Panoramic snapshot of serum soluble mediator interplay in pregnant women with convalescent COVID-19: an exploratory study.

Introduction: SARS-CoV-2 infection during pregnancy can induce changes in the maternal immune response, with effects on pregnancy outcome and offspring. This is a cross-sectional observational study designed to characterize the immunological status of pregnant women with convalescent COVID-19 at distinct pregnancy trimesters. The study focused on providing a clear snapshot of the interplay among serum soluble mediators. Methods: A sample of 141 pregnant women from all prenatal periods (1st, 2nd and 3rd trimesters) comprised patients with convalescent SARS-CoV-2 infection at 3-20 weeks after symptoms onset (COVID, n=89) and a control group of pre-pandemic non-infected pregnant women (HC, n=52). Chemokine, pro-inflammatory/regulatory cytokine and growth factor levels were quantified by a high-throughput microbeads array. Results: In the HC group, most serum soluble mediators progressively decreased towards the 2nd and 3rd trimesters of pregnancy, while higher chemokine, cytokine and growth factor levels were observed in the COVID patient group. Serum soluble mediator signatures and heatmap analysis pointed out that the major increase observed in the COVID group related to pro-inflammatory cytokines (IL-6, TNF-α, IL-12, IFN-γ and IL-17). A larger set of biomarkers displayed an increased COVID/HC ratio towards the 2nd (3x increase) and the 3rd (3x to 15x increase) trimesters. Integrative network analysis demonstrated that HC pregnancy evolves with decreasing connectivity between pairs of serum soluble mediators towards the 3rd trimester. Although the COVID group exhibited a similar profile, the number of connections was remarkably lower throughout the pregnancy. Meanwhile, IL-1Ra, IL-10 and GM-CSF presented a preserved number of correlations (≥5 strong correlations in HC and COVID), IL-17, FGF-basic and VEGF lost connectivity throughout the pregnancy. IL-6 and CXCL8 were included in a set of acquired attributes, named COVID-selective (≥5 strong correlations in COVID and <5 in HC) observed at the 3rd pregnancy trimester. Discussion and conclusion: From an overall perspective, a pronounced increase in serum levels of soluble mediators with decreased network interplay between them demonstrated an imbalanced immune response in convalescent COVID-19 infection during pregnancy that may contribute to the management of, or indeed recovery from, late complications in the post-symptomatic phase of the SARS-CoV-2 infection in pregnant women.

Unbalanced networks and disturbed kinetics of serum soluble mediators associated with distinct disease outcomes in severe COVID-19 patients.

The present study applied distinct models of descriptive analysis to explore the integrative networks and the kinetic timeline of serum soluble mediators to select a set of systemic biomarkers applicable for the clinical management of COVID-19 patients. For this purpose, a total of 246 participants (82 COVID-19 and 164 healthy controls - HC) were enrolled in a prospective observational study. Serum soluble mediators were quantified by high-throughput microbeads array on hospital admission (D0) and at consecutive timepoints (D1-6 and D7-20). The results reinforce that the COVID-19 group exhibited a massive storm of serum soluble mediators. While increased levels of CCL3 and G-CSF were associated with the favorable prognosis of non-mechanical ventilation (nMV) or discharge, high levels of CXCL10 and IL-6 were observed in patients progressing to mechanical ventilation (MV) or death. At the time of admission, COVID-19 patients presented a complex and robust serum soluble mediator network, with a higher number of strong correlations involving IFN-γ, IL-1Ra and IL-9 observed in patients progressing to MV or death. Multivariate regression analysis demonstrates the ability of serum soluble mediators to cluster COVID-19 from HC. Ascendant fold change signatures and the kinetic timeline analysis further confirmed that the pairs "CCL3 and G-CSF" and "CXCL10 and IL-6" were associated with favorable or poor prognosis, respectively. A selected set of systemic mediators (IL-6, IFN-γ, IL-1Ra, IL-13, PDGF and IL-7) were identified as putative laboratory markers, applicable as complementary records for the clinical management of patients with severe COVID-19.

Algorithm Design for a Cytokine Release Assay of Antigen-Specific In Vitro Stimuli of Circulating Leukocytes to Classify Leprosy Patients and Household Contacts.

BACKGROUND: Immunological biomarkers have often been used as a complementary approach to support clinical diagnosis in several infectious diseases. The lack of commercially available laboratory tests for conclusive early diagnosis of leprosy has motivated the search for novel methods for accurate diagnosis. In the present study, we describe an integrated analysis of a cytokine release assay using a machine learning approach to create a decision tree algorithm. This algorithm was used to classify leprosy clinical forms and monitor household contacts. METHODS: A model of Mycobacterium leprae antigen-specific in vitro assay with subsequent cytokine measurements by enzyme-linked immunosorbent assay was employed to measure the levels of tumor necrosis factor (TNF), interferon-γ, interleukin 4, and interleukin 10 (IL-10) in culture supernatants of peripheral blood mononuclear cells from patients with leprosy, healthy controls, and household contacts. Receiver operating characteristic curve analysis was carried out to define each cytokine's global accuracy and performance indices to identify clinical subgroups. RESULTS: Data demonstrated that TNF (control culture [CC]: AUC = 0.72; antigen-stimulated culture [Ml]: AUC = 0.80) and IL-10 (CC: AUC = 0.77; Ml: AUC = 0.71) were the most accurate biomarkers to classify subgroups of household contacts and patients with leprosy, respectively. Decision tree classifier algorithms for TNF analysis categorized subgroups of household contacts according to the operational classification with moderate accuracy (CC: 79% [48/61]; Ml: 84% [51/61]). Additionally, IL-10 analysis categorized leprosy patients' subgroups with moderate accuracy (CC: 73% [22/30] and Ml: 70% [21/30]). CONCLUSIONS: Together, our findings demonstrated that a cytokine release assay is a promising method to complement clinical diagnosis, ultimately contributing to effective control of the disease.

Deep sequencing of small RNAs reveals the repertoire of miRNAs and piRNAs in Biomphalaria glabrata

BACKGROUND Biomphalaria glabrata snails are widely distributed in schistosomiasis endemic areas like America and Caribe, displaying high susceptibility to infection by Schistosoma mansoni. After the availability of B. glabrata genome and transcriptome data, studies focusing on genetic markers and small non-coding RNAs have become more relevant. The small RNAs have been considered important through their ability to finely regulate the gene expression in several organisms, thus controlling the functions like cell growth, metabolism, and susceptibility/resistance to infection. OBJECTIVE The present study aims on identification and characterisation of the repertoire of small non-coding RNAs in B. glabrata (Bgl-small RNAs). METHODS By using small RNA sequencing, bioinformatics tools and quantitative reverse transcription polymerase chain reaction (RT-qPCR), we identified, characterised, and validated the presence of small RNAs in B. glabrata. FINDINGS 89 mature miRNAs were identified and five of them were classified as Mollusk-specific. When compared to model organisms, sequences of B. glabrata miRNAs showed a high degree of conservation. In addition, several target genes were predicted for all the mature miRNAs identified. Furthermore, piRNAs were identified in the genome of B. glabrata for the first time. The B. glabrata piRNAs showed strong conservation of uridine as first nucleotide at 5' end, besides adenine at 10th position. Our results showed that B. glabrata has diverse repertoire of circulating ncRNAs, several which might be involved in mollusk susceptibility to infection, due to their potential roles in the regulation of S. mansoni development. MAIN CONCLUSIONS Further studies are necessary in order to confirm the role of the Bgl-small RNAs in the parasite/host relationship thus opening new perspectives on interference of small RNAs in the organism development and susceptibility to infection.

Computational prediction and characterisation of miRNAs and their pathway genes in human schistosomiasis caused by Schistosoma haematobium

BACKGROUND Key genes control the infectivity of the Schistosoma haematobium causing schistosomiasis. A method for understanding the regulation of these genes might help in developing new disease strategies to control schistosomiasis, such as the silencing mediated by microRNAs (miRNAs). The miRNAs have been studied in schistosome species and they play important roles in the post-transcriptional regulation of genes, and in parasite-host interactions. However, genome-wide identification and characterisation of novel miRNAs and their pathway genes and their gene expression have not been explored deeply in the genome and transcriptome of S. haematobium. OBJECTIVES Identify and characterise mature and precursor miRNAs and their pathway genes in the S. haematobium genome. METHODS Computational prediction and characterisation of miRNAs and genes involved in miRNA pathway from S. haematobium genome on SchistoDB. Conserved domain analysis was performed using PFAM and CDD databases. A robust algorithm was applied to identify mature miRNAs and their precursors. The characterisation of the precursor miRNAs was performed using RNAfold, RNAalifold and Perl scripts. FINDINGS We identified and characterised 14 putative proteins involved in miRNA pathway including ARGONAUTE and DICER in S. haematobium. Besides that, 149 mature miRNAs and 131 precursor miRNAs were identified in the genome including novel miRNAs. MAIN CONCLUSIONS miRNA pathway occurs in the S. haematobium, including endogenous miRNAs and miRNA pathway components, suggesting a role of this type of non-coding RNAs in gene regulation in the parasite. The results found in this work will open up a new avenue for studying miRNAs in the S. haematobium biology in helping to understand the mechanism of gene silencing in the human parasite Schistosome.

Flow cytometric-based protocols for assessing anti-MT-2 IgG1 reactivity: High-dimensional data handling to define predictors for clinical follow-up of Human T-cell Leukemia virus type-1 infection.

The present work provides an innovative methodological approach to assess the anti-HTLV-1 IgG1 reactivity with practical application in clinical laboratory. Serum from non-infected healthy controls (NI) and HTLV-1-infected patients, categorized as asymptomatic (AS), putatively progressing to HTLV-1 associated myelopathy/tropical spastic paraparesis - HAM/TSP (pHAM) or with clinical diagnosis of HAM/TSP (HT) were assayed in two-parallel flow cytometry platforms, referred as: Fix and Fix&Perm protocols. Operating-characteristics analysis indicated that a single pair of attributes ("serum dilution/cut-off") for Fix and Fix&Perm protocols presented excellent performance for the diagnosis of HTLV-1 infection. Conversely, Fix and Fix&Perm protocols displayed weak/moderate overall performances when applied with prognosis purposes of HTLV-1 infection. A panoramic snapshot provided by the reactivity boards revealed clearly the higher sensitivity of Fix&Perm protocol for detecting seropositivity for HT, suggesting that stepwise combinatory criteria would improve the global performance of using a single pair of attributes. Three data mining strategies were tested, including endpoint titer analysis, heatmap assemblage and decision tree analysis. Bi-dimensional heatmap analysis demonstrated that, while the clustering profile of NI vs HTLV-1+ revealed segregation in opposite poles, AS vs HT presented discrete segregation but still displaying an intertwined distribution pattern. The combination of methods for segregating AS from HT displayed a moderate but superior global accuracy (85.7%; LOOCV=71.4%). The comprehensive data analysis support that the combination of methods have improved the performance to the differential diagnosis of AS and HT, with direct association with laboratorial records, including serum cytokine levels and proviral load.