A comprehensive genetic map of cytokine responses in Lyme borreliosis

The incidence of Lyme borreliosis has risen, accompanied by persistent symptoms. The innate immune system and related cytokines are crucial in the host response and symptom development. We characterized cytokine production capacity before and after antibiotic treatment in 1,060 Lyme borreliosis patients. We observed a negative correlation between antibody production and IL-10 responses, as well as increased IL-1Ra responses in patients with disseminated disease. Genome-wide mapping the cytokine production allowed us to identify 34 cytokine quantitative trait loci (cQTLs), with 31 novel ones. We pinpointed the causal variant at the TLR1-6-10 locus and validated the regulation of IL-1Ra responses at transcritpome level using an independent cohort. We found that cQTLs contribute to Lyme borreliosis susceptibility and are relevant to other immune-mediated diseases. Our findings improve the understanding of cytokine responses in Lyme borreliosis and provide a genetic map of immune function as an expanded resource.

A single-cell view on host immune transcriptional response to in vivo BCG-induced trained immunity

Bacillus Calmette-Guérin (BCG) vaccination is a prototype model for the study of trained immunity (TI) in humans, and results in a more effective response of innate immune cells upon stimulation with heterologous stimuli. Here, we investigate the heterogeneity of TI induction by single-cell RNA sequencing of immune cells collected from 156 samples. We observe that both monocytes and CD8⁺ T cells show heterologous transcriptional responses to lipopolysaccharide, with an active crosstalk between these two cell types. Furthermore, the interferon-γ pathway is crucial in BCG-induced TI, and it is upregulated in functional high responders. Data-driven analyses and functional experiments reveal STAT1 to be one of the important transcription factors for TI shared in all identified monocyte subpopulations. Finally, we report the role of type I interferon-related and neutrophil-related TI transcriptional programs in patients with sepsis. These findings provide comprehensive insights into the importance of monocyte heterogeneity during TI in humans.

Elevated plasma level of the glycolysis byproduct methylglyoxal on admission is an independent biomarker of mortality in ICU COVID-19 patients

Biomarkers to identify ICU COVID-19 patients at high risk for mortality are urgently needed for therapeutic care and management. Here we found plasma levels of the glycolysis byproduct methylglyoxal (MG) were 4.4-fold higher in ICU patients upon admission that later died (n = 33), and 1.7-fold higher in ICU patients that survived (n = 32),compared to uninfected controls (n = 30). The increased MG in patients that died correlated inversely with the levels of the MG-degrading enzyme glyoxalase-1 (r² = - 0.50), and its co-factor glutathione (r² = - 0.63), and positively with monocytes (r² = 0.29). The inflammation markers, SSAO (r² = 0.52), TNF-α (r² = 0.41), IL-1β (r² = 0.25), CRP (r² = 0.26) also correlated positively with MG. Logistic regression analysis provides evidence of a significant relationship between the elevated MG upon admission into ICU and death (P < 0.0001), with 42% of the death variability explained. From these data we conclude that elevated plasma MG on admission is a novel independent biomarker that predicts mortality in ICU COVID-19 patients.

Data on fuzzy logic based-modelling and optimization of recovered lipid from microalgae

This article presents the data of recovered lipid from microalgae using fuzzy logic based-modelling and particle swarm optimization (PSO) algorithm. The details of fuzzy model and optimization process were discussed in our work entitled “Application of Fuzzy Modelling and Particle Swarm Optimization to Enhance Lipid Extraction from Microalgae” (Nassef et al., 2019) [1]. The presented data are divided into two main parts. The first part represents the percentage of recovered lipid using fuzzy logic model and ANOVA. However, the second part shows the variation of the cost function (recovered lipid) for the 100 runs of PSO algorithm during optimization process. These data sets can be used as references to analyze the data obtained by any other optimization technique. The data sets are provided in the supplementary materials in Tables 1–2.

Mechanical pretreatment of waste paper for biogas production

In the anaerobic digestion of lignocellulosic materials such as waste paper, the accessibility of microorganisms to the fermentable sugars is restricted by their complex structure. A mechanical pretreatment with a Hollander beater was assessed in order to reduce the biomass particle size and to increase the feedstock' specific surface area available to the microorganisms, and therefore improve the biogas yield. Pretreatment of paper waste for 60min improves the methane yield by 21%, from a value of 210ml/gVS corresponding to untreated paper waste to 254ml/gVS. 30min pretreatment have no significant effect on the methane yield. A response surface methodology was used to evaluate the effect of the beating time and feedstock/inoculum ratio on the methane yield. An optimum methane yield of 253ml/gVS was achieved at 55min of beating pretreatment and a F/I ratio of 0.3.