Influenza A virus reassortment is strain dependent.

RNA viruses can exchange genetic material during coinfection, an interaction that creates novel strains with implications for viral evolution and public health. Influenza A viral genetic exchange can occur when genome segments from distinct strains reassort in coinfected cells. Predicting potential genomic reassortment between influenza strains has been a long-standing goal. Experimental coinfection studies have shed light on factors that limit or promote reassortment. However, determining the reassortment potential between diverse Influenza A strains has remained elusive. To address this challenge, we developed a high throughput genotyping approach to quantify reassortment among a diverse panel of human influenza virus strains encompassing two pandemics (swine and avian origin), three specific epidemics, and both circulating human subtypes A/H1N1 and A/H3N2. We found that reassortment frequency (the proportion of reassortants generated) is an emergent property of specific pairs of strains where strain identity is a predictor of reassortment frequency. We detect little evidence that antigenic subtype drives reassortment as intersubtype (H1N1xH3N2) and intrasubtype reassortment frequencies were, on average, similar. Instead, our data suggest that certain strains bias the reassortment frequency up or down, independently of the coinfecting partner. We observe that viral productivity is also an emergent property of coinfections, but uncorrelated to reassortment frequency; thus viral productivity is a separate factor affecting the total number of reassortants produced. Assortment of individual segments among progeny and pairwise segment combinations within progeny generally favored homologous combinations. These outcomes were not related to strain similarity or shared subtype but reassortment frequency was closely correlated to the proportion of both unique genotypes and of progeny with heterologous pairwise segment combinations. We provide experimental evidence that viral genetic exchange is potentially an individual social trait subject to natural selection, which implies the propensity for reassortment is not evenly shared among strains. This study highlights the need for research incorporating diverse strains to discover the traits that shift the reassortment potential to realize the goal of predicting influenza virus evolution resulting from segment exchange.

The future of zoonotic risk prediction.

In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization, scientists may increasingly rely on data-driven rubrics or machine learning models that learn from known zoonoses to identify which animal pathogens could someday pose a threat to global health. We synthesize the findings of an interdisciplinary workshop on zoonotic risk technologies to answer the following questions. What are the prerequisites, in terms of open data, equity and interdisciplinary collaboration, to the development and application of those tools? What effect could the technology have on global health? Who would control that technology, who would have access to it and who would benefit from it? Would it improve pandemic prevention? Could it create new challenges? This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.

TEMPORAL AND SPATIAL PATTERNS IN CANINE DISTEMPER VIRUS CASES IN WILDLIFE DIAGNOSED AT THE SOUTHEASTERN COOPERATIVE WILDLIFE DISEASE STUDY, 1975-2019.

Canine distemper is a high-impact disease of many mammal species and has caused substantial carnivore population declines. Analysis was conducted on passive surveillance data of canine distemper (CDV)-positive wild mammal cases submitted to the Southeastern Cooperative Wildlife Disease Study, Athens, Georgia, US, between January 1975 and December 2019. Overall, 964 cases from 17 states were CDV positive, including 646 raccoons (Procyon lotor), 254 gray foxes (Urocyon cinereoargenteus), 33 striped skunks (Mephitis mephitis), 18 coyotes (Canis latrans), four red foxes (Vulpes vulpes), three gray wolves (Canis lupus), three American black bears (Ursus americanus), two American mink (Mustela vison), and one long-tailed weasel (Mustela frenata). Raccoon and gray fox case data from the state of Georgia (n=441) were selected for further analysis. Autoregressive integrated moving average models were developed predicting raccoon and gray fox case numbers. The best-performing model for gray foxes used numbers of gray fox CDV cases from the previous 2 mo and of raccoon cases in the present month to predict the numbers of gray fox cases in the present month. The best-performing model for raccoon prediction used numbers of raccoon CDV cases from the previous month and of gray fox cases in the present month and previous 2 mo to predict numbers of raccoon cases in the present month. Temporal trends existed in CDV cases for both species, with cases more likely to occur during the breeding season. Spatial clustering of cases was more likely to occur in areas of medium to high human population density; fewer cases occurred in both the most densely populated and sparsely populated areas. This pattern was most prominent for raccoons, which may correspond to high transmission rates in suburban areas, where raccoon population densities are probably highest, possibly because of a combination of suitable habitat and supplemental resources.

mSphere of Influence: That's Racist-COVID-19, Biological Determinism, and the Limits of Hypotheses.

Kishana Taylor works in the field of virology. In this mSphere of Influence article, she reflects on the personal impact of "Racial health disparities and COVID-19 - caution and context" by Merlin Chowkwanyun and Adolph L. Reed, Jr. (N Engl J Med 383:201-203, 2020, https://doi.org/10.1056/NEJMp2012910) and "A hypothesis is a liability" by Itai Yanai and Martin Lercher (Genome Biol 21:231, 2020, https://doi.org/10.1186/s13059-020-02133-w) and how it became part of the mission for Black In Microbiology Week.

Effects of concentrated poultry operations and cropland manure application on antibiotic resistant Escherichia coli and nutrient pollution in Chesapeake Bay watersheds.

Manure from poultry operations is typically applied to nearby cropland and may affect nutrient loading and the spread of antibiotic resistance (ABR). We analyzed the concentrations of nitrogen and phosphorus and the occurrence of ABR in Escherichia coli (E. coli) and extra-intestinal pathogenic E. coli isolates from streams draining 15 small (<19 km2) watersheds of the Chesapeake Bay with contrasting levels of concentrated poultry operations. Total nitrogen and nitrate plus nitrite concentrations increased with poultry barn density with concentrations two and three times higher, respectively, in watersheds with the highest poultry barn densities compared to those without poultry barns. Analysis of N and O isotopes in nitrate by mass spectrometry showed an increase in the proportion of 15N associated with an increase in barn density, suggesting that the nitrate associated with poultry barns originated from manure. Phosphorus concentrations were not correlated with barn density. Antibiotic susceptibility testing of putative E. coli isolates was conducted using the disk diffusion method for twelve clinically important antibiotics. Of the isolates tested, most were completely susceptible (67%); 33% were resistant to at least one antibiotic, 24% were resistant to ampicillin, 13% were resistant to cefazolin, and 8% were multi-drug resistant. Resistance to three cephalosporin drugs was positively associated with an index of manure exposure estimated from poultry barn density and proportion of cropland in a watershed. The proportion of E. coli isolates resistant to cefoxitin, cefazolin, and ceftriaxone, broad-spectrum antibiotics important in human medicine, increased by 18.9%, 16.9%, and 6.2%, respectively, at the highest estimated level of manure exposure compared to watersheds without manure exposure. Our results suggest that comparisons of small watersheds could be used to identify geographic areas where remedial actions may be needed to reduce nutrient pollution and the public health risks of ABR bacteria.

An Embryonated Egg Transmission Model for Epizootic Hemorrhagic Disease Virus.

Epizootic hemorrhagic disease virus (EHDV) is a vector-borne orbivirus of ruminants; in North America there are three serotypes (EHDV-1, -2, and -6) and these primarily affect white-tailed deer (Odocoilus virginianus). EHDV is vectored by biting midges, Culicoides spp. Embryonated chicken eggs (ECE) have recently been used as an experimental host to investigate the vector competence of Australian Culicoides spp. for bluetongue serotype virus 1 and 23. In this study, we evaluated the use of the ECE model to determine its applicability for evaluating vector competence related to transmission of North American EHDV serotypes. We demonstrated that all three North American EHDV serotypes were able to replicate in ECEs and be transmitted from infected ECEs to Culicoides sonorensis Wirth & Jones. In addition, we were able to complete the transmission cycle from infected C. sonorensis to uninfected ECEs for EHDV-1 and -2.

Differentiation of Salmonella strains from the SARA, SARB and SARC reference collections by using three genes PCR-RFLP and the 2100 Agilent Bioanalyzer.

Rapid molecular typing methods are important tools in surveillance and outbreak investigations of human Salmonella infections. Here we described the development of a three-genes PCR-RFLP typing method for the differentiation of Salmonella species, subspecies and serovars using the Agilent 2100 Bioanalyzer. The fliC, gnd, and mutS genes were PCR-amplified in 160 Salmonella strains representing the two Salmonella species, six subspecies, and 41 different serovars of S. enterica subspecies enterica. PCR products were individually cut with two different restriction enzymes and the resulting 930 restriction patterns were collected using the Agilent 2100 Bioanalyzer followed by cluster analysis. Both species of Salmonella were differentiated by conventional PCR. All of S. bongori tested were gnd PCR negative due to a mismatch at the 3'-end in one the PCR primers. Salmonella subspecies were differentiated into third-teen homogeneous groups representing each of the six subspecies by cluster analysis of restriction patterns generated from the mutS gene cut with AciI. S. enterica subspecies enterica serovars were further differentiated by the combination of the three target genes and five out the six sets of restriction patterns with a discriminatory power of 0.9725 by cluster analysis. The combined RFLP results of five sets of restriction patterns allowed us to assign each of the 160 strains to one of 128 restriction types. During inoculation studies we were able to identify S. Saintpaul and Typhimurium from 24 h pre-enrichment samples using the described method. The use of fliC, gnd, and mutS PCR-RFLP with the Agilent 2100 Bioanalyzer can provide an accessible and automated alternative method for differentiation of Salmonella pathogens.