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Latent class analysis is a widely used statistical method for evaluating diagnostic tests without any gold standard. It requires the results of at least two tests applied to the same individuals. Based on the resulting response patterns, the method estimates the test accuracy and the unknown disease status for all individuals in the sample. An important assumption is the conditional independence of the tests. If tests with the same biological principle are used, the assumption is not fulfilled, which may lead to biased results. In a recent publication, we developed a method that considers the dependencies in the latent class model and estimates all parameters using frequentist methods. Here, we evaluate the practicability of the method by applying it to the results of six ELISA tests for antibodies against the porcine reproductive and respiratory syndrome (PRRS) virus in pigs that generally follow the same biological principle. First, we present different methods of identifying suitable starting values for the algorithm and apply these to the dataset and a vaccinated subgroup. We present the calculated values of the test accuracies, the estimated proportion of antibody-positive animals and the dependency structure for both datasets. Different starting values led to matching results for the entire dataset. For the vaccinated subgroup, the results were more dependent on the selected starting values. All six ELISA tests are well suited to detect antibodies against PRRS virus, whereas none of the tests had the best values for sensitivity and specificity simultaneously. The results thus show that the method used is able to determine the parameter values of conditionally dependent tests with suitable starting values. The choice of test should be based on the general fit-for-purpose concept and the population under study.

Analysis of convalescent plasma derived from individuals has shown that IgG3 has the most important role in binding to SARS-CoV-2 antigens; however, this has not yet been confirmed in large studies, and the link between binding and neutralization has not been confirmed. By analyzing plasma pools consisting of 247–567 individual convalescent donors, we demonstrated the binding of IgG3 and IgM to Spike-1 protein and the receptor-binding domain correlates strongly with viral neutralization in vitro. Furthermore, despite accounting for only approximately 12% of total immunoglobulin mass, collectively IgG3 and IgM account for approximately 80% of the total neutralization. This may have important implications for the development of potent therapies for COVID-19, as it indicates that hyperimmune globulins or convalescent plasma donations with high IgG3 concentrations may be a highly efficacious therapy.

Advanced analytical methods play an important role in quantifying serum disease biomarkers. The problem of separating thousands of proteins can be reduced by analyzing for a ‘sub-proteome’, such as the ‘metalloproteome’, defined as all proteins that contain bound metals. We employed size exclusion chromatography (SEC) coupled to an inductively coupled plasma atomic emission spectrometer (ICP-AES) to analyze plasma from multiple sclerosis (MS) participants (n = 21), acute ischemic stroke (AIS) participants (n = 17) and healthy controls (n = 21) for Fe, Cu and Zn-metalloproteins. Using ANOVA analysis to compare the mean peak areas among the groups revealed no statistically significant differences for ceruloplasmin (p = 0.31), α2macroglobulin (p = 0.51) and transferrin (p = 0.31). However, a statistically significant difference was observed for the haptoglobin-hemoglobin (Hp-Hb) complex (p = 0.04), being driven by the difference between the control group and AIS (p = 0.012), but not with the MS group (p = 0.13), based on Dunnes test. A linear regression model for Hp-Hb complex with the groups now adjusted for age found no statistically significant differences between the groups (p = 0.95), but was suggestive for age (p = 0.057). To measure the strength of association between the Hp-Hb complex and age without possible modifications due to disease, we calculated the Spearman rank correlation in the healthy controls. The latter revealed a positive association (r = 0.39, 95% Confidence Interval = (-0.05, 0.83), which suggests that either the removal of Hp-Hb complexes from the blood circulation slows with age or that the release of Hb from red blood cells increases with age. We also observed that the Fe-peak corresponding to the Hp-Hb complex eluted ~100 s later in ~14% of all study samples, which was not correlated with age or disease diagnosis, but is consistent with the presence of the smaller Hp (1–1) isoform in 15% of the population.

Tumor progression locus 2 (Tpl2) is a serine/threonine kinase that regulates the expression of inflammatory mediators in response to Toll-like receptors (TLR) and cytokine receptors. Global ablation of Tpl2 leads to severe disease in response to influenza A virus (IAV) infection, characterized by respiratory distress, and studies in bone marrow chimeric mice implicated Tpl2 in non-hematopoietic cells. Lung epithelial cells are primary targets and replicative niches of influenza viruses; however, the specific regulation of antiviral responses by Tpl2 within lung epithelial cells has not been investigated. Herein, we show that Tpl2 is basally expressed in primary airway epithelial cells and that its expression increases in both type I and type II airway epithelial cells (AECI and AECII) in response to influenza infection. We used Nkx2.1-cre to drive Tpl2 deletion within pulmonary epithelial cells to delineate epithelial cell-specific functions of Tpl2 during influenza infection in mice. Although modest increases in morbidity and mortality were attributed to cre-dependent deletion in lung epithelial cells, no alterations in host cytokine production or lung pathology were observed. In vitro, Tpl2 inhibition within the type I airway epithelial cell line, LET1, as well as genetic ablation in primary airway epithelial cells did not alter cytokine production. Overall, these findings establish that Tpl2-dependent defects in cells other than AECs are primarily responsible for the morbidity and mortality seen in influenza-infected mice with global Tpl2 ablation.

Contact lens usage has contributed to increased incidence rates of Acanthamoeba keratitis (AK), a serious corneal infection that can lead to blindness. Since symptoms associated with AK closely resemble those incurred by bacterial or fungal keratitis, developing a diagnostic method enabling rapid detection with a high degree of Acanthamoeba-specificity would be beneficial. Here, we produced a polyclonal antibody targeting the carboxylesterase (CE) superfamily protein secreted by the pathogenic Acanthamoeba and evaluated its diagnostic potential. Western blot analysis revealed that the CE antibody specifically interacts with the cell lysates and conditioned media of pathogenic Acanthamoeba, which were not observed from the cell lysates and conditioned media of human corneal epithelial (HCE) cells, Fusarium solani, Staphylococcus aureus, and Pseudomonas aeruginosa. High titers of A. castellanii-specific antibody production were confirmed sera of immunized mice via ELISA, and these antibodies were capable of detecting A. castellanii from the cell lysates and their conditioned media. The specificity of the CE antibody was further confirmed on A. castellanii trophozoites and cysts co-cultured with HCE cells, F. solani, S. aureus, and P. aeruginosa using immunocytochemistry. Additionally, the CE antibody produced in this study successfully interacted with 7 different Acanthamoeba species. Our findings demonstrate that the polyclonal CE antibody specifically detects multiple species belong to the genus Acanthamoeba, thus highlighting its potential as AK diagnostic tool.

PurposeTo explore and compare urine proteome changes among rat models by intraperitoneal injection with single bacteria and co-injection with two bacteria.MethodEscherichia coliandStaphylococcus aureusare two common human pathogens. Three rat models were established: (i) the intraperitoneal co-injection ofE.coliandS.aureusmodel (ES model), (ii) intraperitoneal injection ofE.colimodel (E model), and (iii) intraperitoneal injection ofS.aureusmodel (S model). Urinary proteomes on days 0, 1 and 2 of the three models were analyzed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS).ResultsA total of 111, 34 and 94 differential proteins were identified in the ES model, E model and S model, respectively. Among them, some differential proteins were reported to be associated with bacterial infection. Approximately 47% differential proteins in the E model overlapped with ES model, and 37% differential proteins in the S model overlapped with ES model. Compared with the E model and S model, a total of 71 unique differential proteins were identified in the ES model.ConclusionOur results indicated that (1) the urine proteome could distinguish different bacterial intraperitoneal injections models and (2) the effects of co-injection with two bacteria on the urine proteome were not simple superposition of single injection.

The rapid, sensitive and specific detection of SARS-CoV-2 is critical in responding to the current COVID-19 outbreak. In this proof-of-concept study, we explored the potential of targeted mass spectrometry based (MS) proteomics for the detection of SARS-CoV-2 proteins in both research samples and clinical specimens. First, we assessed the limit of detection for several SARS-CoV-2 proteins by parallel reaction monitoring (PRM) MS in infected Vero E6 cells. For tryptic peptides of Nucleocapsid protein, the limit of detection was in the mid-attomole range (9E-13 g). Next, this PRM methodology was applied to the detection of viral proteins in various COVID-19 patient clinical specimens, such as sputum and nasopharyngeal swabs. SARS-CoV-2 proteins were detected in these samples with high sensitivity in all specimens with PCR Ct values