.0%), erythromycin (95.0%), clindamycin (94.0%), novobiocin (90.0%), tetracycline (88.0%), oxytetracycline (76.0%), and sulfathiazole (53.0%). A high rate of intermediate susceptibility was observed for spectinomycin (67.0%) and sulfathiazole (40.0%). Our findings indicate a potential role of G. anatis as an important poultry pathogen and cause of subsequent disease, alone or in combination with other pathogens. Continuous monitoring and an antimicrobial susceptibility assay are recommended for effective treatment and disease control.

Genetic characterization of a novel pheasant-origin orthoreovirus using Next-Generation Sequencing.

A field isolate (Reo/SDWF /Pheasant/17608/20) of avian orthoreovirus (ARV), isolated from a flock of game-pheasants in Weifang, Shandong Province, was genetically characterized being a field variant or novel strain in our recent research studies in conducting whole genome sequencing by using Next-Generation Sequencing (NGS) technique on Illumina MiSeq platform. Among a total of 870,197 35-151-mer sequencing reads, 297,711 reads (34.21%) were identified as ARV sequences. The de novo assembly of the ARV reads resulted in generation of 10 ARV-related contigs with the average sequencing coverage from 1390× to 1977× according to 10 ARV genome segments. The complete genomes of this pheasant-origin ARV (Reo/SDWF /Pheasant/17608/20) were 23,495 bp in length and consist of 10 dsRNA segments ranged from 1192 bp (S4) to 3958 bp (L1) encoding 12 viral proteins. Sequence comparison between the SDWF17608 and classic ARV reference strains revealed that 58.1-100% nucleotide (nt) identities and 51.4-100% amino acid (aa) identities were in genome segment coding genes. The 10 RNA segments had conversed termini at 5' (5'-GCUUUU) and 3' (UCAUC-3') side, which were identical to the most published ARV strains. Phylogenetic analysis revealed that this pheasant ARV field variant was closely related with chicken ARV strains in 7 genome segment genes, but it possessed significant sequence divergence in M1, M3 and S2 segments. These findings suggested that this pheasant-origin field variant was a divergent ARV strain and was likely originated from reassortments between different chicken ARV strains.

Accurate virus identification with interpretable Raman signatures by machine learning.

Rapid identification of newly emerging or circulating viruses is an important first step toward managing the public health response to potential outbreaks. A portable virus capture device, coupled with label-free Raman spectroscopy, holds the promise of fast detection by rapidly obtaining the Raman signature of a virus followed by a machine learning (ML) approach applied to recognize the virus based on its Raman spectrum, which is used as a fingerprint. We present such an ML approach for analyzing Raman spectra of human and avian viruses. A convolutional neural network (CNN) classifier specifically designed for spectral data achieves very high accuracy for a variety of virus type or subtype identification tasks. In particular, it achieves 99% accuracy for classifying influenza virus type A versus type B, 96% accuracy for classifying four subtypes of influenza A, 95% accuracy for differentiating enveloped and nonenveloped viruses, and 99% accuracy for differentiating avian coronavirus (infectious bronchitis virus [IBV]) from other avian viruses. Furthermore, interpretation of neural net responses in the trained CNN model using a full-gradient algorithm highlights Raman spectral ranges that are most important to virus identification. By correlating ML-selected salient Raman ranges with the signature ranges of known biomolecules and chemical functional groups­for example, amide, amino acid, and carboxylic acid­we verify that our ML model effectively recognizes the Raman signatures of proteins, lipids, and other vital functional groups present in different viruses and uses a weighted combination of these signatures to identify viruses.

Identification of 6 gene markers for survival prediction in osteosarcoma cases based on multi-omics analysis.

Multiple-omics sequencing information with high-throughput has laid a solid foundation to identify genes associated with cancer prognostic process. Multiomics information study is capable of revealing the cancer occurring and developing system according to several aspects. Currently, the prognosis of osteosarcoma is still poor, so a genetic marker is needed for predicting the clinically related overall survival result. First, Office of Cancer Genomics (OCG Target) provided RNASeq, copy amount variations information, and clinically related follow-up data. Genes associated with prognostic process and genes exhibiting copy amount difference were screened in the training group, and the mentioned genes were integrated for feature selection with least absolute shrinkage and selection operator (Lasso). Eventually, effective biomarkers received the screening process. Lastly, this study built and demonstrated one gene-associated prognosis mode according to the set of the test and gene expression omnibus validation set; 512 prognosis-related genes (P < 0.01), 336 copies of amplified genes (P < 0.05), and 36 copies of deleted genes (P < 0.05) were obtained, and those genes of the mentioned genomic variants display close associations with tumor occurring and developing mechanisms. This study generated 10 genes for candidates through the integration of genomic variant genes as well as prognosis-related genes. Six typical genes (i.e. MYC, CHIC2, CCDC152, LYL1, GPR142, and MMP27) were obtained by Lasso feature selection and stepwise multivariate regression study, many of which are reported to show a relationship to tumor progressing process. The authors conducted Cox regression study for building 6-gene sign, i.e. one single prognosis-related element, in terms of cases carrying osteosarcoma. In addition, the samples were able to be risk stratified in the training group, test set, and externally validating set. The AUC of five-year survival according to the training group and validation set reached over 0.85, with superior predictive performance as opposed to the existing researches. Here, 6-gene sign was built to be new prognosis-related marking elements for assessing osteosarcoma cases' surviving state.

Rapid Size-Based Isolation of Extracellular Vesicles by Three-Dimensional Carbon Nanotube Arrays.

Recent discoveries reveal that extracellular vesicles (EVs) play an important role in transmitting signals. Although this emerging transcellular pathway enables a better understanding of neural communication, the lack of techniques for effectively isolating EVs impedes their studies. Herein, we report an emergent high-throughput platform consisting of three-dimensional carbon nanotube arrays that rapidly capture different EVs based on their sizes, without any labels. More importantly, this label-free capture maintains the integrity of the EVs when they are excreted from a host cell, thus allowing comprehensive downstream analyses using conventional approaches. To study neural communication, we developed a stamping technique to construct a gradient of nanotube herringbone arrays and integrated them into a microdevice that allowed us processing of a wide range of sample volumes, microliters to milliliters, in several minutes through a syringe via manual hand pushing and without any sample preparation. This microdevice successfully captured and separated EVs excreted from glial cells into subgroups according to their sizes. During capture, this technology preserved the structural integrity and originality of the EVs that enabled us to monitor and follow internalization of EVs of different sizes by neurons and cells. As a proof of concept, our results showed that smaller EVs (∼80 nm in diameter) have a higher uptake efficiency compared to larger EVs (∼300 nm in diameter). In addition, after being internalized, small EVs could enter endoplasmic reticulum and Golgi but not the largest ones. Our platform significantly shortens sample preparation, allows the profiling of the different EVs based on their size, and facilitates the understanding of extracellular communication. Thus, it leads to early diagnostics and the development of novel therapeutics for neurological diseases.

A rapid and label-free platform for virus capture and identification from clinical samples.

Emerging and reemerging viruses are responsible for a number of recent epidemic outbreaks. A crucial step in predicting and controlling outbreaks is the timely and accurate characterization of emerging virus strains. We present a portable microfluidic platform containing carbon nanotube arrays with differential filtration porosity for the rapid enrichment and optical identification of viruses. Different emerging strains (or unknown viruses) can be enriched and identified in real time through a multivirus capture component in conjunction with surface-enhanced Raman spectroscopy. More importantly, after viral capture and detection on a chip, viruses remain viable and get purified in a microdevice that permits subsequent in-depth characterizations by various conventional methods. We validated this platform using different subtypes of avian influenza A viruses and human samples with respiratory infections. This technology successfully enriched rhinovirus, influenza virus, and parainfluenza viruses, and maintained the stoichiometric viral proportions when the samples contained more than one type of virus, thus emulating coinfection. Viral capture and detection took only a few minutes with a 70-fold enrichment enhancement; detection could be achieved with as little as 102 EID50/mL (50% egg infective dose per microliter), with a virus specificity of 90%. After enrichment using the device, we demonstrated by sequencing that the abundance of viral-specific reads significantly increased from 4.1 to 31.8% for parainfluenza and from 0.08 to 0.44% for influenza virus. This enrichment method coupled to Raman virus identification constitutes an innovative system that could be used to quickly track and monitor viral outbreaks in real time.

Smartphone-Based Point-of-Care Microfluidic Platform Fabricated with a ZnO Nanorod Template for Colorimetric Virus Detection.

Viruses pose serious infectious disease threats to humans and animals. To significantly decrease the mortality and morbidity caused by virus infections, there is an urgent need of sensitive and rapid point-of-care platforms for virus detection, especially in low-resource settings. Herein, we developed a smartphone-based point-of-care platform for highly sensitive and selective detection of the avian influenza virus based on nanomaterial-enabled colorimetric detection. The 3D nanostructures, which serve as a scaffold for antibody conjugation to capture the avian influenza virus, are made on PDMS herringbone structures with a ZnO nanorod template. After virus capture, the on-chip gold nanoparticle-based colorimetric reaction allows virus detection by naked eyes with a detection limit of 2.7 × 104 EID50/mL, which is one order of magnitude better than that of conventional fluorescence-based ELISA. Furthermore, a smartphone imaging system with data processing capability further improves the detection limit, reaching down to 8 × 103 EID50/mL. The entire virus capture and detection process can be completed in 1.5 h. We envision that this point-of-care microfluidic system integrated with smartphone imaging and colorimetric detection would provide a fast, cheap, sensitive, and user-friendly platform for virus detection in low-resource settings.

A Portable Device Integrated with Aligned Carbon Nanotubes for Sensitive Virus Capture and Detection.

Point-of-care virus diagnosis is highly desirable in worldwide infectious disease control. Here we report a hand-held device for capturing viruses by applying physical size based exclusion inside a point-of-care device integrated with vertically aligned carbon nanotube (VACNT) nanostructures to achieve label-free and high throughput virus capture. The microfluidic device is constructed from a VACNT channel wall synthesized bottom-up via chemical vapor deposition (CVD). The VACNT has ~117 nm average gap size and ~97& porosity. By bonding with a polydimethylsiloxane (PDMS) cover sealing the top, the aqueous sample containing virus particles filter through the VACNT channel wall under negative pressure applied at the outlet end. We have demonstrated that the device is capable of filtering 50 µL of PBS containing ~6.3 × 104 counts of lentivirus particles in 10 minutes with 97& of capture efficiency, quantified by the cell infectious titration technique.

Light-Emitting Transition Metal Dichalcogenide Monolayers under Cellular Digestion.

2D materials cover a wide spectrum of electronic properties. Their applications are extended from electronic, optical, and chemical to biological. In terms of biomedical uses of 2D materials, the interactions between living cells and 2D materials are of paramount importance. However, biointerfacial studies are still in their infancy. This work studies how living organisms interact with transition metal dichalcogenide monolayers. For the first time, cellular digestion of tungsten disulfide (WS2 ) monolayers is observed. After digestion, cells intake WS2 and become fluorescent. In addition, these light-emitting cells are not only viable, but also able to pass fluorescent signals to their progeny cells after cell division. By combining synthesis of 2D materials and a cell culturing technique, a procedure for monitoring the interactions between WS2 monolayers and cells is developed. These observations open up new avenues for developing novel cellular labeling and imaging approaches, thus triggering further studies on interactions between 2D materials and living organisms.

A Nanostructured Microfluidic Immunoassay Platform for Highly Sensitive Infectious Pathogen Detection.

Rapid and simultaneous detection of multiple potential pathogens by portable devices can facilitate early diagnosis of infectious diseases, and allow for rapid and effective implementation of disease prevention and treatment measures. The development of a ZnO nanorod integrated microdevice as a multiplex immunofluorescence platform for highly sensitive and selective detection of avian influenza virus (AIV) is described. The 3D morphology and unique optical property of the ZnO nanorods boost the detection limit of the H5N2 AIV to as low as 3.6 × 103 EID50 mL-1 (EID50 : 50% embryo infectious dose), which is ≈22 times more sensitive than conventional enzyme-linked immunosorbent assay. The entire virus capture and detection process could be completed within 1.5 h with excellent selectivity. Moreover, this microfluidic biosensor is capable of detecting multiple viruses simultaneously by spatial encoding of capture antibodies. One prominent feature of the device is that the captured H5N2 AIV can be released by simply dissolving ZnO nanorods under slightly acidic environment for subsequent off-chip analyses. As a whole, this platform provides a powerful tool for rapid detection of multiple pathogens, which may extent to the other fields for low-cost and convenient biomarker detection.

Label-Free Virus Capture and Release by a Microfluidic Device Integrated with Porous Silicon Nanowire Forest.

Viral diseases are perpetual threats to human and animal health. Detection and characterization of viral pathogens require accurate, sensitive, and rapid diagnostic assays. For field and clinical samples, the sample preparation procedures limit the ultimate performance and utility of the overall virus diagnostic protocols. This study presents the development of a microfluidic device embedded with porous silicon nanowire (pSiNW) forest for label-free size-based point-of-care virus capture in a continuous curved flow design. The pSiNW forests with specific interwire spacing are synthesized in situ on both bottom and sidewalls of the microchannels in a batch process. With the enhancement effect of Dean flow, this study demonstrates that about 50% H5N2 avian influenza viruses are physically trapped without device clogging. A unique feature of the device is that captured viruses can be released by inducing self-degradation of the pSiNWs in physiological aqueous environment. About 60% of captured viruses can be released within 24 h for virus culture, subsequent molecular diagnosis, and other virus characterization and analyses. This device performs viable, unbiased, and label-free virus isolation and release. It has great potentials for virus discovery, virus isolation and culture, functional studies of virus pathogenicity, transmission, drug screening, and vaccine development.

Tunable and label-free virus enrichment for ultrasensitive virus detection using carbon nanotube arrays.

Viral infectious diseases can erupt unpredictably, spread rapidly, and ravage mass populations. Although established methods, such as polymerase chain reaction, virus isolation, and next-generation sequencing have been used to detect viruses, field samples with low virus count pose major challenges in virus surveillance and discovery. We report a unique carbon nanotube size-tunable enrichment microdevice (CNT-STEM) that efficiently enriches and concentrates viruses collected from field samples. The channel sidewall in the microdevice was made by growing arrays of vertically aligned nitrogen-doped multiwalled CNTs, where the intertubular distance between CNTs could be engineered in the range of 17 to 325 nm to accurately match the size of different viruses. The CNT-STEM significantly improves detection limits and virus isolation rates by at least 100 times. Using this device, we successfully identified an emerging avian influenza virus strain [A/duck/PA/02099/2012(H11N9)] and a novel virus strain (IBDV/turkey/PA/00924/14). Our unique method demonstrates the early detection of emerging viruses and the discovery of new viruses directly from field samples, thus creating a universal platform for effectively remediating viral infectious diseases.

Rapid detection of avian influenza virus H5N1 in chicken tracheal samples using an impedance aptasensor with gold nanoparticles for signal amplification.

Highly pathogenic avian influenza virus H5N1 is a continuous threat to public health and poultry industry. The recurrence of the H5N1 led us to develop a robust, specific, and rapid detection method for the virus. In this study, an impedance aptasensor was developed for the virus detection using specific H5N1 aptamer and a gold interdigitated microelectrode. Streptavidin was immobilized on the microelectrode surface and biotin labeled H5N1 aptamer was bound to the immobilized streptavidin. The microelectrode was blocked with the polyethylene glycol and the bound aptamer captured the virus. The impedance change caused by the captured virus was measured using an impedance analyzer. To enhance impedance signal, a nanoparticle-based amplifier was designed and implemented by forming a network-like gold nanoparticles/H5N1-aptamer/thiocyanuric acid. The detection limit of the impedance aptasensor was 0.25 HAU for the pure virus and 1 HAU for the tracheal chicken swab samples spiked with the H5N1 virus. The detection time of aptasensor without employing the amplifier was less than an hour. The amplifier increased impedance by a 57-fold for the 1 HAU samples. Only negligible impedance change was observed for non-target viruses such as H5N2, H5N3, H7N2, H1N1, and H2N2. This aptasensor provides a foundation for the development of a portable aptasensor instrument.

Detection and characterization of two co-infection variant strains of avian orthoreovirus (ARV) in young layer chickens using next-generation sequencing (NGS).

Using next-generation sequencing (NGS) for full genomic characterization studies of the newly emerging avian orthoreovirus (ARV) field strains isolated in Pennsylvania poultry, we identified two co-infection ARV variant strains from one ARV isolate obtained from ARV-affected young layer chickens. The de novo assembly of the ARV reads generated 19 contigs of two different ARV variant strains according to 10 genome segments of each ARV strain. The two variants had the same M2 segment. The complete genomes of each of the two variant strains were 23,493 bp in length, and 10 dsRNA segments ranged from 1192 bp (S4) to 3958 bp (L1), encoding 12 viral proteins. Sequence comparison of nucleotide (nt) and amino acid (aa) sequences of all 10 genome segments revealed 58.1-100% and 51.4-100% aa identity between the two variant strains, and 54.3-89.4% and 49.5-98.1% aa identity between the two variants and classic vaccine strains. Phylogenetic analysis revealed a moderate to significant nt sequence divergence between the two variant and ARV reference strains. These findings have demonstrated the first naturally occurring co-infection of two ARV variants in commercial young layer chickens, providing scientific evidence that multiple ARV strains can be simultaneously present in one host species of chickens.

Whole genome alignment based one-step real-time RT-PCR for universal detection of avian orthoreoviruses of chicken, pheasant and turkey origins.

Newly emerging avian orthoreovirus (ARV) variants have been continuously detected in Pennsylvania poultry since 2011. In this paper, we report our recent diagnostic assay development of one-step real-time RT-PCR (rRT-PCR) for the rapid and universal detection of all ARVs or reference strains of chicken, pheasant and turkey origins and six σC genotypes of the newly emerging field ARV variants in Pennsylvania (PA) poultry. Primers and probes for the rRT-PCR were designed from the conserved region of the M1 genome segment 5' end based on the whole-genome alignment of various ARV strains, including six field variants or novel strains obtained in PA poultry. The detection limit of the newly developed rRT-PCR for ARV was as low as 10 copies/reaction of viral RNA, and 10(0.50)-10(0.88) tissue culture infectious dose (TCID50)/100 µL of viruses. This new rRT-PCR detected all six σC genotypes from the 66 ARV field variant strains and reference strains tested in this study. There were no cross-reactions with other avian viruses. Reproducibility of the assay was confirmed by intra- and inter-assay tests with variability from 0.12% to 2.19%. Sensitivity and specificity of this new rRT-PCR for ARV were achieved at 100% and 88%, respectively, in comparison with virus isolation as the "gold standard" in testing poultry tissue specimen.

Isolation and molecular characterization of newly emerging avian reovirus variants and novel strains in Pennsylvania, USA, 2011-2014.

Avian reovirus (ARV) infections of broiler and turkey flocks have caused significant clinical disease and economic losses in Pennsylvania (PA) since 2011. Most of the ARV-infected birds suffered from severe arthritis, tenosynovitis, pericarditis and depressed growth or runting-stunting syndrome (RSS). A high morbidity (up to 20% to 40%) was observed in ARV-affected flocks, and the flock mortality was occasionally as high as 10%. ARV infections in turkeys were diagnosed for the first time in PA in 2011. From 2011 to 2014, a total of 301 ARV isolations were made from affected PA poultry. The molecular characterization of the Sigma C gene of 114 field isolates, representing most ARV outbreaks, revealed that only 21.93% of the 114 sequenced ARV isolates were in the same genotyping cluster (cluster 1) as the ARV vaccine strains (S1133, 1733, and 2048), whereas 78.07% of the sequenced isolates were in genotyping clusters 2, 3, 4, 5, and 6 (which were distinct from the vaccine strains) and represented newly emerging ARV variants. In particular, genotyping cluster 6 was a new ARV genotype that was identified for the first time in 10 novel PA ARV variants of field isolates.

An Impedance Aptasensor with Microfluidic Chips for Specific Detection of H5N1 Avian Influenza Virus.

In this research a DNA aptamer, which was selected through SELEX (systematic evolution of ligands by exponential enrichment) to be specific against the H5N1 subtype of the avian influenza virus (AIV), was used as an alternative reagent to monoclonal antibodies in an impedance biosensor utilizing a microfluidics flow cell and an interdigitated microelectrode for the specific detection of H5N1 AIV. The gold surface of the interdigitated microelectrode embedded in a microfluidics flow cell was modified using streptavidin. The biotinylated aptamer against H5N1 was then immobilized on the electrode surface using biotin-streptavidin binding. The target virus was captured on the microelectrode surface, causing an increase in impedance magnitude. The aptasensor had a detection time of 30 min with a detection limit of 0.0128 hemagglutinin units (HAU). Scanning electron microscopy confirmed the binding of the target virus onto the electrode surface. The DNA aptamer was specific to H5N1 and had no cross-reaction to other subtypes of AIV (e.g., H1N1, H2N2, H7N2). The newly developed aptasensor offers a portable, rapid, low-cost alternative to current methods with the same sensitivity and specificity.

Genomic characterization of a novel avian arthritis orthoreovirus variant by next-generation sequencing.

By using next-generation sequencing (NGS) technology, we have identified a divergent avian orthoreovirus (ARV) field variant (Reo/PA/Broiler/15511/13, or PA15511), isolated from broiler chickens with viral arthritis in Pennsylvania in 2013. The complete genome of the PA15511 field strain was 23,495 bp in length with 10 dsRNA segments encoding 12 viral proteins. The lengths of the genomic segments ranged from 1192 bp (S4) to 3958 bp (L1). Genomic analysis has revealed that this virus is distinct from reference ARV strains and meets criteria for a new or novel strain.

Genomic characterization of a turkey reovirus field strain by Next-Generation Sequencing.

The genome of a turkey arthritis reovirus (TARV) field strain (Reo/PA/Turkey/22342/13), isolated from a turkey flock in Pennsylvania (PA) in 2013, has been sequenced using Next-Generation Sequencing (NGS) on the Illumina MiSeq platform. The genome of the PA TARV field strain was 23,496bp in length with 10 dsRNA segments encoding 12 viral proteins. The lengths of the genomic segments ranged from 1192bp (S4) to 3959bp (L1). The 5' and 3' conserved terminal sequences of the PA TARV field strain were similar to the two Minnesota (MN) TARVs (MN9 and MN10) published recently and avian orthoreovirus (ARV) reference strains. Phylogenetic analysis of the nucleotide sequences of all 10 genome segments revealed that there was a low to significant nucleotide sequence divergence between the PA TARV field strain and reference TARV and ARV strains. Analysis of the PA TARV sequence indicates that this PA TARV field strain is a unique strain and is different from the TARV MN9 or MN10 in M2 segment genes and ARV S1133 vaccine strain.