The Principles of SARS-CoV-2 Intervariant Competition Are Exemplified in the Pre-Omicron Era of the Colombian Epidemic.

The first 18 months of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in Colombia were characterized by three epidemic waves. During the third wave, from March through August 2021, intervariant competition resulted in Mu replacing Alpha and Gamma. We employed Bayesian phylodynamic inference and epidemiological modeling to characterize the variants in the country during this period of competition. Phylogeographic analysis indicated that Mu did not emerge in Colombia but acquired increased fitness there through local transmission and diversification, contributing to its export to North America and Europe. Despite not having the highest transmissibility, Mu's genetic composition and ability to evade preexisting immunity facilitated its domination of the Colombian epidemic landscape. Our results support previous modeling studies demonstrating that both intrinsic factors (transmissibility and genetic diversity) and extrinsic factors (time of introduction and acquired immunity) influence the outcome of intervariant competition. This analysis will help set practical expectations about the inevitable emergences of new variants and their trajectories. IMPORTANCE Before the appearance of the Omicron variant in late 2021, numerous SARS-CoV-2 variants emerged, were established, and declined, often with different outcomes in different geographic areas. In this study, we considered the trajectory of the Mu variant, which only successfully dominated the epidemic landscape of a single country: Colombia. We demonstrate that Mu competed successfully there due to its early and opportune introduction time in late 2020, combined with its ability to evade immunity granted by prior infection or the first generation of vaccines. Mu likely did not effectively spread outside of Colombia because other immune-evading variants, such as Delta, had arrived in those locales and established themselves first. On the other hand, Mu's early spread within Colombia may have prevented the successful establishment of Delta there. Our analysis highlights the geographic heterogeneity of early SARS-CoV-2 variant spread and helps to reframe the expectations for the competition behaviors of future variants.

Transcriptome signatures of wastewater effluent exposure in larval zebrafish vary with seasonal mixture composition in an effluent-dominated stream.

Wastewater treatment plant (WWTP) effluent-dominated streams provide critical habitat for aquatic and terrestrial organisms but also continually expose them to complex mixtures of pharmaceuticals that can potentially impair growth, behavior, and reproduction. Currently, few biomarkers are available that relate to pharmaceutical-specific mechanisms of action. In the experiment reported in this paper, zebrafish (Danio rerio) embryos at two developmental stages were exposed to water samples from three sampling sites (0.1 km upstream of the outfall, at the effluent outfall, and 0.1 km below the outfall) during base-flow conditions from two months (January and May) of a temperate-region effluent-dominated stream containing a complex mixture of pharmaceuticals and other contaminants of emerging concern. RNA-sequencing identified potential biological impacts and biomarkers of WWTP effluent exposure that extend past traditional markers of endocrine disruption. Transcriptomics revealed changes to a wide range of biological functions and pathways including cardiac, neurological, visual, metabolic, and signaling pathways. These transcriptomic changes varied by developmental stage and displayed sensitivity to variable chemical composition and concentration of effluent, thus indicating a need for stage-specific biomarkers. Some transcripts are known to be associated with genes related to pharmaceuticals that were present in the collected samples. Although traditional biomarkers of endocrine disruption were not enriched in either month, a high estrogenicity signal was detected upstream in May and implicates the presence of unidentified chemical inputs not captured by the targeted chemical analysis. This work reveals associations between bioeffects of exposure, stage of development, and the composition of chemical mixtures in effluent-dominated surface water. The work underscores the importance of measuring effects beyond the endocrine system when assessing the impact of bioactive chemicals in WWTP effluent and identifies a need for non-targeted chemical analysis when bioeffects are not explained by the targeted analysis.

Methods to evaluate the impact of SARS-CoV-2 nucleocapsid mutations on antigen detection by rapid diagnostic tests.

Mutations in the nucleocapsid of SARS-CoV-2 may interfere with antigen detection by diagnostic tests. We used several methods to evaluate the effect of various SARS-CoV-2 nucleocapsid mutations on the performance of the Panbio™ and BinaxNOW™ lateral flow rapid antigen tests and a prototype high-throughput immunoassay that utilizes Panbio antibodies. Variant detection was also evaluated by immunoblot and BIAcore™ assay. A panel of 23 recombinant nucleocapsid antigens (rAgs) were produced that included mutations found in circulating SARS-CoV-2 variants, including variants of concern. All mutant rAgs were detected by all assays, at a sensitivity equivalent to wild-type control (Wuhan strain). Thus, using a rAg approach, we found that the SARS-CoV-2 nucleocapsid mutations examined do not directly impact antigen detection or antigen assay performance.

The early SARS-CoV-2 epidemic in Senegal was driven by the local emergence of B.1.416 and the introduction of B.1.1.420 from Europe.

Molecular surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is growing in west Africa, especially in the Republic of Senegal. Here, we present a molecular epidemiology study of the early waves of SARS-CoV-2 infections in this country based on Bayesian phylogeographic approaches. Whereas the first wave in mid-2020 was characterized by a significant diversification of lineages and predominance of B.1.416, the second wave in late 2020 was composed primarily of B.1.1.420. Our results indicate that B.1.416 originated in Senegal and was exported mainly to Europe. In contrast, B.1.1.420 was introduced from Italy, gained fitness in Senegal, and then spread worldwide. Since both B.1.416 and B.1.1.420 lineages carry several positive selected mutations in the spike and nucleocapsid genes, each of which may explain their local dominance, their mutation profiles should be carefully monitored. As the pandemic continues to evolve, molecular surveillance in all regions of Africa will play a key role in stemming its spread.

Cross-species transcriptomic signatures identify mechanisms related to species sensitivity and common responses to nanomaterials.

Physico-chemical characteristics of engineered nanomaterials are known to be important in determining the impact on organisms but effects are equally dependent upon the characteristics of the organism exposed. Species sensitivity may vary by orders of magnitude, which could be due to differences in the type or magnitude of the biochemical response, exposure or uptake of nanomaterials. Synthesizing conclusions across studies and species is difficult as multiple species are not often included in a study, and differences in batches of nanomaterials, the exposure duration and media across experiments confound comparisons. Here three model species, Danio rerio, Daphnia magna and Chironomus riparius, that differ in sensitivity to lithium cobalt oxide nanosheets are found to differ in immune-response, iron-sulfur protein and central nervous system pathways, among others. Nanomaterial uptake and dissolution does not fully explain cross-species differences. This comparison provides insight into how biomolecular responses across species relate to the varying sensitivity to nanomaterials.

Detection of SARS-CoV-2 variants by Abbott molecular, antigen, and serological tests.

BACKGROUND: Viral diversity presents an ongoing challenge for diagnostic tests, which need to accurately detect all circulating variants. The Abbott Global Surveillance program monitors severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) variants and their impact on diagnostic test performance. OBJECTIVES: To evaluate the capacity of Abbott molecular, antigen, and serologic assays to detect circulating SARS-CoV-2 variants, including all current variants of concern (VOC): B.1.1.7 (alpha), B.1.351 (beta), P.1 (gamma) and B.1.617.2 (delta). STUDY DESIGN: Dilutions of variant virus cultures (B.1.1.7, B.1.351, B.1.429, B.1.526.1, B.1.526.2, B.1.617.1, B.1.617.2, P.1, R.1 and control isolate WA1) and a panel of N = 248 clinical samples from patients with sequence confirmed variant infections (B.1.1.7, B.1.351, B.1.427, B.1.429, B.1.526, B.1.526.1, B.1.526.2, P.1, P.2, R.1) were evaluated on at least one assay: Abbott ID NOW COVID-19, m2000 RealTime SARS-CoV-2, Alinity m SARS-CoV-2, and Alinity m Resp-4-Plex molecular assays; the BinaxNOW COVID-19 Ag Card and Panbio COVID-19 Ag Rapid Test Device; and the ARCHITECT/Alinity i SARS-CoV-2 IgG and AdviseDx IgM assays, Panbio COVID-19 IgG assay, and ARCHITECT/Alinity i AdviseDx SARS-CoV-2 IgG II assay. RESULTS: Consistent with in silico predictions, each molecular and antigen assay detected VOC virus cultures with equivalent sensitivity to the WA1 control strain. Notably, 100% of all tested variant patient specimens were detected by molecular assays (N = 197 m2000, N = 88 Alinity m, N = 99 ID NOW), and lateral flow assays had a sensitivity of >94% for specimens with genome equivalents (GE) per device above 4 log (85/88, Panbio; 54/57 Binax). Furthermore, Abbott antibody assays detected IgG and IgM in 94-100% of sera from immune competent B.1.1.7 patients 15-26 days after symptom onset. CONCLUSIONS: These data confirm variant detection for 11 SARS-CoV-2 assays, which is consistent with each assay target region being highly conserved. Importantly, alpha, beta, gamma, and delta VOCs were detected by molecular and antigen assays, indicating that these tests may be suitable for widescale use where VOCs predominate.

Energy Starvation in Daphnia magna from Exposure to a Lithium Cobalt Oxide Nanomaterial.

Growing evidence across organisms points to altered energy metabolism as an adverse outcome of metal oxide nanomaterial toxicity, with a mechanism of toxicity potentially related to the redox chemistry of processes involved in energy production. Despite this evidence, the significance of this mechanism has gone unrecognized in nanotoxicology due to the field's focus on oxidative stress as a universal─but nonspecific─nanotoxicity mechanism. To further explore metabolic impacts, we determined lithium cobalt oxide's (LCO's) effects on these pathways in the model organism Daphnia magna through global gene-expression analysis using RNA-Seq and untargeted metabolomics by direct-injection mass spectrometry. Our results show that a sublethal 1 mg/L 48 h exposure of D. magna to LCO nanosheets causes significant impacts on metabolic pathways versus untreated controls, while exposure to ions released over 48 h does not. Specifically, transcriptomic analysis using DAVID indicated significant enrichment (Benjamini-adjusted p ≤0.0.5) in LCO-exposed animals for changes in pathways involved in the cellular response to starvation (25 genes), mitochondrial function (70 genes), ATP-binding (70 genes), oxidative phosphorylation (53 genes), NADH dehydrogenase activity (12 genes), and protein biosynthesis (40 genes). Metabolomic analysis using MetaboAnalyst indicated significant enrichment (γ-adjusted p <0.1) for changes in amino acid metabolism (19 metabolites) and starch, sucrose, and galactose metabolism (7 metabolites). Overlap of significantly impacted pathways by RNA-Seq and metabolomics suggests amino acid breakdown and increased sugar import for energy production. Results indicate that LCO-exposed Daphnia respond to energy starvation by altering metabolic pathways, both at the gene expression and metabolite levels. These results support altered energy production as a sensitive nanotoxicity adverse outcome for LCO exposure and suggest negative impacts on energy metabolism as an important avenue for future studies of nanotoxicity, including for other biological systems and for metal oxide nanomaterials more broadly.

Urban wastewater bacterial communities assemble into seasonal steady states.

BACKGROUND: Microorganisms in urban sanitary sewers exhibit community properties that suggest sewers are a novel ecosystem. Sewer microorganisms present both an opportunity as a control point for wastewater treatment and a risk to human health. If treatment processes are to be improved and health risks quantified, then it is necessary to understand microbial distributions and dynamics within this community. Here, we use 16S rRNA gene sequencing to characterize raw influent wastewater bacterial communities in a 5-year time series from two wastewater treatment plants in Milwaukee, WI; influent wastewater from 77 treatment plants across the USA; and wastewater in 12 Milwaukee residential sewers. RESULTS: In Milwaukee, we find that in transit from residences to treatment plants, the human bacterial component of wastewater decreases in proportion and exhibits stochastic temporal variation. In contrast, the resident sewer community increases in abundance during transit and cycles seasonally according to changes in wastewater temperature. The result is a bacterial community that assembles into two distinct community states each year according to the extremes in wastewater temperature. Wastewater bacterial communities from other northern US cities follow temporal trends that mirror those in Milwaukee, but southern US cities have distinct community compositions and differ in their seasonal patterns. CONCLUSIONS: Our findings provide evidence that environmental conditions associated with seasonal change and climatic differences related to geography predictably structure the bacterial communities residing in below-ground sewer pipes. Video abstract.

Protein Fe-S Centers as a Molecular Target of Toxicity of a Complex Transition Metal Oxide Nanomaterial with Downstream Impacts on Metabolism and Growth.

Oxidative stress is frequently identified as a mechanism of toxicity of nanomaterials. However, rarely have the specific underlying molecular targets responsible for these impacts been identified. We previously demonstrated significant negative impacts of transition metal oxide (TMO) lithium-ion battery cathode nanomaterial, lithium cobalt oxide (LCO), on the growth, development, hemoglobin, and heme synthesis gene expression in the larvae of a model sediment invertebrate Chironomus riparius. Here, we propose that alteration of the Fe-S protein function by LCO is a molecular initiating event leading to these changes. A 10 mg/L LCO exposure causes significant oxidation of the aconitase 4Fe-4S center after 7 d as determined from the electron paramagnetic resonance spectroscopy measurements of intact larvae and a significant reduction in the aconitase activity of larval protein after 48 h (p < 0.05). Next-generation RNA sequencing identified significant changes in the expression of genes involved in 4Fe-4S center binding, Fe-S center synthesis, iron ion binding, and metabolism for 10 mg/L LCO at 48 h (FDR-adjusted, p < 0.1). We propose an adverse outcome pathway, where the oxidation of metabolic and regulatory Fe-S centers of proteins by LCO disrupts metabolic homeostasis, which negatively impacts the growth and development, a mechanism that may apply for these conserved proteins across species and for other TMO nanomaterials.