We have surveyed avian influenza virus (AIV) genomes from live poultry markets within China since 2014. Here we present a total of 16,091 samples that were collected from May 2016 to February 2019 in 23 provinces and municipalities in China. We identify 2048 AIV-positive samples and perform next generation sequencing. AIV-positive rates (12.73%) from samples had decreased substantially since 2016, compared to that during 2014–2016 (26.90%). Additionally, H9N2 has replaced H5N6 and H7N9 as the dominant AIV subtype in both chickens and ducks. Notably, novel reassortants and variants continually emerged and disseminated in avian populations, including H7N3, H9N9, H9N6 and H5N6 variants. Importantly, almost all of the H9 AIVs and many H7N9 and H6N2 strains prefer human-type receptors, posing an increased risk for human infections. In summary, our nation-wide surveillance highlights substantial changes in the circulation of AIVs since 2016, which greatly impacts the prevention and control of AIVs in China and worldwide.

Avian Influenza (AI) is a complex but still poorly understood disease; specifically when it comes to reservoirs, co-infections, connectedness and wider landscape perspectives. Low pathogenic (Low-path LP) AI in chickens caused by less virulent strains of AI viruses (AIVs)—when compared with highly pathogenic AIVs (HPAIVs)—are not even well-described yet or known how they contribute to wider AI and immune system issues. Co-circulation of LPAIVs with HPAIVs suggests their interactions in their ecological aspects. Here we show for the Pacific Rim an international approach how to data mine and model-predict LP AI and its ecological niche with machine learning and open access data sets and geographic information systems (GIS) on a 5 km pixel size for best-possible inference. This is based on the best-available data on the issue (~ 40,827 records of lab-analyzed field data from Japan, Russia, Vietnam, Mongolia, Alaska and Influenza Research Database (IRD) and U.S. Department of Agriculture (USDA) database sets, as well as 19 GIS data layers). We sampled 157 hosts and 110 low-path AIVs with 32 species as drivers. The prevalence across low-path AIV subtypes is dominated by Muscovy ducks, Mallards, Whistling Swans and gulls also emphasizing industrial impacts for the human-dominated wildlife contact zone. This investigation sets a good precedent for the study of reservoirs, big data mining, predictions and subsequent outbreaks of HPAI and other pandemics.

In the absence of virus-targeting small-molecule drugs approved for the treatment and prevention of COVID-19, broadening the repertoire of potent SARS-CoV-2-neutralizing antibodies represents an important area of research in response to the ongoing pandemic. Systematic analysis of such antibodies and their combinations can be particularly instrumental for identification of candidates that may prove resistant to the emerging viral escape variants. Here, we isolated a panel of 23 RBD-specific human monoclonal antibodies from the B cells of convalescent patients. A surprisingly large proportion of such antibodies displayed potent virus-neutralizing activity both in vitro and in vivo. Four of the isolated nAbs can be categorized as ultrapotent with an apparent IC₁₀₀ below 16 ng/mL. We show that individual nAbs as well as dual combinations thereof retain activity against currently circulating SARS-CoV-2 variants of concern (such as B.1.1.7, B.1.351, B.1.617, and C.37), as well as against other viral variants. When used as a prophylactics or therapeutics, these nAbs could potently suppress viral replication and prevent lung pathology in SARS-CoV-2-infected hamsters. Our data contribute to the rational development of oligoclonal therapeutic nAb cocktails mitigating the risk of SARS-CoV-2 escape.

This article evaluates the link between ligands on rhenium clusters and their toxicity.