The first-known aptamer for the stress biomarker cortisol was selected using a tunable stringency magnetic bead selection strategy. The capture DNA probe immobilized on the beads was systematically lengthened to increase the number of bases bound to the complementary pool primer regions following selection enrichment. This resulted in a single sequence (15-1) dominating the final round 15 pool, where the same sequence was the second-highest copy number candidate in the enriched pool with the shorter capture DNA probe (round 13). A thorough analysis of the next-generation sequencing results showed that a high copy number may only correlate with enhanced affinity under certain stringency and enrichment conditions, in contrast with prior published reports. Aptamer 15-1 demonstrated enhanced binding to cortisol (K(d) = 6.9 ± 2.8 μM by equilibrium dialysis; 16.1 ± 0.6 μM by microscale thermophoresis) when compared with the top sequence from round 13 and the negative control progesterone. Whereas most aptamer selections terminate at the selection round demonstrating the highest enrichment, this work shows that extending the selection with higher stringency conditions leads to lower amounts eluted by the target but higher copy numbers of a sequence with enhanced binding. The structure-switching aptamer was applied to a gold nanoparticle assay in buffer and was shown to discriminate between cortisol and two other stress biomarkers, norepinephrine and epinephrine, and a structurally analogous biomarker of liver dysfunction, cholic acid. We believe this approach enhances aptamer selection and serves as proof-of-principle work toward development of point-of-care diagnostics for medical, combat, or bioterrorism targets.

Introduction The coronavirus disease 2019 (COVID-19) pandemic is a global public health emergency causing a disparate burden of death and disability around the world. The molecular characteristics of the virus that predict better or worse outcome are largely still being discovered. Methods We downloaded 155,958 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from GISAID. Of these genomes, 3,637 samples included useable metadata on patient outcomes. Using this subset, we evaluated whether SARS-CoV-2 viral genomic variants improved prediction of reported severity beyond age and region. First, we established whether including genomic variants as model features meaningfully increased predictive power of our model. Next, we evaluated specific variants in order to determine the magnitude of association with severity and the frequency of these variants among SARS-CoV-2 genomes. Results Logistic regression models that included viral genomic variants outperformed other models (AUC = 0.91 as compared with 0.68 for age and gender alone; p < 0.001). Among individual variants, we found 17 single nucleotide variants in SARS-CoV-2 have more than two-fold greater odds of being associated with higher severity and 67 variants associated with ≤0.5 times the odds of severity. The median frequency of associated variants was 0.15% (interquartile range 0.09%-0.45%). Altogether 85% of genomes had at least one variant associated with patient outcome. Conclusion Numerous SARS-CoV-2 variants have two-fold or greater association with odds of mild or severe outcome and collectively, these variants are common. In addition to comprehensive mitigation efforts, public health measures should be prioritized to control the more severe manifestations of COVID-19 and the transmission chains linked to these severe cases. Lay Summary This study explores which, if any, SARS-CoV-2 viral genomic variants are associated with mild or severe COVID-19 patient outcomes. Our results suggest that there are common genomic variants in SARS-CoV-2 that are more often associated with negative patient outcomes, which may impact downstream public health measures.

Background Comparing humoral responses in SARS-CoV-2 vaccinees, those with SARS-CoV-2 infection, or combinations of vaccine/infection (‘hybrid immunity’), may clarify predictors of vaccine immunogenicity. Methods We studied 2660 U.S. Military Health System beneficiaries with a history of SARS-CoV-2 infection-alone (n = 705), vaccination-alone (n = 932), vaccine-after-infection (n = 869), and vaccine-breakthrough-infection (n = 154). Peak anti-spike-IgG responses through 183 days were compared, with adjustment for vaccine product, demography, and comorbidities. We excluded those with evidence of clinical or sub-clinical SARS-CoV-2 reinfection from all groups. Results Multivariable regression results indicated vaccine-after-infection anti-spike-IgG responses were higher than infection-alone (p < 0.01), regardless of prior infection severity. An increased time between infection and vaccination was associated with a greater post-vaccination IgG response (p < 0.01). Vaccination-alone elicited a greater IgG response, but more rapid waning of IgG (p < 0.01), compared to infection-alone (p < 0.01). BNT162b2 and mRNA-1273 vaccine-receipt was associated with greater IgG responses compared to JNJ-78436735 (p < 0.01), regardless of infection history. Those with vaccine-after-infection or vaccine-breakthrough-infection had a more durable anti-spike-IgG response compared to infection-alone (p < 0.01). Conclusions Vaccine-receipt elicited higher anti-spike-IgG responses than infection-alone, although IgG levels waned faster in those vaccinated (compared to infection-alone). Vaccine-after-infection elicits a greater humoral response compared to vaccine or infection alone; and the timing, but not disease severity, of prior infection predicted these post-vaccination IgG responses. While differences between groups were small in magnitude, these results offer insights into vaccine immunogenicity variations that may help inform vaccination timing strategies.

Mercury is a ubiquitous pollutant that when absorbed is extremely toxic to a wide variety of biochemical processes. Mercury (II) is a strong, ''invisible'' poison that is rapidly absorbed by tissues of the intestinal tract, kidneys, and liver upon ingestion. In this study, a novel fluorescence-based biosensor is presented that allows for the direct monitoring of the uptake and distribution of the metal under noninvasive in vivo conditions. With the introduction of a cysteine residue at position 205, located in close proximity to the chromophore, the green fluorescent protein (GFP) from Aequorea victoria was converted into a highly specific biosensor for this metal ion. The mutant protein exhibits a dramatic absorbance and fluorescence change upon mercuration at neutral pH. Absorbance and fluorescence properties with respect to the metal concentration exhibit sigmoidal binding behavior with a detection limit in the low nanomolar range. Time-resolved binding studies indicate rapid subsecond binding of the metal to the protein. The crystal structures obtained of mutant eGFP205C indicate a possible access route of the metal into the core of the protein. To our knowledge, this engineered protein is a first example of a biosensor that allows for noninvasive and real-time imaging of mercury uptake in a living cell. A major advantage is that its expression can be genetically controlled in many organisms to enable unprecedented studies of tissue specific mercury uptake.Keywords: mercury; biosensor; GFP; fluorescence Supplemental material: see www.proteinscience.org Understanding the uptake and distribution of toxic metals is crucial to the diagnosis and identification of heavy metal induced diseases and contaminations. Many of these metals are hazardous when absorbed at even minute concentrations, causing severe neurobehavioral effects and cardiovascular and digestive diseases. Mercury, in particular, is a very potent inhibitor to many protein functions as it can readily be absorbed in the lungs, through the skin, or by ingestion. Many of the diseases induced by the absorption of mercuric compounds are most frequently caused by a chronic low-level exposure to the metal or by temporary high-level exposure due to human negligence and pollution. The uptake of mercury through inhalation predominantly affects bronchial tissues, whereas mercury absorption by ingestion primarily affects stomach, intestine, kidneys, and liver. Hydrophobic organomercurials can also cross the blood-brain barrier, Reprint requests to: Martin Sagermann, University of California, Santa Barbara, 1631 Physical Science North, Santa Barbara, CA 93106-9510, USA; e-mail: sagermann@chem.ucsb.edu; fax: (805) 893-4120.Article published online ahead of print. Article and publication date are at http://www.proteinscience.org/cgi

Background The FLU-PRO Plus is a patient-reported outcome data collection instrument assessing symptoms of viral respiratory tract infections across eight body systems. This study evaluated the measurement properties of FLU-PRO Plus in a study enrolling individuals with COVID-19. Methods Data from a prospective cohort study (EPICC) in US Military Health System (MHS) beneficiaries evaluated for COVID-19 was utilized. Adults with symptomatic SARS-CoV-2 infection with FLU-PRO Plus survey information within one week of symptom onset were included. Reliability of FLU-PRO Plus was estimated using intraclass correlation coefficients (ICC; 2 days reproducibility). Known-groups validity was assessed using patient global assessments (PGA) of disease severity. Patient report of return to usual health was used to assess responsiveness (day 1-6/7). Results 226 SARS-CoV-2 positive participants were included in the analysis. Reliability among those who reported no change in their symptoms from one day to the next was high for most domains (ICC range 0.68-0.94 for day 1 to day 2). Construct validity was demonstrated by moderate to high correlation between the PGA rating of disease severity and domain and total scores (e.g., total scores correlation: 0.69 (influenza-like illness severity), 0.69 (interference in daily activities), and -0.58 (physical health)). In addition, FLU-PRO Plus demonstrated good known-groups validity, with increasing domain and total scores observed with increasing severity ratings. Conclusions FLU-PRO Plus performs well in measuring signs and symptoms in SARS-CoV-2 infection with excellent construct validity, known-groups validity, and responsiveness to change. Standardized data collection instruments facilitate meta-analyses, vaccine effectiveness studies, and other COVID-19 research activities.

Conformational changes play important roles in the regulation of many enzymatic reactions. Specific motions of side chains, secondary structures, or entire protein domains facilitate the precise control of substrate selection, binding, and catalysis. Likewise, the engineering of allostery into proteins is envisioned to enable unprecedented control of chemical reactions and molecular assembly processes. We here study the structural effects of engineered ionizable residues in the core of the glutathione-S-transferase to convert this protein into a pHdependent allosteric protein. The underlying rational of these substitutions is that in the neutral state, an uncharged residue is compatible with the hydrophobic environment. In the charged state, however, the residue will invoke unfavorable interactions, which are likely to induce conformational changes that will affect the function of the enzyme. To test this hypothesis, we have engineered a single aspartate, cysteine, or histidine residue at a distance from the active site into the protein. All of the mutations exhibit a dramatic effect on the protein's affinity to bind glutathione. Whereas the aspartate or histidine mutations result in permanently nonbinding or binding versions of the protein, respectively, mutant GST50C exhibits distinct pH-dependent GSH-binding affinity. The crystal structures of the mutant protein GST50C under ionizing and nonionizing conditions reveal the recruitment of water molecules into the hydrophobic core to produce conformational changes that influence the protein's active site. The methodology described here to create and characterize engineered allosteric proteins through affinity chromatography may lead to a general approach to engineer effector-specific allostery into a protein structure.

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IntroductionThe coronavirus disease 2019 (COVID-19) pandemic is a global public health emergency causing a disparate burden of death and disability around the world. The molecular characteristics of the virus that predict better or worse outcome are largely still being discovered.MethodsWe downloaded 155,958 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from GISAID and evaluated whether variants improved prediction of reported severity beyond age and region. We also evaluated specific variants to determine the magnitude of association with severity and the frequency of these variants among the genomes.ResultsLogistic regression models that included viral genomic variants outperformed other models (AUC=0.91 as compared with 0.68 for age and gender alone; p<0.001). Among individual variants, we found 17 single nucleotide variants in SARS-CoV-2 have more than two-fold greater odds of being associated with higher severity and 67 variants associated with ≤ 0.5 times the odds of severity. The median frequency of associated variants was 0.15% (interquartile range 0.09%-0.45%). Altogether 85% of genomes had at least one variant associated with patient outcome.ConclusionNumerous SARS-CoV-2 variants have two-fold or greater association with odds of mild or severe outcome and collectively, these variants are common. In addition to comprehensive mitigation efforts, public health measures should be prioritized to control the more severe manifestations of COVID-19 and the transmission chains linked to these severe cases.