Resolving distinct molecular origins for copper effects on PAI-1.

Components of the fibrinolytic system are subjected to stringent control to maintain proper hemostasis. Central to this regulation is the serpin plasminogen activator inhibitor-1 (PAI-1), which is responsible for specific and rapid inhibition of fibrinolytic proteases. Active PAI-1 is inherently unstable and readily converts to a latent, inactive form. The binding of vitronectin and other ligands influences stability of active PAI-1. Our laboratory recently observed reciprocal effects on the stability of active PAI-1 in the presence of transition metals, such as copper, depending on the whether vitronectin was also present (Thompson et al. Protein Sci 20:353-365, 2011). To better understand the molecular basis for these copper effects on PAI-1, we have developed a gel-based copper sensitivity assay that can be used to assess the copper concentrations that accelerate the conversion of active PAI-1 to a latent form. The copper sensitivity of wild-type PAI-1 was compared with variants lacking N-terminal histidine residues hypothesized to be involved in copper binding. In these PAI-1 variants, we observed significant differences in copper sensitivity, and these data were corroborated by latency conversion kinetics and thermodynamics of copper binding by isothermal titration calorimetry. These studies identified a copper-binding site involving histidines at positions 2 and 3 that confers a remarkable stabilization of PAI-1 beyond what is observed with vitronectin alone. A second site, independent from the two histidines, binds metal and increases the rate of the latency conversion.

A collaborative approach to improving representation in viral genomic surveillance.

The lack of routine viral genomic surveillance delayed the initial detection of SARS-CoV-2, allowing the virus to spread unfettered at the outset of the U.S. epidemic. Over subsequent months, poor surveillance enabled variants to emerge unnoticed. Against this backdrop, long-standing social and racial inequities have contributed to a greater burden of cases and deaths among minority groups. To begin to address these problems, we developed a new variant surveillance model geared toward building 'next generation' genome sequencing capacity at universities in or near rural areas and engaging the participation of their local communities. The resulting genomic surveillance network has generated more than 1,000 SARS-CoV-2 genomes to date, including the first confirmed case in northeast Louisiana of Omicron, and the first and sixth confirmed cases in Georgia of the emergent BA.2.75 and BQ.1.1 variants, respectively. In agreement with other studies, significantly higher viral gene copy numbers were observed in Delta variant samples compared to those from Omicron BA.1 variant infections, and lower copy numbers were seen in asymptomatic infections relative to symptomatic ones. Collectively, the results and outcomes from our collaborative work demonstrate that establishing genomic surveillance capacity at smaller academic institutions in rural areas and fostering relationships between academic teams and local health clinics represent a robust pathway to improve pandemic readiness.

A collaborative approach to improve representation in viral genomic surveillance.

The lack of routine viral genomic surveillance delayed the initial detection of SARS-CoV-2, allowing the virus to spread unfettered at the outset of the U.S. epidemic. Over subsequent months, poor surveillance enabled variants to emerge unnoticed. Against this backdrop, long-standing social and racial inequities have contributed to a greater burden of cases and deaths among minority groups. To begin to address these problems, we developed a new variant surveillance model geared toward building microbial genome sequencing capacity at universities in or near rural areas and engaging the participation of their local communities. The resulting genomic surveillance network has generated more than 1,000 SARS-CoV-2 genomes to date, including the first confirmed case in northeast Louisiana of Omicron, and the first and sixth confirmed cases in Georgia of the emergent BA.2.75 and BQ.1.1 variants, respectively. In agreement with other studies, significantly higher viral gene copy numbers were observed in Delta variant samples compared to those from Omicron BA.1 variant infections, and lower copy numbers were seen in asymptomatic infections relative to symptomatic ones. Collectively, the results and outcomes from our collaborative work demonstrate that establishing genomic surveillance capacity at smaller academic institutions in rural areas and fostering relationships between academic teams and local health clinics represent a robust pathway to improve pandemic readiness. Author summary: Genomic surveillance involves decoding a pathogen’s genetic code to track its spread and evolution. During the pandemic, genomic surveillance programs around the world provided valuable data to scientists, doctors, and public health officials. Knowing the complete SARS-CoV-2 genome has helped detect the emergence of new variants, including ones that are more transmissible or cause more severe disease, and has supported the development of diagnostics, vaccines, and therapeutics. The impact of genomic surveillance on public health depends on representative sampling that accurately reflects the diversity and distribution of populations, as well as rapid turnaround time from sampling to data sharing. After a slow start, SARS-CoV-2 genomic surveillance in the United States grew exponentially. Despite this, many rural regions and ethnic minorities remain poorly represented, leaving significant gaps in the data that informs public health responses. To address this problem, we formed a network of universities and clinics in Louisiana, Georgia, and Mississippi with the goal of increasing SARS-CoV-2 sequencing volume, representation, and equity. Our results demonstrate the advantages of rapidly sequencing pathogens in the same communities where the cases occur and present a model that leverages existing academic and clinical infrastructure for a powerful decentralized genomic surveillance system.