Post-COVID symptoms are associated with endotypes reflecting poor inflammatory and hemostatic modulation

IntroductionPersistent symptoms after COVID-19 infection (“long COVID”) negatively affects almost half of COVID-19 survivors. Despite its prevalence, its pathophysiology is poorly understood, with multiple host systems likely affected. Here, we followed patients from hospital to discharge and used a systems-biology approach to identify mechanisms of long COVID.MethodsRNA-seq was performed on whole blood collected early in hospital and 4-12 weeks after discharge from 24 adult COVID-19 patients (10 reported post-COVID symptoms after discharge). Differential gene expression analysis, pathway enrichment, and machine learning methods were used to identify underlying mechanisms for post-COVID symptom development.ResultsCompared to patients with post-COVID symptoms, patients without post-COVID symptoms had larger temporal gene expression changes associated with downregulation of inflammatory and coagulation genes over time. Patients could also be separated into three patient endotypes with differing mechanistic trajectories, which was validated in another published patient cohort. The “Resolved” endotype (lowest rate of post-COVID symptoms) had robust inflammatory and hemostatic responses in hospital that resolved after discharge. Conversely, the inflammatory/hemostatic responses of “Suppressive” and “Unresolved” endotypes (higher rates of patients with post-COVID symptoms) were persistently dampened and activated, respectively. These endotypes were accurately defined by specific blood gene expression signatures (6-7 genes) for potential clinical stratification.DiscussionThis study allowed analysis of long COVID whole blood transcriptomics trajectories while accounting for the issue of patient heterogeneity. Two of the three identified and externally validated endotypes (“Unresolved” and “Suppressive”) were associated with higher rates of post-COVID symptoms and either persistently activated or suppressed inflammation and coagulation processes. Gene biomarkers in blood could potentially be used clinically to stratify patients into different endotypes, paving the way for personalized long COVID treatment

Multi-Omic Data Integration Allows Baseline Immune Signatures to Predict Hepatitis B Vaccine Response in a Small Cohort

Background: Vaccination remains one of the most effective means of reducing the burden of infectious diseases globally. Improving our understanding of the molecular basis for effective vaccine response is of paramount importance if we are to ensure the success of future vaccine development efforts. Methods: We applied cutting edge multi-omics approaches to extensively characterize temporal molecular responses following vaccination with hepatitis B virus (HBV) vaccine. Data were integrated across cellular, epigenomic, transcriptomic, proteomic, and fecal microbiome profiles, and correlated to final HBV antibody titres. Results: Using both an unsupervised molecular-interaction network integration method (NetworkAnalyst) and a data-driven integration approach (DIABLO), we uncovered baseline molecular patterns and pathways associated with more effective vaccine responses to HBV. Biological associations were unravelled, with signalling pathways such as JAK-STAT and interleukin signalling, Toll-like receptor cascades, interferon signalling, and Th17 cell differentiation emerging as important pre-vaccination modulators of response. Conclusion: This study provides further evidence that baseline cellular and molecular characteristics of an individual’s immune system influence vaccine responses, and highlights the utility of integrating information across many parallel molecular datasets

Host Response of Human Epidermis to Methicillin-Resistant Staphylococcus aureus Biofilm Infection and Synthetic Antibiofilm Peptide Treatment

Bacterial biofilm infections associated with wounded skin are prevalent, recalcitrant, and in urgent need of treatments. Additionally, host responses in the skin to biofilm infections are not well understood. Here we employed a human organoid skin model to explore the transcriptomic changes of thermally-injured epidermis to methicillin-resistant Staphylococcus aureus (MRSA) biofilm colonization. MRSA biofilm impaired skin barrier function, enhanced extracellular matrix remodelling, elicited inflammatory responses including IL-17, IL-12 family and IL-6 family interleukin signalling, and modulated skin metabolism. Synthetic antibiofilm peptide DJK-5 effectively diminished MRSA biofilm and associated skin inflammation in wounded human ex vivo skin. In the epidermis, DJK-5 shifted the overall skin transcriptome towards homeostasis including modulating the biofilm induced inflammatory response, promoting the skin DNA repair function, and downregulating MRSA invasion of thermally damaged skin. These data clarified the underlying immunopathogenesis of biofilm infections and revealed the intrinsic promise of synthetic peptides in reducing inflammation and biofilm infections

Surfing motility is a complex adaptation dependent on the stringent stress response in Pseudomonas aeruginosa LESB58.

Cystic fibrosis (CF) is a genetic disease that affects mucin-producing body organs such as the lungs. Characteristic of CF is the production of thick, viscous mucus, containing the glycoprotein mucin, that can lead to progressive airway obstruction. Recently, we demonstrated that the presence of mucin induced a rapid surface adaptation in motile bacteria termed surfing motility, which data presented here indicates is very different from swarming motility. Pseudomonas aeruginosa, the main colonizing pathogen in CF, employs several stress coping mechanisms to survive the highly viscous environment of the CF lung. We used motility-based assays and RNA-Seq to study the stringent stress response in the hypervirulent CF isolate LESB58 (Liverpool Epidemic Strain). Motility experiments revealed that an LESB58 stringent response mutant (ΔrelAΔspoT) was unable to surf. Transcriptional profiling of ΔrelAΔspoT mutant cells from surfing agar plates, when compared to wild-type cells from the surfing edge, revealed 2,584 dysregulated genes. Gene Ontology and KEGG enrichment analysis revealed effects of the stringent response on amino acid, nucleic acid and fatty acid metabolism, TCA cycle and glycolysis, type VI secretion, as well as chemotaxis, cell communication, iron transport, nitrogen metabolic processes and cyclic-di-GMP signalling. Screening of the ordered PA14 transposon library revealed 224 mutants unable to surf and very limited overlap with genes required for swarming. Mutants affecting surfing included two downstream effector genes of the stringent stress response, the copper regulator cueR and the quinolone synthase pqsH. Both the cueR and pqsH cloned genes complemented the surfing deficiency of ΔrelAΔspoT. Our study revealed insights into stringent stress dependency in LESB58 and showed that surfing motility is stringently-controlled via the expression of cueR and pqsH. Downstream factors of the stringent stress response are important to investigate in order to fully understand its ability to colonize and persist in the CF lung

Machine Learning-Based Single Cell and Integrative Analysis Reveals That Baseline mDC Predisposition Correlates With Hepatitis B Vaccine Antibody Response

Vaccination to prevent infectious disease is one of the most successful public health interventions ever developed. And yet, variability in individual vaccine effectiveness suggests that a better mechanistic understanding of vaccine-induced immune responses could improve vaccine design and efficacy. We have previously shown that protective antibody levels could be elicited in a subset of recipients with only a single dose of the hepatitis B virus (HBV) vaccine and that a wide range of antibody levels were elicited after three doses. The immune mechanisms responsible for this vaccine response variability is unclear. Using single cell RNA sequencing of sorted innate immune cell subsets, we identified two distinct myeloid dendritic cell subsets (NDRG1-expressing mDC2 and CDKN1C-expressing mDC4), the ratio of which at baseline (pre-vaccination) correlated with the immune response to a single dose of HBV vaccine. Our results suggest that the participants in our vaccine study were in one of two different dendritic cell dispositional states at baseline - an NDRG2-mDC2 state in which the vaccine elicited an antibody response after a single immunization or a CDKN1C-mDC4 state in which the vaccine required two or three doses for induction of antibody responses. To explore this correlation further, genes expressed in these mDC subsets were used for feature selection prior to the construction of predictive models using supervised canonical correlation machine learning. The resulting models showed an improved correlation with serum antibody titers in response to full vaccination. Taken together, these results suggest that the propensity of circulating dendritic cells toward either activation or suppression, their "dispositional endotype" at pre-vaccination baseline, could dictate response to vaccination

Multi-Omic Data Integration Allows Baseline Immune Signatures to Predict Hepatitis B Vaccine Response in a Small Cohort

BackgroundVaccination remains one of the most effective means of reducing the burden of infectious diseases globally. Improving our understanding of the molecular basis for effective vaccine response is of paramount importance if we are to ensure the success of future vaccine development efforts.MethodsWe applied cutting edge multi-omics approaches to extensively characterize temporal molecular responses following vaccination with hepatitis B virus (HBV) vaccine. Data were integrated across cellular, epigenomic, transcriptomic, proteomic, and fecal microbiome profiles, and correlated to final HBV antibody titres.ResultsUsing both an unsupervised molecular-interaction network integration method (NetworkAnalyst) and a data-driven integration approach (DIABLO), we uncovered baseline molecular patterns and pathways associated with more effective vaccine responses to HBV. Biological associations were unravelled, with signalling pathways such as JAK-STAT and interleukin signalling, Toll-like receptor cascades, interferon signalling, and Th17 cell differentiation emerging as important pre-vaccination modulators of response.ConclusionThis study provides further evidence that baseline cellular and molecular characteristics of an individual's immune system influence vaccine responses, and highlights the utility of integrating information across many parallel molecular datasets