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Background: The long-term sequelae after COVID-19 constitute a challenge to public health and increased knowledge is needed. We investigated the prevalence of self-reported persistent symptoms and reduced health-related quality of life (HRQoL) in relation to functional exercise capacity, 6 months after infection, and explored risk factors for COVID-19 sequalae.

Methods: This was a prospective, multicenter, cohort study including 434 patients. At 6 months, physical exercise capacity was assessed by a 1-minute sit-to-stand test (1MSTST) and persistent symptoms were reported and HRQoL was evaluated through the EuroQol 5-level 5-dimension (EQ-5D-5L) questionnaire. Patients with both persistent symptoms and reduced HRQoL were classified into a new definition of post-acute COVID syndrome, PACS+. Risk factors for developing persistent symptoms, reduced HRQoL and PACS+ were identified by multivariable Poisson regression.

Results: Persistent symptoms were experienced by 79% of hospitalized, and 59% of non-hospitalized patients at 6 months. Hospitalized patients had a higher prevalence of self-assessed reduced overall health (28 vs. 12%) and PACS+ (31 vs. 11%). PACS+ was associated with reduced exercise capacity but not with abnormal pulse/desaturation during 1MSTST. Hospitalization was the most important independent risk factor for developing persistent symptoms, reduced overall health and PACS+.

Conclusion: Persistent symptoms and reduced HRQoL are common among COVID-19 survivors, but abnormal pulse and peripheral saturation during exercise could not distinguish patients with PACS+. Patients with severe infection requiring hospitalization were more likely to develop PACS+, hence these patients should be prioritized for clinical follow-up after COVID-19.

Phospholipids, major constituents of bilayer cell membranes, are present in large amounts in pulmonary surfactant and play key roles in cell signaling. Here, we aim at finding clinically useful disease markers in community-acquired pneumonia (CAP) using comprehensive phospholipid profiling in blood and modeling of changes between sampling time points. Serum samples from 33 patients hospitalized with CAP were collected at admission, three hours after the start of intravenous antibiotics, Day 1 (at 12–24 h), Day 2 (at 36–48 h), and several weeks after recovery. A profile of 75 phospholipid species including quantification of the bioactive lysophosphatidylcholines (LPCs) was determined using liquid chromatography coupled to time-of-flight mass spectrometry. To control for possible enzymatic degradation of LPCs, serum autotaxin levels were examined. Twenty-two of the 33 patients with a clinical diagnosis of CAP received a laboratory-verified CAP diagnosis by microbial culture or microbial DNA detection by qPCR. All major phospholipid species, especially the LPCs, were pronouncedly decreased in the acute stage of illness. Total and individual LPC concentrations increased shortly after the initiation of antibiotic treatment, concentrations were at their lowest 3h after the initiation, and increased after Day 1. The total LPC concentration increased by a change ratio of 1.6–1.7 between acute illness and Day 2, and by a ratio of 3.7 between acute illness and full disease resolution. Autotaxin levels were low in acute illness and showed little changes over time, contradicting a hypothesis of enzymatic degradation causing the low levels of LPCs. In this sample of patients with CAP, the results demonstrate that LPC concentration changes in serum of patients with CAP closely mirrored the early transition from acute illness to recovery after the initiation of antibiotics. LPCs should be further explored as potential disease stage biomarkers in CAP and for their potential physiological role during recovery.

A metabolomics approach for prediction of bacteremic sepsis in patients in the emergency room (ER) was investigated. In a prospective study, whole blood samples from 65 patients with bacteremic sepsis and 49 ER controls were compared. The blood samples were analyzed using gas chromatography coupled to time-of-flight mass spectrometry. Multivariate and logistic regression modeling using metabolites identified by chromatography or using conventional laboratory parameters and clinical scores of infection were employed. A predictive model of bacteremic sepsis with 107 metabolites was developed and validated. The number of metabolites was reduced stepwise until identifying a set of 6 predictive metabolites. A 6-metabolite predictive logistic regression model showed a sensitivity of 0.91(95% CI 0.69-0.99) and a specificity 0.84 (95% CI 0.58-0.94) with an AUC of 0.93 (95% CI 0.89-1.01). Myristic acid was the single most predictive metabolite, with a sensitivity of 1.00 (95% CI 0.85-1.00) and specificity of 0.95 (95% CI 0.74-0.99), and performed better than various combinations of conventional laboratory and clinical parameters. We found that a metabolomics approach for analysis of acute blood samples was useful for identification of patients with bacteremic sepsis. Metabolomics should be further evaluated as a new tool for infection diagnostics.

Analogues to the salicylanilide N-(4-Chlorophenyl)-2-acetoxy-3,5-diiodobenzamide, 1a, an inhibitor of type III secretion (T3S) in Yersinia, were selected, synthesized, and biologically evaluated in three cycles. First, a set of analogues with variations in the salicylic acid ring moiety was synthesized to probe possible structural variation. A basic structure-activity relationship was established and then used to cherry-pick compounds from a principal component analysis score plot of salicylanilides to generate a second set. A third set with increased likelihood of biological activity was designed using D-optimal onion design. A quantitative structure-activity relationship model using hierarchical partial least-square regression to latent structures (Hi-PLS) was computed using PLS score vectors of building blocks correlated to the % inhibition of T3S as a response. A PLS discriminant analysis (PLS-DA) model was derived using the same descriptor set as that for the Hi-PLS model. Both models were validated with an external test set.

Compound 1, 2-(benzo[1,2,5]thiadiazole-4-sulfonylamino)-5-chloro-N-(3,4-dichloro-phenyl)-benzamide, was identified as a putative type III secretion inhibitor in Yersinia, and the compound thus has a potential to be used to prevent or treat bacterial infections. A set of seven analogues was synthesized and evaluated in a type III secretion dependent reporter-gene assay with viable bacterial to give basic SAR. A second set of 19 compounds was obtained by statistical molecular design in the building block and product space and subsequent synthesis. Evaluation in the reporter-gene assay showed that the compounds ranged from non-active to compounds more potent than 1. Based on the data multivariate QSAR models were established and the final Hi-PLS model showed good correlation between experimentally determined % inhibition and the calculated % inhibition of the reporter-gene signal.

Despite the large arsenal of antibiotics available on the market, treatment of bacterial infections becomes more challenging in view of the fact that microbes develop resistance against existing drugs. There is an obvious need for novel drugs acting on both old and new targets in bacteria. In this thesis we have employed a whole cell bacterial assay for screening and identification of type III secretion system (T3SS) inhibitors in Yersinia pseudotuberculosis. The T3SS is a common virulence mechanism utilized by several clinically relevant Gram-negative bacteria including Salmonella, Shigella, Pseudomonas aeruginosa, Chlamydiae and Escherichia coli. Several components in the T3SS have proved to be conserved and hence data generated with Y. pseudotuberculosis as model might also be valid for other bacterial species.

We have screened a 9,400 commercial compound library for T3S inhibitors in Y. pseudotuberculosis using a yopE reporter gene assay. The initial ~ 30 hits were followed up in a growth inhibition assay resulting in 26 interesting compounds that were examined in more detail. Three of the most interesting compounds, salicylanilides, 2-hydroxybenzylidene-hydrazides and 2-arylsulfonamino-benzanilides, were selected for continued investigations. The inhibitor classes show different profiles regarding the effects on T3SS in Yersinia and their use as research tools and identification of the target proteins using a chemical biology approach will increase our understanding of bacterial virulence.

The 2-hydroxybenzylidene-hydrazides have been extensively studied in vitro and show potential as selective T3S inhibitors in several Gram-negative pathogens besides Y. pseudotuberculosis. The data obtained suggest that this inhibitor class targets a conserved protein in the secretion apparatus. In cell-based ex vivo infection models T3SS was inhibited to the advantage of the infected eukaryotic cells. The salicylanilides and 2-arylsulfonamino-benzanilides have been further investigated by statistical molecular design (SMD) followed by synthesis and biological evaluation in the T3SS linked reporter gene assay. Multivariate QSAR models were established despite the challenges with data obtained from assays using viable bacteria. Our results indicate that this SMD QSAR strategy is powerful in development of virulence inhibitors targeting the T3SS.