AnnoView enables large-scale analysis, comparison, and visualization of microbial gene neighborhoods.

The analysis and comparison of gene neighborhoods is a powerful approach for exploring microbial genome structure, function, and evolution. Although numerous tools exist for genome visualization and comparison, genome exploration across large genomic databases or user-generated datasets remains a challenge. Here, we introduce AnnoView, a web server designed for interactive exploration of gene neighborhoods across the bacterial and archaeal tree of life. Our server offers users the ability to identify, compare, and visualize gene neighborhoods of interest from 30 238 bacterial genomes and 1672 archaeal genomes, through integration with the comprehensive Genome Taxonomy Database and AnnoTree databases. Identified gene neighborhoods can be visualized using pre-computed functional annotations from different sources such as KEGG, Pfam and TIGRFAM, or clustered based on similarity. Alternatively, users can upload and explore their own custom genomic datasets in GBK, GFF or CSV format, or use AnnoView as a genome browser for relatively small genomes (e.g. viruses and plasmids). Ultimately, we anticipate that AnnoView will catalyze biological discovery by enabling user-friendly search, comparison, and visualization of genomic data. AnnoView is available at http://annoview.uwaterloo.ca.

Evaluation of multiple displacement amplification for metagenomic analysis of low biomass samples.

Combining multiple displacement amplification (MDA) with metagenomics enables the analysis of samples with extremely low DNA concentrations, making them suitable for high-throughput sequencing. Although amplification bias and nonspecific amplification have been reported from MDA-amplified samples, the impact of MDA on metagenomic datasets is not well understood. We compared three MDA methods (i.e. bulk MDA, emulsion MDA, and primase MDA) for metagenomic analysis of two DNA template concentrations (approx. 1 and 100 pg) derived from a microbial community standard "mock community" and two low biomass environmental samples (i.e. borehole fluid and groundwater). We assessed the impact of MDA on metagenome-based community composition, assembly quality, functional profiles, and binning. We found amplification bias against high GC content genomes but relatively low nonspecific amplification such as chimeras, artifacts, or contamination for all MDA methods. We observed MDA-associated representational bias for microbial community profiles, especially for low-input DNA and with the primase MDA method. Nevertheless, similar taxa were represented in MDA-amplified libraries to those of unamplified samples. The MDA libraries were highly fragmented, but similar functional profiles to the unamplified libraries were obtained for bulk MDA and emulsion MDA at higher DNA input and across these MDA libraries for the groundwater sample. Medium to low-quality bins were possible for the high input bulk MDA metagenomes for the most simple microbial communities, borehole fluid, and mock community. Although MDA-based amplification should be avoided, it can still reveal meaningful taxonomic and functional information from samples with extremely low DNA concentration where direct metagenomics is otherwise impossible.

Nasopharyngeal metatranscriptomics reveals host-pathogen signatures of pediatric sinusitis.

Acute sinusitis (AS) is the fifth leading cause of antibiotic prescriptions in children. Distinguishing bacterial AS from common viral upper respiratory infections in children is crucial to prevent unnecessary antibiotic use but is challenging with current diagnostic methods. Despite its speed and cost, untargeted RNA sequencing of clinical samples from children with suspected AS has the potential to overcome several limitations of other methods. However, the utility of sequencing-based approaches in analysis of AS has not been fully explored. Here, we performed RNA-seq of nasopharyngeal samples from 221 children with clinically diagnosed AS to characterize their pathogen and host-response profiles. Results from RNA-seq were compared with those obtained using culture for three common bacterial pathogens and qRT-PCR for 12 respiratory viruses. Metatranscriptomic pathogen detection showed high concordance with culture or qRT-PCR, showing 87%/81% sensitivity (sens) / specificity (spec) for detecting bacteria, and 86%/92% (sens/spec) for viruses, respectively. We also detected an additional 22 pathogens not tested for in the clinical panel, and identified plausible pathogens in 11/19 (58%) of cases where no organism was detected by culture or qRT-PCR. We assembled genomes of 205 viruses across the samples including novel strains of coronaviruses, respiratory syncytial virus (RSV), and enterovirus D68. By analyzing host gene expression, we identified host-response signatures that distinguished bacterial and viral infections and correlated with pathogen abundance. Ultimately, our study demonstrates the potential of untargeted metatranscriptomics for in depth analysis of the etiology of AS, comprehensive host-response profiling, and using these together to work towards optimized patient care.

Genomic and transcriptomic characterization of delta SARS-CoV-2 infection in free-ranging white-tailed deer (Odocoileus virginianus).

White-tailed deer (WTD) are susceptible to SARS-CoV-2 and represent an important species for surveillance. Samples from WTD (n = 258) collected in November 2021 from Québec, Canada were analyzed for SARS-CoV-2 RNA. We employed viral genomics and host transcriptomics to further characterize infection and investigate host response. We detected Delta SARS-CoV-2 (B.1.617.2) in WTD from the Estrie region; sequences clustered with human sequences from October 2021 from Vermont, USA, which borders this region. Mutations in the S-gene and a deletion in ORF8 were detected. Host expression patterns in SARS-CoV-2 infected WTD were associated with the innate immune response, including signaling pathways related to anti-viral, pro- and anti-inflammatory signaling, and host damage. We found limited correlation between genes associated with innate immune response from human and WTD nasal samples, suggesting differences in responses to SARS-CoV-2 infection. Our findings provide preliminary insights into host response to SARS-CoV-2 infection in naturally infected WTD.

Cannabis smoke suppresses antiviral immune responses to influenza A in mice.

Rationale: Despite its increasingly widespread use, little is known about the impact of cannabis smoking on the response to viral infections like influenza A virus (IAV). Many assume that cannabis smoking will disrupt antiviral responses in a manner similar to cigarette smoking; however, since cannabinoids exhibit anti-inflammatory effects, cannabis smoke exposure may impact viral infection in distinct ways. Methods: Male and female BALB/c mice were exposed daily to cannabis smoke and concurrently intranasally instilled with IAV. Viral burden, inflammatory mediator levels (multiplex ELISA), lung immune cells populations (flow cytometry) and gene expression patterns (RNA sequencing) were assessed in the lungs. Plasma IAV-specific antibodies were measured via ELISA. Results: We found that cannabis smoke exposure increased pulmonary viral burden while decreasing total leukocytes, including macrophages, monocytes and dendritic cell populations in the lungs. Furthermore, infection-induced upregulation of certain inflammatory mediators (interferon-γ and C-C motif chemokine ligand 5) was blunted by cannabis smoke exposure, which in females was linked to the transcriptional downregulation of pathways involved in innate and adaptive immune responses. Finally, plasma levels of IAV-specific IgM and IgG1 were significantly decreased in cannabis smoke-exposed, infected mice compared to infected controls, only in female mice. Conclusions: Overall, cannabis smoke exposure disrupted host-defence processes, leading to increased viral burden and dampened inflammatory signalling. These results suggest that cannabis smoking is detrimental to the maintenance of pulmonary homeostasis during viral infection and highlight the need for data regarding the impact on immune competency in humans.

Genomic classification and antimicrobial resistance profiling of Streptococcus pneumoniae and Haemophilus influenza isolates associated with paediatric otitis media and upper respiratory infection.

Acute otitis media (AOM) is the most common childhood bacterial infectious disease requiring antimicrobial therapy. Most cases of AOM are caused by translocation of Streptococcus pneumoniae or Haemophilus influenzae from the nasopharynx to the middle ear during an upper respiratory tract infection (URI). Ongoing genomic surveillance of these pathogens is important for vaccine design and tracking of emerging variants, as well as for monitoring patterns of antibiotic resistance to inform treatment strategies and stewardship.In this work, we examined the ability of a genomics-based workflow to determine microbiological and clinically relevant information from cultured bacterial isolates obtained from patients with AOM or an URI. We performed whole genome sequencing (WGS) and analysis of 148 bacterial isolates cultured from the nasopharynx (N = 124, 94 AOM and 30 URI) and ear (N = 24, all AOM) of 101 children aged 6-35 months presenting with AOM or an URI. We then performed WGS-based sequence typing and antimicrobial resistance profiling of each strain and compared results to those obtained from traditional microbiological phenotyping.WGS of clinical isolates resulted in 71 S. pneumoniae genomes and 76 H. influenzae genomes. Multilocus sequencing typing (MSLT) identified 33 sequence types for S. pneumoniae and 19 predicted serotypes including the most frequent serotypes 35B and 3. Genome analysis predicted 30% of S. pneumoniae isolates to have complete or intermediate penicillin resistance. AMR predictions for S. pneumoniae isolates had strong agreement with clinical susceptibility testing results for beta-lactam and non beta-lactam antibiotics, with a mean sensitivity of 93% (86-100%) and a mean specificity of 98% (94-100%). MLST identified 29 H. influenzae sequence types. Genome analysis identified beta-lactamase genes in 30% of H. influenzae strains, which was 100% in agreement with clinical beta-lactamase testing. We also identified a divergent highly antibiotic-resistant strain of S. pneumoniae, and found its closest sequenced strains, also isolated from nasopharyngeal samples from over 15 years ago.Ultimately, our work provides the groundwork for clinical WGS-based workflows to aid in detection and analysis of H. influenzae and S. pneumoniae isolates.

Ancient Clostridium DNA and variants of tetanus neurotoxins associated with human archaeological remains.

The analysis of microbial genomes from human archaeological samples offers a historic snapshot of ancient pathogens and provides insights into the origins of modern infectious diseases. Here, we analyze metagenomic datasets from 38 human archaeological samples and identify bacterial genomic sequences related to modern-day Clostridium tetani, which produces the tetanus neurotoxin (TeNT) and causes the disease tetanus. These genomic assemblies had varying levels of completeness, and a subset of them displayed hallmarks of ancient DNA damage. Phylogenetic analyses revealed known C. tetani clades as well as potentially new Clostridium lineages closely related to C. tetani. The genomic assemblies encode 13 TeNT variants with unique substitution profiles, including a subgroup of TeNT variants found exclusively in ancient samples from South America. We experimentally tested a TeNT variant selected from an ancient Chilean mummy sample and found that it induced tetanus muscle paralysis in mice, with potency comparable to modern TeNT. Thus, our ancient DNA analysis identifies DNA from neurotoxigenic C. tetani in archaeological human samples, and a novel variant of TeNT that can cause disease in mammals.

Phylogenomic Analysis of 155 Helminth Species Reveals Widespread Absence of Oxygen Metabolic Capacity.

The terminal electron acceptor of most aerobic respiratory chains, cytochrome c oxidase (COX), has been highly conserved throughout evolution, from aerobic prokaryotes to complex eukaryotes. Oxygen metabolism in parasitic helminths differs significantly from that of most aerobic eukaryotes, as these organisms can switch between aerobic and anaerobic metabolisms throughout their life cycles. Early studies suggested a lack of COX activity in certain parasitic helminths, and the role of COX in helminth mitochondria remains unclear. To determine whether a functional COX is widely present in helminths, we analyzed the phylogenetic distribution of oxygen metabolism systems across 155 helminth genomes, investigating three distinct sets of protein-coding genes involved in different aspects of oxygen metabolism: COX and its assembly factors, peroxisomes, and the most abundant reactive oxygen species (ROS)-metabolizing proteins. While glycolytic and citric acid cycle enzymes are highly conserved in helminthic species, we observed an apparent widespread absence of essential COX genes across 52% of helminth species investigated. While the most common proteins involved in the defense against ROS are highly maintained across virtually all lineages, we also observed an apparent absence of essential peroxisomal protein-coding genes in 42% of species investigated. Our results suggest that a subset of parasitic helminths utilize oxygen differently from related, nonparasitic species such as Caenorhabditis elegans, with significant differences in their mitochondrial electron transport chains and peroxisomes. The identification of substantive differences between parasite and host metabolism offers a new avenue for the development of anthelmintic agents that could target these divergent pathways.

A Machine Learning Framework Identifies Plastid-Encoded Proteins Harboring C3 and C4 Distinguishing Sequence Information.

C4 photosynthesis is known to have at least 61 independent origins across plant lineages making it one of the most notable examples of convergent evolution. Of the >60 independent origins, a predicted 22-24 origins, encompassing greater than 50% of all known C4 species, exist within the Panicoideae, Arundinoideae, Chloridoideae, Micrairoideae, Aristidoideae, and Danthonioideae (PACMAD) clade of the Poaceae family. This clade is therefore primed with species ideal for the study of genomic changes associated with the acquisition of the C4 photosynthetic trait. In this study, we take advantage of the growing availability of sequenced plastid genomes and employ a machine learning (ML) approach to screen for plastid genes harboring C3 and C4 distinguishing information in PACMAD species. We demonstrate that certain plastid-encoded protein sequences possess distinguishing and informative sequence information that allows them to train accurate ML C3/C4 classification models. Our RbcL-trained model, for example, informs a C3/C4 classifier with greater than 99% accuracy. Accurate prediction of photosynthetic type from individual sequences suggests biologically relevant, and potentially differing roles of these sequence products in C3 versus C4 metabolism. With this ML framework, we have identified several key sequences and sites that are most predictive of C3/C4 status, including RbcL, subunits of the NAD(P)H dehydrogenase complex, and specific residues within, further highlighting their potential significance in the evolution and/or maintenance of C4 photosynthetic machinery. This general approach can be applied to uncover intricate associations between other similar genotype-phenotype relationships.

Functional Profiling and Evolutionary Analysis of a Marine Microalgal Virus Pangenome.

Phycodnaviridae are large double-stranded DNA viruses, which facilitate studies of host-virus interactions and co-evolution due to their prominence in algal infection and their role in the life cycle of algal blooms. However, the genomic interpretation of these viruses is hampered by a lack of functional information, stemming from the surprising number of hypothetical genes of unknown function. It is also unclear how many of these genes are widely shared within the clade. Using one of the most extensively characterized genera, Coccolithovirus, as a case study, we combined pangenome analysis, multiple functional annotation tools, AlphaFold structural modeling, and literature analysis to compare the core and accessory pangenome and assess support for novel functional predictions. We determined that the Coccolithovirus pangenome shares 30% of its genes with all 14 strains, making up the core. Notably, 34% of its genes were found in at most three strains. Core genes were enriched in early expression based on a transcriptomic dataset of Coccolithovirus EhV-201 algal infection, were more likely to be similar to host proteins than the non-core set, and were more likely to be involved in vital functions such as replication, recombination, and repair. In addition, we generated and collated annotations for the EhV representative EhV-86 from 12 different annotation sources, building up information for 142 previously hypothetical and putative membrane proteins. AlphaFold was further able to predict structures for 204 EhV-86 proteins with a modelling accuracy of good-high. These functional clues, combined with generated AlphaFold structures, provide a foundational framework for the future characterization of this model genus (and other giant viruses) and a further look into the evolution of the Coccolithovirus proteome.

Comparative analysis of adenylate isopentenyl transferase genes in plant growth-promoting bacteria and plant pathogenic bacteria.

Cytokinin is a major phytohormone that has been used in agriculture as a plant-growth stimulating compound since its initial discovery in the 1960s. Isopentenyl transferase (IPT) is a rate-limiting enzyme for cytokinin biosynthesis, which is produced by plants as well as bacteria including both plant pathogenic species and plant growth-promoting bacteria (PGPB). It has been hypothesized that there may be differences in IPT function between plant pathogens and PGPB. However, a comprehensive comparison of IPT genes between plant pathogenic and PGPB species has not been performed. Here, we performed a global comparison of IPT genes across bacteria, analyzing their DNA sequences, codon usage, phyletic distribution, promoter structure and genomic context. We found that adenylate type IPT genes are highly specific to plant-associated bacteria and subdivide into two major clades: clade A, largely composed of proteobacterial plant pathogens; and clade B, largely composed of actinomycete PGPB species. Besides these phylogenetic differences, we identified several genomic features that suggest differences in IPT regulation between pathogens and PGPB. Pathogen-associated IPTs tended to occur in predicted virulence loci, whereas PGPB-associated IPTs tended to co-occur with other genes involved in cytokinin metabolism and degradation. Pathogen-associated IPTs also showed elevated gene copy numbers, significant deviation in codon usage patterns, and extended promoters, suggesting differences in regulation and activity levels. Our results are consistent with the hypothesis that differences in IPT regulation and activity exist between plant pathogens and PGPB, which determine their effect on plant host phenotypes through the control of cytokinin levels.

Identification of TFPI as a receptor reveals recombination-driven receptor switching in Clostridioides difficile toxin B variants.

Toxin B (TcdB) is a major exotoxin responsible for diseases associated with Clostridioides difficile infection. Its sequence variations among clinical isolates may contribute to the difficulty in developing effective therapeutics. Here, we investigate receptor-binding specificity of major TcdB subtypes (TcdB1 to TcdB12). We find that representative members of subtypes 2, 4, 7, 10, 11, and 12 do not recognize the established host receptor, frizzled proteins (FZDs). Using a genome-wide CRISPR-Cas9-mediated screen, we identify tissue factor pathway inhibitor (TFPI) as a host receptor for TcdB4. TFPI is recognized by a region in TcdB4 that is homologous to the FZD-binding site in TcdB1. Analysis of 206 TcdB variant sequences reveals a set of six residues within this receptor-binding site that defines a TFPI binding-associated haplotype (designated B4/B7) that is present in all TcdB4 members, a subset of TcdB7, and one member of TcdB2. Intragenic micro-recombination (IR) events have occurred around this receptor-binding region in TcdB7 and TcdB2 members, resulting in either TFPI- or FZD-binding capabilities. Introduction of B4/B7-haplotype residues into TcdB1 enables dual recognition of TFPI and FZDs. Finally, TcdB10 also recognizes TFPI, although it does not belong to the B4/B7 haplotype, and shows species selectivity: it recognizes TFPI of chicken and to a lesser degree mouse, but not human, dog, or cattle versions. These findings identify TFPI as a TcdB receptor and reveal IR-driven changes on receptor-specificity among TcdB variants.

Identification and characterization of a novel peptide from rainbow trout (Oncorhynchus mykiss) with antimicrobial activity against Streptococcus iniae.

The overuse and misuse of antibiotics has led to the emergence of antibiotic-resistant bacterial species which remain a challenge to treat therapeutically. Novel and efficacious drugs are desperately needed to combat pathogens. One method to facilitate these discoveries is the use of in silico methods. Computational biology has the power to scan large data sets and screen for potential molecules with antibacterial function. In the current study, an in silico approach was used to identify an antimicrobial peptide (AMP) derived from rainbow trout von Willebrand Factor. The AMP was tested against a panel of aquatic bacterial pathogens and was found to possess antibacterial activity against Streptococcus iniae (S. iniae). Since S. iniae is a zoonotic pathogen, this may be useful in other species as well. The peptide was non-hemolytic and non-cytotoxic at the concentrations tested in rainbow trout cells. Pre-treatment of rainbow trout cells with the peptide did not result in an upregulation of immune genes but stimulating the rainbow trout macrophage/monocyte-like cell line, RTS11, with heat-killed S. iniae, did result in a significant upregulation of the tumor necrosis factor alpha (tnfa) gene. In this study, a new AMP has been identified but its expression, synthesis and role in vivo remains unknown. Nevertheless, the findings presented improve our understanding of fish gill and macrophage responses towards this important zoonotic pathogen.

Glutamine Metabolism Mediates Sensitivity to Respiratory Complex II Inhibition in Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is a hematologic malignancy metabolically dependent on oxidative phosphorylation and mitochondrial electron transport chain (ETC) activity. AML cells are distinct from their normal hematopoietic counterparts by this metabolic reprogramming, which presents targets for new selective therapies. Here, metabolic changes in AML cells after ETC impairment are investigated. Genetic knockdown of the ETC complex II (CII) chaperone protein SDHAF1 (succinate dehydrogenase assembly factor 1) suppressed CII activity and delayed AML cell growth in vitro and in vivo. As a result, a novel small molecule that directly binds to the ubiquinone binding site of CII and inhibits its activity was identified. Pharmacologic inhibition of CII induced selective death of AML cells while sparing normal hematopoietic progenitors. Through stable isotope tracing, results show that genetic or pharmacologic inhibition of CII truncates the tricarboxylic acid cycle (TCA) and leads to anaplerotic glutamine metabolism to reestablish the truncated cycle. The inhibition of CII showed divergent fates, as AML cells lacked the metabolic plasticity to adequately utilize glutamine metabolism, resulting in preferential depletion of key TCA metabolites and death; normal cells were unaffected. These findings provide insight into the metabolic mechanisms that underlie AML's selective inhibition of CII. IMPLICATIONS: This work highlights the effects of direct CII inhibition in mediating selective AML cell death and provides insights into glutamine anaplerosis as a metabolic adaptation that can be therapeutically targeted.

Intronic regulation of SARS-CoV-2 receptor (ACE2) expression mediated by immune signaling and oxidative stress pathways.

The angiotensin-converting enzyme 2 (ACE2) protein is a key catalytic regulator of the renin-angiotensin system (RAS), involved in fluid homeostasis and blood pressure modulation. ACE2 also serves as a cell-surface receptor for some coronaviruses such as SARS-CoV and SARS-CoV-2. Improved characterization of ACE2 regulation may help us understand the effects of pre-existing conditions on COVID-19 incidence, as well as pathogenic dysregulation following viral infection. Here, we perform bioinformatic analyses to hypothesize on ACE2 gene regulation in two different physiological contexts, identifying putative regulatory elements of ACE2 expression. We perform functional validation of our computational predictions via targeted CRISPR-Cas9 deletions of these elements in vitro, finding them responsive to immune signaling and oxidative-stress pathways. This contributes to our understanding of ACE2 gene regulation at baseline and immune challenge. Our work supports pursuit of these putative mechanisms in our understanding of infection/disease caused by current, and future, SARS-related viruses such as SARS-CoV-2.

Structures of distant diphtheria toxin homologs reveal functional determinants of an evolutionarily conserved toxin scaffold.

Diphtheria toxin (DT) is the archetype for bacterial exotoxins implicated in human diseases and has played a central role in defining the field of toxinology since its discovery in 1888. Despite being one of the most extensively characterized bacterial toxins, the origins and evolutionary adaptation of DT to human hosts remain unknown. Here, we determined the first high-resolution structures of DT homologs outside of the Corynebacterium genus. DT homologs from Streptomyces albireticuli (17% identity to DT) and Seinonella peptonophila (20% identity to DT), despite showing no toxicity toward human cells, display significant structural similarities to DT sharing both the overall Y-shaped architecture of DT as well as the individual folds of each domain. Through a systematic investigation of individual domains, we show that the functional determinants of host range extend beyond an inability to bind cellular receptors; major differences in pH-induced pore-formation and cytosolic release further dictate the delivery of toxic catalytic moieties into cells, thus providing multiple mechanisms for a conserved structural fold to adapt to different hosts. Our work provides structural insights into the expanding DT family of toxins, and highlights key transitions required for host adaptation.

"From Protein Toxins to Applied Toxicological Testing" virtual workshop identifies the need for a bioinformatic framework to assess novel food protein safety.

On October 21-22, 2020 the HESI (Health and Environmental Sciences Institute) Protein Allergens, Toxins, and Bioinformatics Committee, and the Society of Toxicology Food Safety Specialty Section co-hosted a virtual workshop titled "From Protein Toxins to Applied Toxicological Testing". The workshop focused on the safety assessment of novel proteins contained in foods and feeds, was globally represented by over 200 stakeholder attendees, and featured contributions from experts in academia, government and non-government organizations, and agricultural biotechnology developers from the private sector. A range of topics relevant to novel protein safety were discussed, including: the state of protein toxin biology, modes and mechanisms of action, structures and activity, use of bioinformatic analyses to assess the safety of a protein, and ways to leverage computational biology with in silico approaches for protein toxin identification/characterization. Key outcomes of the workshop included the appreciation of the complexity of developing a definition for a protein toxin when viewed from the perspective of food and feed safety, confirming the need for a case-by-case hypothesis-driven interpretation of bioinformatic results that leverages additional metadata rather than an alignment threshold-driven interpretation, and agreement that a "toxin protein database" is not necessary, as the bioinformatic needs for toxin detection may be accomplished by existing databases such as Pfam and UniProtKB/Swiss-Prot. In this paper, a path forward is proposed.

Potentiation of long-acting ß2-agonist and glucocorticoid responses in human airway epithelial cells by modulation of intracellular cAMP.

INTRODUCTION: Over 300 million people in the world live with asthma, resulting in 500,000 annual global deaths with future increases expected. It is estimated that around 50-80% of asthma exacerbations are due to viral infections. Currently, a combination of long-acting beta agonists (LABA) for bronchodilation and glucocorticoids (GCS) to control lung inflammation represent the dominant strategy for the management of asthma, however, it is still sub-optimal in 35-50% of moderate-severe asthmatics resulting in persistent lung inflammation, impairment of lung function, and risk of mortality. Mechanistically, LABA/GCS combination therapy results in synergistic efficacy mediated by intracellular cyclic adenosine monophosphate (cAMP). HYPOTHESIS: Increasing intracellular cAMP during LABA/GCS combination therapy via inhibiting phosphodiesterase 4 (PDE4) and/or blocking the export of cAMP by ATP Binding Cassette Transporter C4 (ABCC4), will potentiate anti-inflammatory responses of mainstay LABA/GCS therapy. METHODS: Expression and localization experiments were performed using in situ hybridization and immunohistochemistry in human lung tissue from healthy subjects, while confirmatory transcript and protein expression analyses were performed in primary human airway epithelial cells and cell lines. Intervention experiments were performed on the human airway epithelial cell line, HBEC-6KT, by pre-treatment with combinations of LABA/GCS with PDE4 and/or ABCC4 inhibitors followed by Poly I:C or imiquimod challenge as a model for viral stimuli. Cytokine readouts for IL-6, IL-8, CXCL10/IP-10, and CCL5/RANTES were quantified by ELISA. RESULTS: Using archived human lung and human airway epithelial cells, ABCC4 gene and protein expression were confirmed in vitro and in situ. LABA/GCS attenuation of Poly I:C or imiquimod-induced IL-6 and IL-8 were potentiated with ABCC4 and PDE4 inhibition, which was greater when ABCC4 and PDE4 inhibition was combined. Modulation of cAMP levels had no impact on LABA/GCS modulation of Poly I:C-induced CXCL10/IP-10 or CCL5/RANTES. CONCLUSION: Modulation of intracellular cAMP levels by PDE4 or ABCC4 inhibition potentiates LABA/GCS efficacy in human airway epithelial cells challenged with viral stimuli. The data suggest further exploration of the value of adding cAMP modulators to mainstay LABA/GCS therapy in asthma for potentiated anti-inflammatory efficacy.

PathFams: statistical detection of pathogen-associated protein domains.

BACKGROUND: A substantial fraction of genes identified within bacterial genomes encode proteins of unknown function. Identifying which of these proteins represent potential virulence factors, and mapping their key virulence determinants, is a challenging but important goal. RESULTS: To facilitate virulence factor discovery, we performed a comprehensive analysis of 17,929 protein domain families within the Pfam database, and scored them based on their overrepresentation in pathogenic versus non-pathogenic species, taxonomic distribution, relative abundance in metagenomic datasets, and other factors. CONCLUSIONS: We identify pathogen-associated domain families, candidate virulence factors in the human gut, and eukaryotic-like mimicry domains with likely roles in virulence. Furthermore, we provide an interactive database called PathFams to allow users to explore pathogen-associated domains as well as identify pathogen-associated domains and domain architectures in user-uploaded sequences of interest. PathFams is freely available at https://pathfams.uwaterloo.ca .

Experimental and natural evidence of SARS-CoV-2-infection-induced activation of type I interferon responses.

Type I interferons (IFNs) are our first line of defense against virus infection. Recent studies have suggested the ability of SARS-CoV-2 proteins to inhibit IFN responses. Emerging data also suggest that timing and extent of IFN production is associated with manifestation of COVID-19 severity. In spite of progress in understanding how SARS-CoV-2 activates antiviral responses, mechanistic studies into wild-type SARS-CoV-2-mediated induction and inhibition of human type I IFN responses are scarce. Here we demonstrate that SARS-CoV-2 infection induces a type I IFN response in vitro and in moderate cases of COVID-19. In vitro stimulation of type I IFN expression and signaling in human airway epithelial cells is associated with activation of canonical transcriptions factors, and SARS-CoV-2 is unable to inhibit exogenous induction of these responses. Furthermore, we show that physiological levels of IFNα detected in patients with moderate COVID-19 is sufficient to suppress SARS-CoV-2 replication in human airway cells.