A recent study published in Nature sheds light on the complex dynamics of highly pathogenic avian influenza (HPAI) H5N1 since 2021, uncovering critical shifts in the virus's behavior and providing insights for more effective mitigation strategies. The research emphasizes the importance of understanding the ecological and virological factors driving the intensified global activity of HPAI H5N1 to better prepare for and manage future outbreaks.
Researchers explored the genetic variability among the monkeypox virus genomes of Clade IIb lineage B.1 using a phylodynamic and genetic survey to confirm the epidemic cluster in the clade and understand the evolution of the virus.
The space-for-time substitution approach provides a valuable empirical assessment to infer temporal effects of disturbance from spatial gradients. Applied to predict the response of different ecosystems under current climate change scenarios, it remains poorly tested in microbial ecology studies, partly due to the trophic complexity of the ecosystems studied. The McMurdo Dry Valleys of Antarctica represent a trophically simple polar desert projected to experience drastic changes in water availability under current climate change predictions. We used this ideal model system to develop and validate a microbial space-for-time sampling approach, using the variation of geochemical profiles that follow alterations in water availability and reflect past and future changes in the system. Our framework measured soil electrical conductivity, pH, and water activity in situ to geochemically define 17 space-for-time transects from the shores of four dynamic and two static Dry Valley lakes. We ident
What tells us that this new form of H1N1 is swine flu and not regular old human flu or avian flu?
If we had a lab, we might use antibodies, but when you're a digital biologist, you use a computer.
Activity 4. Picking influenza sequences and comparing them with phylogenetic trees
We can get the genome sequences, piece by piece, as I described in earlier, but the NCBI has other tools that are useful, too.
The novel coronavirus (SARS-CoV-2) pandemic resulted in the largest public health crisis in recent times. Significant drug design effort against SARS-CoV-2 is focused on the receptor-binding domain (RBD) of the spike protein, although this region is highly prone to mutations causing therapeutic resistance. We applied deep data analysis methods on all-atom molecular dynamics simulations to identify key non-RBD residues that play a crucial role in spike−receptor binding and infection. Because the non-RBD residues are typically conserved across multiple coronaviruses, they can be targeted by broad-spectrum antibodies and drugs to treat infections from new strains that might appear during future epidemics.
The MD trajectories are available from Zenodo at [doi.org/10.528c1/zenodo.5052691][1]. The codes and the residue correlation data used in this study are available from GitHub at <https://github.com/dhimanray/COVID-19-correlation-work>. All further details about the methods and t