Identification of SARS-CoV-2 variants in indoor dust.

Environmental surveillance of pathogens underlying infectious disease is critical to ensure public health. Recent efforts to track SARS-CoV-2 have utilized wastewater sampling to infer community trends in viral abundance and variant composition. Indoor dust has also been used for building-level inferences, though to date no sequencing data providing variant-scale resolution have been reported from dust samples, and strategies to monitor circulating variants in dust are needed to help inform public health decisions. In this study, we demonstrate that SARS-CoV-2 lineages can be detected and sequenced from indoor bulk dust samples. We collected 93 vacuum bags from April 2021 to March 2022 from buildings on The Ohio State University's (OSU) Columbus campus, and the dust was used to develop and apply an amplicon-based whole-genome sequencing protocol to identify the variants present and estimate their relative abundances. Three variants of concern were detected in the dust: Alpha, Delta, and Omicron. Alpha was found in our earliest sample in April 2021 with an estimated frequency of 100%. Delta was the primary variant present from October of 2021 to January 2022, with an average estimated frequency of 91% (±1.3%). Omicron became the primary variant in January 2022 and was the dominant strain in circulation through March with an estimated frequency of 87% (±3.2%). The detection of these variants on OSU's campus correlates with the circulation of these variants in the surrounding population (Delta p<0.0001 and Omicron p = 0.02). Overall, these results support the hypothesis that dust can be used to track COVID-19 variants in buildings.

Hypermethylation and small RNA expression are associated with increased age in almond (Prunus dulcis [Mill.] D.A. Webb) accessions.

The focus of this study is to profile changes in DNA methylation and small RNA expression occurring with increased age in almond breeding germplasm to identify possible biomarkers of age that can be used to assess the potential of individuals to develop aging-related disorders. To profile DNA methylation in almond germplasm, 70 methylomes were generated from almond individuals representing three age cohorts (11, 7, and 2 years old) using an enzymatic methyl-seq approach followed by analysis to call differentially methylated regions (DMRs) within these cohorts. Small RNA (sRNA) expression was profiled in three breeding selections, each from two age cohorts (1 and 6 years old), using sRNA-Seq followed by differential expression analysis. Weighted chromosome-level methylation analysis reveals hypermethylation in 11-year-old almond breeding selections when compared to 2-year-old selections in the CG and CHH contexts. Seventeen consensus DMRs were identified in all age contrasts. sRNA expression differed significantly between the two age cohorts tested, with significantly decreased expression in sRNAs in the 6-year-old selections compared to the 1-year-old. Almond shows a pattern of hypermethylation and decreased sRNA expression with increased age. Identified DMRs and differentially expressed sRNAs could function as putative biomarkers of age following validation in additional age groups.

Ohio Coronavirus Wastewater Monitoring Network: Implementation of Statewide Monitoring for Protecting Public Health.

CONTEXT: Prior to the COVID-19 pandemic, wastewater influent monitoring for tracking disease burden in sewered communities was not performed in Ohio, and this field was only on the periphery of the state academic research community. PROGRAM: Because of the urgency of the pandemic and extensive state-level support for this new technology to detect levels of community infection to aid in public health response, the Ohio Water Resources Center established relationships and support of various stakeholders. This enabled Ohio to develop a statewide wastewater SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) monitoring network in 2 months starting in July 2020. IMPLEMENTATION: The current Ohio Coronavirus Wastewater Monitoring Network (OCWMN) monitors more than 70 unique locations twice per week, and publicly available data are updated weekly on the public dashboard. EVALUATION: This article describes the process and decisions that were made during network initiation, the network progression, and data applications, which can inform ongoing and future pandemic response and wastewater monitoring. DISCUSSION: Overall, the OCWMN established wastewater monitoring infrastructure and provided a useful tool for public health professionals responding to the pandemic.

Genetic mutations linked to field-evolved Cry1Fa-resistance in the European corn borer, Ostrinia nubilalis.

Transgenic corn, Zea mays (L.), expressing insecticidal toxins such as Cry1Fa, from Bacillus thuringiensis (Bt corn) targeting Ostrinia nubilalis (Hübner) (Lepidoptera: Crambidae) resulted in over 20 years of management success. The first case of practical field-evolved resistance by O. nubilalis to a Bt corn toxin, Cry1Fa, was discovered in Nova Scotia, Canada, in 2018. Laboratory-derived Cry1Fa-resistance by O. nubilalis was linked to a genome region encoding the ATP Binding Cassette subfamily C2 (ABCC2) gene; however, the involvement of ABCC2 and specific mutations in the gene leading to resistance remain unknown. Using a classical candidate gene approach, we report on O. nubilalis ABCC2 gene mutations linked to laboratory-derived and field-evolved Cry1Fa-resistance. Using these mutations, a DNA-based genotyping assay was developed to test for the presence of the Cry1Fa-resistance alleles in O. nubilalis strains collected in Canada. Screening data provide strong evidence that field-evolved Cry1Fa-resistance in O. nubilalis maps to the ABCC2 gene and demonstrates the utility of this assay for detecting the Cry1Fa resistance allele in O. nubilalis. This study is the first to describe mutations linked to Bt resistance in O. nubilalis and provides a DNA-based detection method that can be used for monitoring.

MixviR: an R Package for Exploring Variation Associated with Genomic Sequence Data from Environmental SARS-CoV-2 and Other Mixed Microbial Samples.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)/coronavirus disease 2019 (COVID-19) pandemic has highlighted an important role for efficient surveillance of microbial pathogens. High-throughput sequencing technologies provide valuable surveillance tools, offering opportunities to conduct high-resolution monitoring from diverse sample types, including from environmental sources. However, given their large size and potential to contain mixtures of lineages within samples, such genomic data sets can present challenges for analyzing the data and communicating results with diverse stakeholders. Here, we report MixviR, an R package for exploring, analyzing, and visualizing genomic data from potentially mixed samples of a target microbial group. MixviR characterizes variation at both the nucleotide and amino acid levels and offers the RShiny interactive dashboard for exploring data. We demonstrate MixviR's utility with validation studies using mixtures of known lineages from both SARS-CoV-2 and Mycobacterium tuberculosis and with a case study analyzing lineages of SARS-CoV-2 in wastewater samples over time at a sampling location in Ohio, USA. IMPORTANCE High-throughput sequencing technologies hold great potential for contributing to genomic-based surveillance of microbial diversity from environmental samples. However, the size of the data sets, along with the potential for environmental samples to contain multiple evolutionary lineages of interest, present challenges around analyzing and effectively communicating inferences from these data sets. The software described here provides a novel and valuable tool for exploring such data. Though originally designed and used for monitoring SARS-CoV-2 lineages in wastewater, it can also be applied to analyses of genomic diversity in other microbial groups.

The Role of Egg Yolk in Modulating the Virulence of Salmonella Enterica Serovar Enteritidis.

Contribution of food vehicles to pathogenicity of disease-causing microorganisms is an important but overlooked research field. The current study was initiated to reveal the relationship between virulence of Salmonella enterica serovar Enteritidis and egg yolk as a hosting medium. Mice were orally challenged with Salmonella Enteritidis cultured in egg yolk or tryptic soy broth (TSB). Additionally, mice were challenged with Salmonella Enteritidis cultured in TSB, followed by administration of sterile egg yolk, to discern the difference between pre-growth of the pathogen and its mere presence in egg yolk during infection. The pathogen's Lethal dose 50 (LD50) was the lowest when grown in yolk (2.8×102 CFU), compared to 1.1×103 CFU in TSB, and 4.6×103 CFU in TSB followed by administration of sterile yolk. Additionally, mice that orally received Salmonella Enteritidis grown in egg yolk expressed a high death rate. These findings were supported by transcriptional analysis results. Expression of promoters of virulence-related genes (sopB and sseA) in genetically modified Salmonella Enteritidis reporter strains was significantly higher (p < 0.05) when the bacterium was grown in the yolk, compared to that grown in TSB. Sequencing of RNA (RNA-seq) revealed 204 differentially transcribed genes in Salmonella Enteritidis grown in yolk vs. TSB. Yolk-grown Salmonella Enteritidis exhibited upregulated virulence pathways, including type III secretion systems, epithelial cell invasion, and infection processes; these observations were confirmed by RT-qPCR results. The transcriptomic analysis suggested that upregulation of virulence machinery of Salmonella Enteritidis grown in egg yolk was related to increased iron uptake, biotin utilization, flagellar biosynthesis, and export of virulence proteins encoded on Salmonella pathogenicity island 1, 2, 4, and 5. These biological responses may have acted in concert to increase the virulence of Salmonella infection in mice. In conclusion, growth in egg yolk enhanced Salmonella Enteritidis virulence, indicating the significance of this food vehicle to the risk assessment of salmonellosis.

Dietary omega-3 fatty acid intake impacts peripheral blood DNA methylation -anti-inflammatory effects and individual variability in a pilot study.

Omega-3 or n-3 polyunsaturated fatty acids (PUFAs) are widely studied for health benefits that may relate to anti-inflammatory activity. However, mechanisms mediating an anti-inflammatory response to n-3 PUFA intake are not fully understood. Of interest is the emerging role of fatty acids to impact DNA methylation (DNAm) and thereby modulate mediating inflammatory processes. In this pilot study, we investigated the impact of n-3 PUFA intake on DNAm in inflammation-related signaling pathways in peripheral blood mononuclear cells (PBMCs) of women at high risk of breast cancer. PBMCs of women at high risk of breast cancer (n=10) were obtained at baseline and after 6 months of n-3 PUFA (5 g/d EPA+DHA dose arm) intake in a previously reported dose finding trial. DNA methylation of PBMCs was assayed by reduced representation bisulfite sequencing (RRBS) to obtain genome-wide methylation profiles at the single nucleotide level. We examined the impact of n-3 PUFA on genome-wide DNAm and focused upon a set of candidate genes associated with inflammation signaling pathways and breast cancer. We identified 24,842 differentially methylated CpGs (DMCs) in gene promoters of 5507 genes showing significant enrichment for hypermethylation in both the candidate gene and genome-wide analyses. Pathway analysis identified significantly hypermethylated signaling networks after n-3 PUFA treatment, such as the Toll-like Receptor inflammatory pathway. The DNAm pattern in individuals and the response to n-3 PUFA intake are heterogeneous. PBMC DNAm profiling suggests a mechanism whereby n-3 PUFAs may impact inflammatory cascades associated with disease processes including carcinogenesis.

Frequency, composition and mobility of Escherichia coli-derived transposable elements in holdings of plasmid repositories.

By providing the scientific community with uniform and standardized resources of consistent quality, plasmid repositories play an important role in enabling scientific reproducibility. Plasmids containing insertion sequence elements (IS elements) represent a challenge from this perspective, as they can change the plasmid structure and function. In this study, we conducted a systematic analysis of a subset of plasmid stocks distributed by plasmid repositories (The Arabidopsis Biological Resource Center and Addgene) which carry unintended integrations of bacterial mobile genetic elements. The integration of insertion sequences was most often found in, but not limited to, pBR322-derived vectors, and did not affect the function of the specific plasmids. In certain cases, the entire stock was affected, but the majority of the stocks tested contained a mixture of the wild-type and the mutated plasmids, suggesting that the acquisition of IS elements likely occurred after the plasmids were acquired by the repositories. However, comparison of the sequencing results of the original samples revealed that some plasmids already carried insertion mutations at the time of donation. While an extensive BLAST analysis of 47 877 plasmids sequenced from the Addgene repository uncovered IS elements in only 1.12%, suggesting that IS contamination is not widespread, further tests showed that plasmid integration of IS elements can propagate in conventional Escherichia coli hosts over a few tens of generations. Use of IS-free E. coli hosts prevented the emergence of IS insertions as well as that of small indels, suggesting that the use of IS-free hosts by donors and repositories could help limit unexpected and unwanted IS integrations into plasmids.

CLEAR: coverage-based limiting-cell experiment analysis for RNA-seq.

BACKGROUND: Direct cDNA preamplification protocols developed for single-cell RNA-seq have enabled transcriptome profiling of precious clinical samples and rare cell populations without the need for sample pooling or RNA extraction. We term the use of single-cell chemistries for sequencing low numbers of cells limiting-cell RNA-seq (lcRNA-seq). Currently, there is no customized algorithm to select robust/low-noise transcripts from lcRNA-seq data for between-group comparisons. METHODS: Herein, we present CLEAR, a workflow that identifies reliably quantifiable transcripts in lcRNA-seq data for differentially expressed genes (DEG) analysis. Total RNA obtained from primary chronic lymphocytic leukemia (CLL) CD5+ and CD5- cells were used to develop the CLEAR algorithm. Once established, the performance of CLEAR was evaluated with FACS-sorted cells enriched from mouse Dentate Gyrus (DG). RESULTS: When using CLEAR transcripts vs. using all transcripts in CLL samples, downstream analyses revealed a higher proportion of shared transcripts across three input amounts and improved principal component analysis (PCA) separation of the two cell types. In mouse DG samples, CLEAR identifies noisy transcripts and their removal improves PCA separation of the anticipated cell populations. In addition, CLEAR was applied to two publicly-available datasets to demonstrate its utility in lcRNA-seq data from other institutions. If imputation is applied to limit the effect of missing data points, CLEAR can also be used in large clinical trials and in single cell studies. CONCLUSIONS: lcRNA-seq coupled with CLEAR is widely used in our institution for profiling immune cells (circulating or tissue-infiltrating) for its transcript preservation characteristics. CLEAR fills an important niche in pre-processing lcRNA-seq data to facilitate transcriptome profiling and DEG analysis. We demonstrate the utility of CLEAR in analyzing rare cell populations in clinical samples and in murine neural DG region without sample pooling.

Overcoming resistance to anabolic SARM therapy in experimental cancer cachexia with an HDAC inhibitor.

No approved therapy exists for cancer-associated cachexia. The colon-26 mouse model of cancer cachexia mimics recent late-stage clinical failures of anabolic anti-cachexia therapy and was unresponsive to anabolic doses of diverse androgens, including the selective androgen receptor modulator (SARM) GTx-024. The histone deacetylase inhibitor (HDACi) AR-42 exhibited anti-cachectic activity in this model. We explored combined SARM/AR-42 therapy as an improved anti-cachectic treatment paradigm. A reduced dose of AR-42 provided limited anti-cachectic benefits, but, in combination with GTx-024, significantly improved body weight, hindlimb muscle mass, and grip strength versus controls. AR-42 suppressed the IL-6/GP130/STAT3 signaling axis in muscle without impacting circulating cytokines. GTx-024-mediated ß-catenin target gene regulation was apparent in cachectic mice only when combined with AR-42. Our data suggest cachectic signaling in this model involves catabolic signaling insensitive to anabolic GTx-024 therapy and a blockade of GTx-024-mediated anabolic signaling. AR-42 mitigates catabolic gene activation and restores anabolic responsiveness to GTx-024. Combining GTx-024, a clinically established anabolic therapy, with AR-42, a clinically evaluated HDACi, represents a promising approach to improve anabolic response in cachectic patients.

Within-group relatedness is correlated with colony-level social structure and reproductive sharing in a social fish.

In group-living species, the degree of relatedness among group members often governs the extent of reproductive sharing, cooperation and conflict within a group. Kinship among group members can be shaped by the presence and location of neighbouring groups, as these provide dispersal or mating opportunities that can dilute kinship among current group members. Here, we assessed how within-group relatedness varies with the density and position of neighbouring social groups in Neolamprologus pulcher, a colonial and group-living cichlid fish. We used restriction site-associated DNA sequencing (RADseq) methods to generate thousands of polymorphic SNPs. Relative to microsatellite data, RADseq data provided much tighter confidence intervals around our relatedness estimates. These data allowed us to document novel patterns of relatedness in relation to colony-level social structure. First, the density of neighbouring groups was negatively correlated with relatedness between subordinates and dominant females within a group, but no such patterns were observed between subordinates and dominant males. Second, subordinates at the colony edge were less related to dominant males in their group than subordinates in the colony centre, suggesting a shorter breeding tenure for dominant males at the colony edge. Finally, subordinates who were closely related to their same-sex dominant were more likely to reproduce, supporting some restraint models of reproductive skew. Collectively, these results demonstrate that within-group relatedness is influenced by the broader social context, and variation between groups in the degree of relatedness between dominants and subordinates can be explained by both patterns of reproductive sharing and the nature of the social landscape.

Genetic diversity in migratory bats: Results from RADseq data for three tree bat species at an Ohio windfarm.

Genetic analyses can identify the scale at which wildlife species are impacted by human activities, and provide demographic information useful for management. Here, we use thousands of nuclear DNA genetic loci to assess whether genetic structure occurs within Lasiurus cinereus (Hoary Bat), L. borealis (Red Bat), and Lasionycteris noctivagans (Silver-Haired Bat) bats found at a wind turbine site in Ohio, and to also estimate demographic parameters in each of these three groups. Our specific goals are to: 1) demonstrate the feasibility of isolating RADseq loci from these tree bat species, 2) test for genetic structure within each species, including any structure that may be associated with time (migration period), and 3) use coalescent-based modeling approaches to estimate genetically-effective population sizes and patterns of population size changes over evolutionary timescales. Thousands of loci were successfully genotyped for each species, demonstrating the value of RADseq for generating polymorphic loci for population genetic analyses in these bats. There was no evidence for genetic differentiation between groups of samples collected at different times throughout spring and fall migration, suggesting that individuals from each species found at the wind facility are from single panmictic populations. Estimates of present-day effective population sizes varied across species, but were consistently large, on the order of 10(5)-10(6). All populations show evidence of expansions that date to the Pleistocene. These results, along with recent work also suggesting limited genetic structure in bats across North America, argue that additional biomarker systems such as stable-isotopes or trace elements should be investigated as alternative and/or complementary approaches to genetics for sourcing individuals collected at single wind farm sites.

AftrRAD: a pipeline for accurate and efficient de novo assembly of RADseq data.

An increase in studies using restriction site-associated DNA sequencing (RADseq) methods has led to a need for both the development and assessment of novel bioinformatic tools that aid in the generation and analysis of these data. Here, we report the availability of AftrRAD, a bioinformatic pipeline that efficiently assembles and genotypes RADseq data, and outputs these data in various formats for downstream analyses. We use simulated and experimental data sets to evaluate AftrRAD's ability to perform accurate de novo assembly of loci, and we compare its performance with two other commonly used programs, stacks and pyrad. We demonstrate that AftrRAD is able to accurately assemble loci, while accounting for indel variation among alleles, in a more computationally efficient manner than currently available programs. AftrRAD run times are not strongly affected by the number of samples in the data set, making this program a useful tool when multicore systems are not available for parallel processing, or when data sets include large numbers of samples.

The effects of locus number, genetic divergence, and genotyping error on the utility of dominant markers for hybrid identification.

In surveys of hybrid zones, dominant genetic markers are often used to identify individuals of hybrid origin and assign these individuals to one of several potential hybrid classes. Quantitative analyses that address the statistical power of dominant markers in such inference are scarce. In this study, dominant genotype data were simulated to evaluate the effects of, first, the number of loci analyzed, second, the magnitude of differentiation between the markers scored in the groups that are hybridizing, and third, the level of genotyping error associated with the data when assigning individuals to various parental and hybrid categories. The overall performance of the assignment methods was relatively modest at the lowest level of divergence examined (F st ˜ 0.4), but improved substantially at higher levels of differentiation (F st ˜ 0.67 or 0.8). The effect of genotyping error was dependent on the level of divergence between parental taxa, with larger divergences tempering the effects of genotyping error. These results highlight the importance of considering the effects of each of the variables when assigning individuals to various parental and hybrid categories, and can help guide decisions regarding the number of loci employed in future hybridization studies to achieve the power and level of resolution desired.

Venomics of New World pit vipers: genus-wide comparisons of venom proteomes across Agkistrodon.

We report a genus-wide comparison of venom proteome variation across New World pit vipers in the genus Agkistrodon. Despite the wide variety of habitats occupied by this genus and that all its taxa feed on diverse species of vertebrates and invertebrate prey, the venom proteomes of copperheads, cottonmouths, and cantils are remarkably similar, both in the type and relative abundance of their different toxin families. The venoms from all the eleven species and subspecies sampled showed relatively similar proteolytic and PLA2 activities. In contrast, quantitative differences were observed in hemorrhagic and myotoxic activities in mice. The highest myotoxic activity was observed with the venoms of A. b. bilineatus, followed by A. p. piscivorus, whereas the venoms of A. c. contortrix and A. p. leucostoma induced the lowest myotoxic activity. The venoms of Agkistrodon bilineatus subspecies showed the highest hemorrhagic activity and A. c. contortrix the lowest. Compositional and toxicological analyses agree with clinical observations of envenomations by Agkistrodon in the USA and Central America. A comparative analysis of Agkistrodon shows that venom divergence tracks phylogeny of this genus to a greater extent than in Sistrurus rattlesnakes, suggesting that the distinct natural histories of Agkistrodon and Sistrurus clades may have played a key role in molding the patterns of evolution of their venom protein genes. BIOLOGICAL SIGNIFICANCE: A deep understanding of the structural and functional profiles of venoms and of the principles governing the evolution of venomous systems is a goal of venomics. Isolated proteomics analyses have been conducted on venoms from many species of vipers and pit vipers. However, making sense of these large inventories of data requires the integration of this information across multiple species to identify evolutionary and ecological trends. Our genus-wide venomics study provides a comprehensive overview of the toxic arsenal across Agkistrodon and a ground for understanding the natural histories of, and clinical observations of envenomations by, species of this genus.

Phylogeny-based comparative analysis of venom proteome variation in a clade of rattlesnakes (Sistrurus sp.).

A long-standing question in evolutionary studies of snake venoms is the extent to which phylogenetic divergence and diet can account for between-species differences in venom composition. Here we apply phylogeny-based comparative methods to address this question. We use data on venom variation generated using proteomic techniques for all members of a small clade of rattlesnakes (Sistrurus sp.) and two outgroups for which phylogenetic and diet information is available. We first complete the characterization of venom variation for all members of this clade with a "venomic" analysis of pooled venoms from two members of this genus, S. milarius streckeri and S. m. milarius. These venoms exhibit the same general classes of proteins as those found in other Sistrurus species but differ in their relative abundances of specific protein families. We then test whether there is significant phylogenetic signal in the relative abundances of major venom proteins across species and if diet (measured as percent mammals and lizards among all prey consumed) covaries with venom composition after phylogenetic divergence is accounted for. We found no evidence for significant phylogenetic signal in venom variation: K values for seven snake venom proteins and two composite venom variables [PC 1 and 2]) were all nonsignificant and lower (mean = 0.11+0.06 sd) than mean K values (>0.35) previously reported for a wide range of morphological, life history, physiological and behavioral traits from other species. Finally, analyses based on Phylogenetic Generalized Least Squares (PGLS) methods reveal that variation in abundance of some venom proteins, most strongly CRISP is significantly related to snake diet. Our results demonstrate that venom variation in these snakes is evolutionarily a highly labile trait even among very closely-related taxa and that natural selection acting through diet variation may play a role in molding the relative abundance of specific venom proteins.