Evolutionary Shortcuts via Multinucleotide Substitutions and Their Impact on Natural Selection Analyses.

Inference and interpretation of evolutionary processes, in particular of the types and targets of natural selection affecting coding sequences, are critically influenced by the assumptions built into statistical models and tests. If certain aspects of the substitution process (even when they are not of direct interest) are presumed absent or are modeled with too crude of a simplification, estimates of key model parameters can become biased, often systematically, and lead to poor statistical performance. Previous work established that failing to accommodate multinucleotide (or multihit, MH) substitutions strongly biases dN/dS-based inference towards false-positive inferences of diversifying episodic selection, as does failing to model variation in the rate of synonymous substitution (SRV) among sites. Here, we develop an integrated analytical framework and software tools to simultaneously incorporate these sources of evolutionary complexity into selection analyses. We found that both MH and SRV are ubiquitous in empirical alignments, and incorporating them has a strong effect on whether or not positive selection is detected (1.4-fold reduction) and on the distributions of inferred evolutionary rates. With simulation studies, we show that this effect is not attributable to reduced statistical power caused by using a more complex model. After a detailed examination of 21 benchmark alignments and a new high-resolution analysis showing which parts of the alignment provide support for positive selection, we show that MH substitutions occurring along shorter branches in the tree explain a significant fraction of discrepant results in selection detection. Our results add to the growing body of literature which examines decades-old modeling assumptions (including MH) and finds them to be problematic for comparative genomic data analysis. Because multinucleotide substitutions have a significant impact on natural selection detection even at the level of an entire gene, we recommend that selection analyses of this type consider their inclusion as a matter of routine. To facilitate this procedure, we developed, implemented, and benchmarked a simple and well-performing model testing selection detection framework able to screen an alignment for positive selection with two biologically important confounding processes: site-to-site synonymous rate variation, and multinucleotide instantaneous substitutions.

Temporal changes in antibiotic resistance and population structure of methicillin-resistant Staphylococcus pseudintermedius between 2010 and 2021 in the United States.

The aim of this study was to perform a phenotypic and molecular epidemiological survey to determine temporal changes in the antimicrobial resistance and population structure of methicillin-resistant Staphylococcus pseudintermedius (MRSP) in the United States. Samples from 200 S. pseudintermedius isolates were obtained from veterinary diagnostic facilities located in geographic regions sampled approximately ten years ago and compared to samples obtained in 2021. Kirby-Bauer disk diffusion was used to determine antimicrobial susceptibility. geoBURST analysis and MrBayes were used to infer relationships of isolates using MLST data. Almost all MRSP isolates (98%) in 2021 were multidrug-resistant with 21% of these isolates resistant to more than 16 antimicrobials. In 2010, 190 S. pseudintermedius isolates were collected and 141 of them were MRSP. From 2010-2021 there was a significant increase in resistance observed to all antibiotics tested except cephalothin and sulfonamides. Whereas ten years previously multilocus sequence types (ST) ST68 (35.7%), ST71 (10%), and ST84 (17.4%) predominated, these strains have been supplanted by other STs, notably ST45 (n = 14), ST155 (n = 9), ST181 (n = 13), ST496 (n = 9) and ST551 (n = 9). The newly prevalent STs are distantly related to ST68, ST71 and ST84 and most likely do not share any recent common ancestors. The population structure of MRSP is far more elastic than expected with new, highly resistant strains replacing the ones that predominated in the United States a decade ago. Antibiotic use may play a role in selection; however, the strains that were replaced were also multidrug-resistant and other factors are likely involved.

Fast and accurate genome-wide predictions and structural modeling of protein-protein interactions using Galaxy.

BACKGROUND: Protein-protein interactions play a crucial role in almost all cellular processes. Identifying interacting proteins reveals insight into living organisms and yields novel drug targets for disease treatment. Here, we present a publicly available, automated pipeline to predict genome-wide protein-protein interactions and produce high-quality multimeric structural models. RESULTS: Application of our method to the Human and Yeast genomes yield protein-protein interaction networks similar in quality to common experimental methods. We identified and modeled Human proteins likely to interact with the papain-like protease of SARS-CoV2's non-structural protein 3. We also produced models of SARS-CoV2's spike protein (S) interacting with myelin-oligodendrocyte glycoprotein receptor and dipeptidyl peptidase-4. CONCLUSIONS: The presented method is capable of confidently identifying interactions while providing high-quality multimeric structural models for experimental validation. The interactome modeling pipeline is available at usegalaxy.org and usegalaxy.eu.

Natural selection differences detected in key protein domains between non-pathogenic and pathogenic feline coronavirus phenotypes.

Feline coronaviruses (FCoVs) commonly cause mild enteric infections in felines worldwide (termed feline enteric coronavirus [FECV]), with around 12 per cent developing into deadly feline infectious peritonitis (FIP; feline infectious peritonitis virus [FIPV]). Genomic differences between FECV and FIPV have been reported, yet the putative genotypic basis of the highly pathogenic phenotype remains unclear. Here, we used state-of-the-art molecular evolutionary genetic statistical techniques to identify and compare differences in natural selection pressure between FECV and FIPV sequences, as well as to identify FIPV- and FECV-specific signals of positive selection. We analyzed full-length FCoV protein coding genes thought to contain mutations associated with FIPV (Spike, ORF3abc, and ORF7ab). We identified two sites exhibiting differences in natural selection pressure between FECV and FIPV: one within the S1/S2 furin cleavage site (FCS) and the other within the fusion domain of Spike. We also found fifteen sites subject to positive selection associated with FIPV within Spike, eleven of which have not previously been suggested as possibly relevant to FIP development. These sites fall within Spike protein subdomains that participate in host cell receptor interaction, immune evasion, tropism shifts, host cellular entry, and viral escape. There were fourteen sites (twelve novel sites) within Spike under positive selection associated with the FECV phenotype, almost exclusively within the S1/S2 FCS and adjacent to C domain, along with a signal of relaxed selection in FIPV relative to FECV, suggesting that furin cleavage functionality may not be needed for FIPV. Positive selection inferred in ORF7b was associated with the FECV phenotype and included twenty-four positively selected sites, while ORF7b had signals of relaxed selection in FIPV. We found evidence of positive selection in ORF3c in FCoV-wide analyses, but no specific association with the FIPV or FECV phenotype. We hypothesize that some combination of mutations in FECV may contribute to FIP development, and that it is unlikely to be one singular 'switch' mutational event. This work expands our understanding of the complexities of FIP development and provides insights into how evolutionary forces may alter pathogenesis in coronavirus genomes.

Genomes of endangered great hammerhead and shortfin mako sharks reveal historic population declines and high levels of inbreeding in great hammerhead.

Despite increasing threats of extinction to Elasmobranchii (sharks and rays), whole genome-based conservation insights are lacking. Here, we present chromosome-level genome assemblies for the Critically Endangered great hammerhead (Sphyrna mokarran) and the Endangered shortfin mako (Isurus oxyrinchus) sharks, with genetic diversity and historical demographic comparisons to other shark species. The great hammerhead exhibited low genetic variation, with 8.7% of the 2.77 Gbp genome in runs of homozygosity (ROH) > 1 Mbp and 74.4% in ROH >100 kbp. The 4.98 Gbp shortfin mako genome had considerably greater diversity and <1% in ROH > 1 Mbp. Both these sharks experienced precipitous declines in effective population size (Ne) over the last 250 thousand years. While shortfin mako exhibited a large historical Ne that may have enabled the retention of higher genetic variation, the genomic data suggest a possibly more concerning picture for the great hammerhead, and a need for evaluation with additional individuals.

Natural selection differences detected in key protein domains between non-pathogenic and pathogenic Feline Coronavirus phenotypes.

Feline Coronaviruses (FCoVs) commonly cause mild enteric infections in felines worldwide (termed Feline Enteric Coronavirus [FECV]), with around 12% developing into deadly Feline Infectious Peritonitis (FIP; Feline Infectious Peritonitis Virus [FIPV]). Genomic differences between FECV and FIPV have been reported, yet the putative genotypic basis of the highly pathogenic phenotype remains unclear. Here, we used state-of-the-art molecular evolutionary genetic statistical techniques to identify and compare differences in natural selection pressure between FECV and FIPV sequences, as well as to identify FIPV and FECV specific signals of positive selection. We analyzed full length FCoV protein coding genes thought to contain mutations associated with FIPV (Spike, ORF3abc, and ORF7ab). We identified two sites exhibiting differences in natural selection pressure between FECV and FIPV: one within the S1/S2 furin cleavage site, and the other within the fusion domain of Spike. We also found 15 sites subject to positive selection associated with FIPV within Spike, 11 of which have not previously been suggested as possibly relevant to FIP development. These sites fall within Spike protein subdomains that participate in host cell receptor interaction, immune evasion, tropism shifts, host cellular entry, and viral escape. There were 14 sites (12 novel) within Spike under positive selection associated with the FECV phenotype, almost exclusively within the S1/S2 furin cleavage site and adjacent C domain, along with a signal of relaxed selection in FIPV relative to FECV, suggesting that furin cleavage functionality may not be needed for FIPV. Positive selection inferred in ORF7b was associated with the FECV phenotype, and included 24 positively selected sites, while ORF7b had signals of relaxed selection in FIPV. We found evidence of positive selection in ORF3c in FCoV wide analyses, but no specific association with the FIPV or FECV phenotype. We hypothesize that some combination of mutations in FECV may contribute to FIP development, and that is unlikely to be one singular "switch" mutational event. This work expands our understanding of the complexities of FIP development and provides insights into how evolutionary forces may alter pathogenesis in coronavirus genomes.

RASCL: Rapid Assessment of Selection in CLades through molecular sequence analysis.

An important unmet need revealed by the COVID-19 pandemic is the near-real-time identification of potentially fitness-altering mutations within rapidly growing SARS-CoV-2 lineages. Although powerful molecular sequence analysis methods are available to detect and characterize patterns of natural selection within modestly sized gene-sequence datasets, the computational complexity of these methods and their sensitivity to sequencing errors render them effectively inapplicable in large-scale genomic surveillance contexts. Motivated by the need to analyze new lineage evolution in near-real time using large numbers of genomes, we developed the Rapid Assessment of Selection within CLades (RASCL) pipeline. RASCL applies state of the art phylogenetic comparative methods to evaluate selective processes acting at individual codon sites and across whole genes. RASCL is scalable and produces automatically updated regular lineage-specific selection analysis reports: even for lineages that include tens or hundreds of thousands of sampled genome sequences. Key to this performance is (i) generation of automatically subsampled high quality datasets of gene/ORF sequences drawn from a selected "query" viral lineage; (ii) contextualization of these query sequences in codon alignments that include high-quality "background" sequences representative of global SARS-CoV-2 diversity; and (iii) the extensive parallelization of a suite of computationally intensive selection analysis tests. Within hours of being deployed to analyze a novel rapidly growing lineage of interest, RASCL will begin yielding JavaScript Object Notation (JSON)-formatted reports that can be either imported into third-party analysis software or explored in standard web-browsers using the premade RASCL interactive data visualization dashboard. By enabling the rapid detection of genome sites evolving under different selective regimes, RASCL is well-suited for near-real-time monitoring of the population-level selective processes that will likely underlie the emergence of future variants of concern in measurably evolving pathogens with extensive genomic surveillance.

Conserved recombination patterns across coronavirus subgenera.

Recombination contributes to the genetic diversity found in coronaviruses and is known to be a prominent mechanism whereby they evolve. It is apparent, both from controlled experiments and in genome sequences sampled from nature, that patterns of recombination in coronaviruses are non-random and that this is likely attributable to a combination of sequence features that favour the occurrence of recombination break points at specific genomic sites, and selection disfavouring the survival of recombinants within which favourable intra-genome interactions have been disrupted. Here we leverage available whole-genome sequence data for six coronavirus subgenera to identify specific patterns of recombination that are conserved between multiple subgenera and then identify the likely factors that underlie these conserved patterns. Specifically, we confirm the non-randomness of recombination break points across all six tested coronavirus subgenera, locate conserved recombination hot- and cold-spots, and determine that the locations of transcriptional regulatory sequences are likely major determinants of conserved recombination break-point hotspot locations. We find that while the locations of recombination break points are not uniformly associated with degrees of nucleotide sequence conservation, they display significant tendencies in multiple coronavirus subgenera to occur in low guanine-cytosine content genome regions, in non-coding regions, at the edges of genes, and at sites within the Spike gene that are predicted to be minimally disruptive of Spike protein folding. While it is apparent that sequence features such as transcriptional regulatory sequences are likely major determinants of where the template-switching events that yield recombination break points most commonly occur, it is evident that selection against misfolded recombinant proteins also strongly impacts observable recombination break-point distributions in coronavirus genomes sampled from nature.

Human HspB1, HspB3, HspB5 and HspB8: Shaping these disease factors during vertebrate evolution.

Small heat shock proteins (sHSPs) emerged early in evolution and occur in all domains of life and nearly in all species, including humans. Mutations in four sHSPs (HspB1, HspB3, HspB5, HspB8) are associated with neuromuscular disorders. The aim of this study is to investigate the evolutionary forces shaping these sHSPs during vertebrate evolution. We performed comparative evolutionary analyses on a set of orthologous sHSP sequences, based on the ratio of non-synonymous: synonymous substitution rates for each codon. We found that these sHSPs had been historically exposed to different degrees of purifying selection, decreasing in this order: HspB8 > HspB1, HspB5 > HspB3. Within each sHSP, regions with different degrees of purifying selection can be discerned, resulting in characteristic selective pressure profiles. The conserved α-crystallin domains were exposed to the most stringent purifying selection compared to the flanking regions, supporting a 'dimorphic pattern' of evolution. Thus, during vertebrate evolution the different sequence partitions were exposed to different and measurable degrees of selective pressures. Among the disease-associated mutations, most are missense mutations primarily in HspB1 and to a lesser extent in the other sHSPs. Our data provide an explanation for this disparate incidence. Contrary to the expectation, most missense mutations cause dominant disease phenotypes. Theoretical considerations support a connection between the historic exposure of these sHSP genes to a high degree of purifying selection and the unusual prevalence of genetic dominance of the associated disease phenotypes. Our study puts the genetics of inheritable sHSP-borne diseases into the context of vertebrate evolution.

Recent Zoonotic Spillover and Tropism Shift of a Canine Coronavirus Is Associated with Relaxed Selection and Putative Loss of Function in NTD Subdomain of Spike Protein.

A canine coronavirus (CCoV) has now been reported from two independent human samples from Malaysia (respiratory, collected in 2017-2018; CCoV-HuPn-2018) and Haiti (urine, collected in 2017); these two viruses were nearly genetically identical. In an effort to identify any novel adaptations associated with this apparent shift in tropism we carried out detailed evolutionary analyses of the spike gene of this virus in the context of related Alphacoronavirus 1 species. The spike 0-domain retains homology to CCoV2b (enteric infections) and Transmissible Gastroenteritis Virus (TGEV; enteric and respiratory). This domain is subject to relaxed selection pressure and an increased rate of molecular evolution. It contains unique amino acid substitutions, including within a region important for sialic acid binding and pathogenesis in TGEV. Overall, the spike gene is extensively recombinant, with a feline coronavirus type II strain serving a prominent role in the recombinant history of the virus. Molecular divergence time for a segment of the gene where temporal signal could be determined, was estimated at around 60 years ago. We hypothesize that the virus had an enteric origin, but that it may be losing that particular tropism, possibly because of mutations in the sialic acid binding region of the spike 0-domain.

RASCL: Rapid Assessment Of SARS-CoV-2 Clades Through Molecular Sequence Analysis.

An important component of efforts to manage the ongoing COVID19 pandemic is the R apid A ssessment of how natural selection contributes to the emergence and proliferation of potentially dangerous S ARS-CoV-2 lineages and CL ades (RASCL). The RASCL pipeline enables continuous comparative phylogenetics-based selection analyses of rapidly growing clade-focused genome surveillance datasets, such as those produced following the initial detection of potentially dangerous variants. From such datasets RASCL automatically generates down-sampled codon alignments of individual genes/ORFs containing contextualizing background reference sequences, analyzes these with a battery of selection tests, and outputs results as both machine readable JSON files, and interactive notebook-based visualizations. AVAILABILITY: RASCL is available from a dedicated repository at https://github.com/veg/RASCL and as a Galaxy workflow https://usegalaxy.eu/u/hyphy/w/rascl . Existing clade/variant analysis results are available here: https://observablehq.com/@aglucaci/rascl . CONTACT: Dr. Sergei L Kosakovsky Pond ( spond@temple.edu ). SUPPLEMENTARY INFORMATION: N/A.

Maternal high-fat diet is associated with impaired fetal lung development.

Maternal nutrition has a profound long-term impact on infant health. Poor maternal nutrition influences placental development and fetal growth, resulting in low birth weight, which is strongly associated with the risk of developing chronic diseases, including heart disease, hypertension, asthma, and type 2 diabetes, later in life. Few studies have delineated the mechanisms by which maternal nutrition affects fetal lung development. Here, we report that maternal exposure to a diet high in fat (HFD) causes placental inflammation, resulting in placental insufficiency, fetal growth restriction (FGR), and inhibition of fetal lung development. Notably, pre- and postnatal exposure to maternal HFD also results in persistent alveolar simplification in the postnatal period. Our novel findings provide a strong association between maternal diet and fetal lung development.

ERα upregulates Phd3 to ameliorate HIF-1 induced fibrosis and inflammation in adipose tissue.

Hypoxia Inducible Factor 1 (HIF-1) promotes fibrosis and inflammation in adipose tissues, while estrogens and Estrogen Receptor α (ERα) have the opposite effect. Here we identify an Estrogen Response Element (ERE) in the promoter of Phd3, which is a negative regulatory enzyme of HIF-1, and we demonstrate HIF-1α is ubiquitinated following 17-ß estradiol (E2)/ERα mediated Phd3 transcription. Manipulating ERα in vivo increases Phd3 transcription and reduces HIF-1 activity, while addition of PHD3 ameliorates adipose tissue fibrosis and inflammation. Our findings outline a novel regulatory relationship between E2/ERα, PHD3 and HIF-1 in adipose tissues, providing a mechanistic explanation for the protective effect of E2/ERα in adipose tissue.

The sexually dimorphic role of adipose and adipocyte estrogen receptors in modulating adipose tissue expansion, inflammation, and fibrosis.

Our data demonstrate that estrogens, estrogen receptor-α (ERα), and estrogen receptor-ß (ERß) regulate adipose tissue distribution, inflammation, fibrosis, and glucose homeostasis, by determining that αERKO mice have increased adipose tissue inflammation and fibrosis prior to obesity onset. Selective deletion of adipose tissue ERα in adult mice using a novel viral vector technology recapitulated the findings in the total body ERα null mice. Generation of a novel mouse model, lacking ERα specifically from adipocytes (AdipoERα), demonstrated increased markers of fibrosis and inflammation, especially in the males. Additionally, we found that the beneficial effects of estrogens on adipose tissue require adipocyte ERα. Lastly, we determined the role of ERß in regulating inflammation and fibrosis, by breeding the AdipoERα into the ßERKO background and found that in the absence of adipocyte ERα, ERß has a protective role. These data suggest that adipose tissue and adipocyte ERα protects against adiposity, inflammation, and fibrosis in both males and females.