A statistical approach for identifying single nucleotide variants that affect transcription factor binding.

Non-coding variants located within regulatory elements may alter gene expression by modifying transcription factor (TF) binding sites, thereby leading to functional consequences. Different TF models are being used to assess the effect of DNA sequence variants, such as single nucleotide variants (SNVs). Often existing methods are slow and do not assess statistical significance of results. We investigated the distribution of absolute maximal differential TF binding scores for general computational models that affect TF binding. We find that a modified Laplace distribution can adequately approximate the empirical distributions. A benchmark on in vitro and in vivo datasets showed that our approach improves upon an existing method in terms of performance and speed. Applications on eQTLs and on a genome-wide association study illustrate the usefulness of our statistics by highlighting cell type-specific regulators and target genes. An implementation of our approach is freely available on GitHub and as bioconda package.

Ribosomal mutations enable a switch between high fitness and high stress resistance in Listeria monocytogenes.

Multiple stress resistant variants of Listeria monocytogenes with mutations in rpsU encoding ribosomal protein RpsU have previously been isolated after a single exposure to acid stress. These variants, including L. monocytogenes LO28 variant V14 with a complete deletion of the rpsU gene, showed upregulation of the general stress sigma factor Sigma B-mediated stress resistance genes and had a lower maximum specific growth rate than the LO28 WT, signifying a trade-off between stress resistance and fitness. In the current work V14 has been subjected to an experimental evolution regime, selecting for higher fitness in two parallel evolving cultures. This resulted in two evolved variants with WT-like fitness: 14EV1 and 14EV2. Comparative analysis of growth performance, acid and heat stress resistance, in combination with proteomics and RNA-sequencing, indicated that in both lines reversion to WT-like fitness also resulted in WT-like stress sensitivity, due to lack of Sigma B-activated stress defense. Notably, genotyping of 14EV1 and 14EV2 provided evidence for unique point-mutations in the ribosomal rpsB gene causing amino acid substitutions at the same position in RpsB, resulting in RpsB22Arg-His and RpsB22Arg-Ser, respectively. Combined with data obtained with constructed RpsB22Arg-His and RpsB22Arg-Ser mutants in the V14 background, we provide evidence that loss of function of RpsU resulting in the multiple stress resistant and reduced fitness phenotype, can be reversed by single point mutations in rpsB leading to arginine substitutions in RpsB at position 22 into histidine or serine, resulting in a WT-like high fitness and low stress resistance phenotype. This demonstrates the impact of genetic changes in L. monocytogenes' ribosomes on fitness and stress resistance.

Improved integration of single-cell transcriptome data demonstrates common and unique signatures of heart failure in mice and humans.

BACKGROUND: Cardiovascular research heavily relies on mouse (Mus musculus) models to study disease mechanisms and to test novel biomarkers and medications. Yet, applying these results to patients remains a major challenge and often results in noneffective drugs. Therefore, it is an open challenge of translational science to develop models with high similarities and predictive value. This requires a comparison of disease models in mice with diseased tissue derived from humans. RESULTS: To compare the transcriptional signatures at single-cell resolution, we implemented an integration pipeline called OrthoIntegrate, which uniquely assigns orthologs and therewith merges single-cell RNA sequencing (scRNA-seq) RNA of different species. The pipeline has been designed to be as easy to use and is fully integrable in the standard Seurat workflow.We applied OrthoIntegrate on scRNA-seq from cardiac tissue of heart failure patients with reduced ejection fraction (HFrEF) and scRNA-seq from the mice after chronic infarction, which is a commonly used mouse model to mimic HFrEF. We discovered shared and distinct regulatory pathways between human HFrEF patients and the corresponding mouse model. Overall, 54% of genes were commonly regulated, including major changes in cardiomyocyte energy metabolism. However, several regulatory pathways (e.g., angiogenesis) were specifically regulated in humans. CONCLUSIONS: The demonstration of unique pathways occurring in humans indicates limitations on the comparability between mice models and human HFrEF and shows that results from the mice model should be validated carefully. OrthoIntegrate is publicly accessible (https://github.com/MarianoRuzJurado/OrthoIntegrate) and can be used to integrate other large datasets to provide a general comparison of models with patient data.

Pulsed electric field treatment for preservation of Chlorella suspensions and retention of gelling capacity.

Pulsed electric field (PEF) processing has emerged as an alternative to thermal pasteurization for the shelf-life extension of heat-sensitive liquids at industrial scale. It offers the advantage of minimal alteration in physicochemical characteristics and functional properties. In this study, a pilot-scale continuous PEF processing (Toutlet < 55 °C) was applied to microalgae Chlorella vulgaris (Cv) suspensions (pH = 6.5), which was proposed as a functional ingredient for plant-based foods. Cv suspensions were inoculated with three distinct food spoilage microorganisms (Pseudomonas guariconensis, Enterobacter soli and Lactococcus lactis), isolated from the Cv biomass. PEF treatments were applied with varying electric field strength Eel of 16 to 28 kV/cm, pulse repetition rate f of 100 to 140 Hz, with a pulse width τ of 20 µs and an inlet product temperature Tin of 30 °C. The aim was to evaluate the PEF-induced microbial reduction and monitor the microbial outgrowth during a 10-day cold storage period (10 °C). Maximum inactivation of 4.1, 3.7 and 3.6 logs was achieved (28 kV/cm and 120 Hz) for the investigated isolates, respectively. Under these conditions, the critical electric field strengths Ecrit, above which inactivation was observed, ranged from 22.6 to 24.6 kV/cm. Moreover, repeated PEF treatment resulted in similar inactivation efficiency, indicating its potential to enhance shelf-life further.

A single point mutation in the Listeria monocytogenes ribosomal gene rpsU enables SigB activation independently of the stressosome and the anti-sigma factor antagonist RsbV.

Microbial population heterogeneity leads to different stress responses and growth behavior of individual cells in a population. Previously, a point mutation in the rpsU gene (rpsUG50C) encoding ribosomal protein S21 was identified in a Listeria monocytogenes LO28 variant, which leads to increased multi-stress resistance and a reduced maximum specific growth rate. However, the underlying mechanisms of these phenotypic changes remain unknown. In L. monocytogenes, the alternative sigma factor SigB regulates the general stress response, with its activation controlled by a series of Rsb proteins, including RsbR1 and anti-sigma factor RsbW and its antagonist RsbV. We combined a phenotype and proteomics approach to investigate the acid and heat stress resistance, growth rate, and SigB activation of L. monocytogenes EGDe wild type and the ΔsigB, ΔrsbV, and ΔrsbR1 mutant strains. While the introduction of rpsUG50C in the ΔsigB mutant did not induce a SigB-mediated increase in robustness, the presence of rpsUG50C in the ΔrsbV and the ΔrsbR1 mutants led to SigB activation and concomitant increased robustness, indicating an alternative signaling pathway for the SigB activation in rpsUG50C mutants. Interestingly, all these rpsUG50C mutants exhibited reduced maximum specific growth rates, independent of SigB activation, possibly attributed to compromised ribosomal functioning. In summary, the increased stress resistance in the L. monocytogenes EGDe rpsUG50C mutant results from SigB activation through an unknown mechanism distinct from the classical stressosome and RsbV/RsbW partner switching model. Moreover, the reduced maximum specific growth rate of the EGDe rpsUG50C mutant is likely unrelated to SigB activation and potentially linked to impaired ribosomal function.

Stress resistant rpsU variants of Listeria monocytogenes can become underrepresented due to enrichment bias.

Population heterogeneity is an important component of the survival mechanism of Listeria monocytogenes, leading to cells in a population with diverse stress resistance levels. We previously demonstrated that several ribosomal gene rpsU mutations enhanced the stress resistance of L. monocytogenes and lowered the growth rate at 30 °C and lower temperatures. This study investigated whether these switches in phenotypes could result in a bias in strain detection when standard enrichment-based procedures are applied to a variety of strains. Detailed growth kinetics analysis of L. monocytogenes strains were performed, including the LO28 wild type (WT) and rpsU variants V14 and V15, during two commonly used enrichment-based procedures described in the ISO 11290-1:2017 and the U.S. Food and Drug Administration Bacteriological Analytical Manual (BAM). WT had a higher growth rate than the variants during the enrichment processes. Co-culture growth kinetics predictions for WT and rpsU variants showed that the detection chances of the rpsU mutants were reduced from ∼52 % to less than ∼13 % and âˆ¼ 3 % during ISO and BAM enrichment, respectively, which were further validated through subsequent qPCR experiments. Higher heat stress resistance of rpsU variants did not lead to faster recovery during enrichment after heat treatment, and different pre-culturing temperatures before heat treatment did not significantly affect the growth kinetics of the WT and rpsU variants. Additionally, post-enrichment isolation procedures involving streaking on selective agar plates did not show preferences for isolating WT or rpsU variants nor affect the detection chance of rpsU variants. The difference in detection chance suggests that the selective enrichment procedures inadequately represent the genotypic diversity present in a sample. Hence, the enrichment bias during the L. monocytogenes isolation procedure may contribute to the observed underrepresentation of the rpsU mutation among L. monocytogenes isolates deposited in publicly available genome databases. The underrepresentation of rpsU mutants in our findings suggests that biases introduced by standard isolation and enrichment procedures could inadvertently skew our understanding of genetic diversity when relying on public databases.

Quantitative assessment of food safety interventions for Campylobacter spp. and Salmonella spp. along the chicken meat supply chain in Burkina Faso and Ethiopia.

Rural and small-scale chicken farming is a major source of income in most African countries, and chicken meat is an important source of nutrients. However, chicken meat can be contaminated with Campylobacter spp. and Salmonella spp., pathogens with a high reported burden of foodborne illnesses. Therefore, it is essential to control these pathogens in chicken meat. Quantitative microbial risk assessments (QMRA) can aid the development of effective food safety control measures and are currently lacking in chicken meat supply chains in the African context. In this study, we developed stochastic QMRA models for Salmonella spp. and Campylobacter spp. in the chicken meat supply chain in Burkina Faso and Ethiopia employing the modular process risk model in @Risk software. The study scope covered chicken farming, transport, slaughtering, consumer handling, and consumption. Effectiveness of candidate interventions was assessed against baseline models' outputs, which showed that the mean annual Campylobacter spp. risk estimates were 6482 cases of illness per 100,000 persons and 164 disability adjusted life years (DALYs) per 100,000 persons in Burkina Faso, and 12,145 cases and 272 DALYs per 100,000 persons in Ethiopia. For Salmonella spp., mean annual estimates were 2713 cases and 1212 DALYs per 100,000 persons in Burkina Faso, and 4745 cases and 432 DALYs per 100,000 persons in Ethiopia. Combining interventions (improved hand washing plus designated kitchen utensils plus improved cooking) resulted in 75 % risk reduction in Burkina Faso at restaurants and 93 to 94 % in Ethiopia at homes for both Salmonella spp. and Campylobacter spp. For Burkina Faso, adding good hygienic slaughter practices at the market to these combined interventions led to over 91 % microbial risk reduction. Interventions that involved multiple food safety actions in a particular step of the supply chain or combining different interventions from different steps of the supply chain resulted in more risk reduction than individual action interventions. Overall, this study demonstrates how diverse and scanty food supply chain information can be applied in QMRA to provide estimates that can be used to stimulate risk-based food safety action in African countries.

Beyond CSF and Neuroimaging Assessment: Evaluating Plasma miR-145-5p as a Potential Biomarker for Mild Cognitive Impairment and Alzheimer's Disease.

Alzheimer's disease (AD) is the most common cause of dementia. New strategies for the early detection of MCI and sporadic AD are crucial for developing effective treatment options. Current techniques used for diagnosis of AD are invasive and/or expensive, so they are not suitable for population screening. Cerebrospinal fluid (CSF) biomarkers such as amyloid ß1-42 (Aß1-42), total tau (T-tau), and phosphorylated tau181 (P-tau181) levels are core biomarkers for early diagnosis of AD. Several studies have proposed the use of blood-circulating microRNAs (miRNAs) as potential novel early biomarkers for AD. We therefore applied a novel approach to identify blood-circulating miRNAs associated with CSF biomarkers and explored the potential of these miRNAs as biomarkers of AD. In total, 112 subjects consisting of 28 dementia due to AD cases, 63 MCI due to AD cases, and 21 cognitively healthy controls were included. We identified seven Aß1-42-associated plasma miRNAs, six P-tau181-associated plasma miRNAs, and nine Aß1-42-associated serum miRNAs. These miRNAs were involved in AD-relevant biological processes, such as PI3K/AKT signaling. Based on this signaling pathway, we constructed an miRNA-gene target network, wherein miR-145-5p has been identified as a hub. Furthermore, we showed that miR-145-5p performs best in the prediction of both AD and MCI. Moreover, miR-145-5p also improved the prediction performance of the mini-mental state examination (MMSE) score. The performance of this miRNA was validated using different datasets including an RT-qPCR dataset from plasma samples of 23 MCI cases and 30 age-matched controls. These findings indicate that blood-circulating miRNAs that are associated with CSF biomarkers levels and specifically plasma miR-145-5p alone or combined with the MMSE score can potentially be used as noninvasive biomarkers for AD or MCI screening in the general population, although studies in other AD cohorts are necessary for further validation.

A web-based microbiological hazard identification tool for infant foods.

An integrated approach to identify and assess Microbiological Hazards (MHs) and mitigate risks in infant food chains is crucial to ensure safe foods for infants and young children. A systematic procedure was developed to identify MHs in specific infant foods. This includes five major steps: 1) relevant hazard-food pairing, 2) process inactivation efficiency, 3) recontamination possibility after processing, 4) MHs growth opportunity, and 5) MHs-food association level. These steps were integrated into an online tool called the Microbiological Hazards IDentification (MiID) decision support system (DSS), targeting food companies, governmental agencies and academia users, and is accessible at https://foodmicrobiologywur.shinyapps.io/Microbial_hazards_ID/. The MiID DSS was validated in four case studies, focussing on infant formula, fruit puree, cereal-based meals, and fresh fruits, each representing distinct products and processing characteristics. The results obtained through the application of the MiID DSS, compared with identification by food safety experts, consistently identified the top MHs in these food products. This process affirms its effectiveness in systematic hazard identification. The introduction of the MiID DSS helps to structure the first steps in HACCP (hazard analysis) and in risk assessment (hazard identification) to follow a structured and well-documented procedure, balancing the risk of overlooking relevant MHs or including too many irrelevant MHs. It is a valuable addition to risk analysis/assessment in infant food chains and has the potential for future extension. This includes the incorporation of newly acquired data related to infant foods via a semi-publicly hosted platform, or it can be adapted for hazard identification in general food products using a similar framework.

Multiomics analysis identifies novel facilitators of human dopaminergic neuron differentiation.

Midbrain dopaminergic neurons (mDANs) control voluntary movement, cognition, and reward behavior under physiological conditions and are implicated in human diseases such as Parkinson's disease (PD). Many transcription factors (TFs) controlling human mDAN differentiation during development have been described, but much of the regulatory landscape remains undefined. Using a tyrosine hydroxylase (TH) human iPSC reporter line, we here generate time series transcriptomic and epigenomic profiles of purified mDANs during differentiation. Integrative analysis predicts novel regulators of mDAN differentiation and super-enhancers are used to identify key TFs. We find LBX1, NHLH1 and NR2F1/2 to promote mDAN differentiation and show that overexpression of either LBX1 or NHLH1 can also improve mDAN specification. A more detailed investigation of TF targets reveals that NHLH1 promotes the induction of neuronal miR-124, LBX1 regulates cholesterol biosynthesis, and NR2F1/2 controls neuronal activity.

BI-3231, an enzymatic inhibitor of HSD17B13, reduces lipotoxic effects induced by palmitic acid in murine and human hepatocytes.

17-ß-hydroxysteroid dehydrogenase 13 (HSD17B13), a lipid droplet-associated enzyme, is primarily expressed in the liver and plays an important role in lipid metabolism. Targeted inhibition of enzymatic function is a potential therapeutic strategy for treating steatotic liver disease (SLD). The present study is aimed at investigating the effects of the first selective HSD17B13 inhibitor, BI-3231, in a model of hepatocellular lipotoxicity using human cell lines and primary mouse hepatocytes in vitro. Lipotoxicity was induced with palmitic acid in HepG2 cells and freshly isolated mouse hepatocytes and the cells were coincubated with BI-3231 to assess the protective effects. Under lipotoxic stress, triglyceride (TG) accumulation was significantly decreased in the BI-3231-treated cells compared with that of the control untreated human and mouse hepatocytes. In addition, treatment with BI-3231 led to considerable improvement in hepatocyte proliferation, cell differentiation, and lipid homeostasis. Mechanistically, BI-3231 increased the mitochondrial respiratory function without affecting ß-oxidation. BI-3231 inhibited the lipotoxic effects of palmitic acid in hepatocytes, highlighting the potential of targeting HSD17B13 as a specific therapeutic approach in steatotic liver disease.NEW & NOTEWORTHY 17-ß-Hydroxysteroid dehydrogenase 13 (HSD17B13) is a lipid droplet protein primarily expressed in the liver hepatocytes. HSD17B13 is associated with the clinical outcome of chronic liver diseases and is therefore a target for the development of drugs. Here, we demonstrate the promising therapeutic effect of BI-3231 as a potent inhibitor of HSD17B13 based on its ability to inhibit triglyceride accumulation in lipid droplets (LDs), restore lipid metabolism and homeostasis, and increase mitochondrial activity in vitro.

Temperature status of domestic refrigerators and its effect on the risk of listeriosis from ready-to-eat (RTE) cooked meat products.

Inadequate domestic refrigeration is frequently cited as a factor that contributes to foodborne poisoning and infection, and consumer behaviour in this regard can vary largely. This study provides insight into the temperature profiles of domestic refrigerators in the Netherlands and the impact on the number of listeriosis cases related to ready-to-eat (RTE) cooked meat products. A survey was conducted among Dutch consumers (n = 1020) to assess their knowledge and behaviour related to refrigerators. Out of these participants, 534 measured their refrigerator's temperature, revealing an average temperature of 5.7 °C (standard deviation (SD) of 2.2 °C) with a maximum of 17 °C. Elderly people (65 years and older) had refrigerators with temperatures that were on average 0.6 °C higher than those of younger people (35 years or younger). The 24-hour temperature profiles of an additional set of actively surveyed refrigerators (n = 50) showed that the temperature measured on the upper shelf was significantly higher (mean 7.7 °C, SD 2.7 °C) than the temperature measured on the bottom shelf (5.7 °C, SD 2.1 °C). Quantitative Microbiological Risk Assessment (QMRA) predicted that the primary factors contributing to the risk of listeriosis were the initial concentration and the time and temperature during household storage. Scenario analysis revealed that storing opened RTE cooked meat products at home for either <7 days or at temperatures <7 °C resulted in a significant reduction of over 80 % in predicted illness cases. Among all illness cases, the elderly represented nearly 90 %. When assessing the impact of the disease in terms of Years of Life Lost (YLL), the contribution of the elderly was 59 %. Targeted communication, particularly directed towards the elderly, on the importance of storing RTE cooked meat products at the recommended temperature on the bottom or middle shelf as well as consuming within two to three days after opening, holds the potential to significantly reduce the number of cases.

Limitations of a biokinetic model to predict the seasonal variations of nitrous oxide emissions from a full-scale wastewater treatment plant.

A biokinetic model based on BioWin's Activated Sludge Digestion Model (ASDM) coupled with a nitrous oxide (N2O) model was setup and calibrated for a full-scale wastewater treatment plant (WWTP) Amsterdam West, in the Netherlands. The model was calibrated using one year of continuous data to predict the seasonal variations of N2O emissions in the gaseous phase. This, according to our best knowledge, is the most complete full-scale data set used to date for this purpose. The results obtained suggest that the currently available biokinetic model predicted the winter, summer, and autumn N2O emissions well but failed to satisfactorily simulate the spring peak. During the calibration process, it was found that the nitrifier denitrification pathway could explain the observed emissions during all seasons while a combination of the nitrifier denitrification and incomplete heterotrophic denitrification pathways seemed to be dominant during the emissions peak observed during the spring season. Specifically, kinetic parameters related to free nitrous acid (FNA) displayed significant sensitivity leading to increased N2O production. The obtained values of two kinetic parameters, i.e., the FNA half-saturation during ammonia oxidising bacteria (AOB) denitrification and the FNA inhibition concentration related to heterotrophic denitrification, suggested a strong influence of the FNA bulk concentration on the N2O emissions and the observed seasonal variations. Based on the suboptimal performance and limitations of the biokinetic model, further research is needed to better understand the biochemical processes behind the seasonal peak and the influence of FNA.

The challenges of research data management in cardiovascular science: a DGK and DZHK position paper-executive summary.

The sharing and documentation of cardiovascular research data are essential for efficient use and reuse of data, thereby aiding scientific transparency, accelerating the progress of cardiovascular research and healthcare, and contributing to the reproducibility of research results. However, challenges remain. This position paper, written on behalf of and approved by the German Cardiac Society and German Centre for Cardiovascular Research, summarizes our current understanding of the challenges in cardiovascular research data management (RDM). These challenges include lack of time, awareness, incentives, and funding for implementing effective RDM; lack of standardization in RDM processes; a need to better identify meaningful and actionable data among the increasing volume and complexity of data being acquired; and a lack of understanding of the legal aspects of data sharing. While several tools exist to increase the degree to which data are findable, accessible, interoperable, and reusable (FAIR), more work is needed to lower the threshold for effective RDM not just in cardiovascular research but in all biomedical research, with data sharing and reuse being factored in at every stage of the scientific process. A culture of open science with FAIR research data should be fostered through education and training of early-career and established research professionals. Ultimately, FAIR RDM requires permanent, long-term effort at all levels. If outcomes can be shown to be superior and to promote better (and better value) science, modern RDM will make a positive difference to cardiovascular science and practice. The full position paper is available in the supplementary materials.

Insight in lag phase of Listeria monocytogenes during enrichment through proteomic and transcriptomic responses.

The dynamics of the enrichment-based detection procedure of the foodborne pathogen Listeria monocytogenes from food still remains poorly understood. This enrichment is crucial in the reliable detection of this pathogen and more insight into the recovery mechanism during this step is important to advance our understanding of lag phase behaviour during enrichment. In this study we combined transcriptomic and proteomic analyses to better understand the physiological processes within the lag phase of L. monocytogenes during enrichment. Upon transfer of BHI-cultured stationary phase L. monocytogenes cells to half-Fraser enrichment broth (HFB), motility-associated genes and proteins were downregulated, while expression of metal uptake transporters, resuscitation-promoting factors that stimulate growth from dormancy, antibiotic efflux pumps and oxidative stress proteins were upregulated. Next to this, when cells with a heat stress history were cultured in enrichment broth, proteins necessary for recovery were upregulated with functions in DNA-damage repair, protein refolding, cell-wall repair, and zinc transport. Proteomic results pointed to possible factors that support shortening the lag duration, including the addition of 10 µM zinc and the addition of spent HFB containing presumed concentrations of resuscitation-promoting factors. However, these interventions did not lead to biologically relevant reduction of lag phase. Also, when cells were enriched in spent HFB, final cell concentrations were similar to enrichments in fresh HFB, indicating that the enrichment broth seems not to lack critical substrates. Concludingly, this study gives insight into the proteomic changes in the lag phase during enrichment and shows that supplementation of HFB is not the best strategy to optimize the current enrichment method.

Multimodal analysis methods in predictive biomedicine.

For medicine to fulfill its promise of personalized treatments based on a better understanding of disease biology, computational and statistical tools must exist to analyze the increasing amount of patient data that becomes available. A particular challenge is that several types of data are being measured to cope with the complexity of the underlying systems, enhance predictive modeling and enrich molecular understanding. Here we review a number of recent approaches that specialize in the analysis of multimodal data in the context of predictive biomedicine. We focus on methods that combine different OMIC measurements with image or genome variation data. Our overview shows the diversity of methods that address analysis challenges and reveals new avenues for novel developments.

Fusogenic Coiled-Coil Peptides Enhance Lipid Nanoparticle-Mediated mRNA Delivery upon Intramyocardial Administration.

Heart failure is a serious condition that results from the extensive loss of specialized cardiac muscle cells called cardiomyocytes (CMs), typically caused by myocardial infarction (MI). Messenger RNA (mRNA) therapeutics are emerging as a very promising gene medicine for regenerative cardiac therapy. To date, lipid nanoparticles (LNPs) represent the most clinically advanced mRNA delivery platform. Yet, their delivery efficiency has been limited by their endosomal entrapment after endocytosis. Previously, we demonstrated that a pair of complementary coiled-coil peptides (CPE4/CPK4) triggered efficient fusion between liposomes and cells, bypassing endosomal entrapment and resulting in efficient drug delivery. Here, we modified mRNA-LNPs with the fusogenic coiled-coil peptides and demonstrated efficient mRNA delivery to difficult-to-transfect induced pluripotent stem-cell-derived cardiomyocytes (iPSC-CMs). As proof of in vivo applicability of these fusogenic LNPs, local administration via intramyocardial injection led to significantly enhanced mRNA delivery and concomitant protein expression. This represents the successful application of the fusogenic coiled-coil peptides to improve mRNA-LNPs transfection in the heart and provides the potential for the advanced development of effective regenerative therapies for heart failure.

Strain diversity in Saccharomyces cerevisiae thiamine production capacity.

Vitamin B1 , also known as thiamine, is an important vitamin that, besides its role in human health, is converted to meat aromas upon exposure to high temperatures. Therefore, it is relevant for the production of vegan meat-like flavours. In this study, we investigated 48 Saccharomyces cerevisiae strains for their thiamine production capacity by measuring the intracellular and extracellular vitamins produced in the thiamine-free minimal medium after 72 h of growth. We found approximately an 8.2-fold difference in overall thiamine yield between the highest and lowest-producing strains. While the highest thiamine yield was 254.6 nmol/L, the highest thiamine-specific productivity was 160.9 nmol/g DW. To assess whether extracellular thiamine was due to leakage caused by cell damage, we monitored membrane permeabilization using propidium iodide (PI) staining and flow cytometry. We found a good correlation between the percentage of extracellular thiamine and PI-stained cells (Spearman's ρ = 0.85). Finally, we compared S. cerevisiae CEN.PK113-7D (wild type [WT]) to three strains evolved in a thiamine-free medium for their thiamine production capacity. On average, we saw an increase in the amount of thiamine produced. One of the evolved strains had a 49% increase in intracellular thiamine-specific productivity and a biomass increase of 20% compared with the WT. This led to a total increase in thiamine yield of 60% in this strain, reaching 208 nmol/L. This study demonstrated that it is possible to achieve thiamine overproduction in S. cerevisiae via strain selection and adaptive laboratory evolution.

Dataset of single nucleotide polymorphisms of immune-associated genes in patients with SARS-CoV-2 infection.

The SARS-CoV-2 pandemic has affected nations globally leading to illness, death, and economic downturn. Why disease severity, ranging from no symptoms to the requirement for extracorporeal membrane oxygenation, varies between patients is still incompletely understood. Consequently, we aimed at understanding the impact of genetic factors on disease severity in infection with SARS-CoV-2. Here, we provide data on demographics, ABO blood group, human leukocyte antigen (HLA) type, as well as next-generation sequencing data of genes in the natural killer cell receptor family, the renin-angiotensin-aldosterone and kallikrein-kinin systems and others in 159 patients with SARS-CoV-2 infection, stratified into seven categories of disease severity. We provide single-nucleotide polymorphism (SNP) data on the patients and a protein structural analysis as a case study on a SNP in the SIGLEC7 gene, which was significantly associated with the clinical score. Our data represent a resource for correlation analyses involving genetic factors and disease severity and may help predict outcomes in infections with future SARS-CoV-2 variants and aid vaccine adaptation.