Estimates of protection levels against SARS-CoV-2 infection and severe COVID-19 in Germany before the 2022/2023 winter season: the IMMUNEBRIDGE project

PURPOSE

Despite the need to generate valid and reliable estimates of protection levels against SARS-CoV-2 infection and severe course of COVID-19 for the German population in summer 2022, there was a lack of systematically collected population-based data allowing for the assessment of the protection level in real time.

METHODS

In the IMMUNEBRIDGE project, we harmonised data and biosamples for nine population-/hospital-based studies (total number of participants n = 33,637) to provide estimates for protection levels against SARS-CoV-2 infection and severe COVID-19 between June and November 2022. Based on evidence synthesis, we formed a combined endpoint of protection levels based on the number of self-reported infections/vaccinations in combination with nucleocapsid/spike antibody responses ("confirmed exposures"). Four confirmed exposures represented the highest protection level, and no exposure represented the lowest.

RESULTS

Most participants were seropositive against the spike antigen; 37% of the participants ≥ 79 years had less than four confirmed exposures (highest level of protection) and 5% less than three. In the subgroup of participants with comorbidities, 46-56% had less than four confirmed exposures. We found major heterogeneity across federal states, with 4-28% of participants having less than three confirmed exposures.

CONCLUSION

Using serological analyses, literature synthesis and infection dynamics during the survey period, we observed moderate to high levels of protection against severe COVID-19, whereas the protection against SARS-CoV-2 infection was low across all age groups. We found relevant protection gaps in the oldest age group and amongst individuals with comorbidities, indicating a need for additional protective measures in these groups.

Aerosolized delivery of ESKAPE pathogens for murine pneumonia models

Murine pneumonia models for ESKAPE pathogens serve to evaluate novel antibacterials or to investigate immunological responses. The majority of published models uses intranasal or to a limited extent the intratracheal instillation to challenge animals. In this study, we propose the aerosol delivery of pathogens using a nebulizer. Aerosol delivery typically results in homogeneous distribution of the inoculum in the lungs because of lower particle size. This is of particular importance when compounds are assessed for their pharmacokinetic and pharmacodynamic (PK/PD) relationships as it allows to conduct several analysis with the same sample material. Moreover, aerosol delivery has the advantage that it mimics the 'natural route' of respiratory infection. In this short and concise study, we show that aerosol delivery of pathogens resulted in a sustained bacterial burden in the neutropenic lung infection model for five pathogens tested, whereas it gave a similar result in immunocompetent mice for three out of five pathogens. Moreover, a substantial bacterial burden in the lungs was already achieved 2 h post inhalation. Hence, this study constitutes a viable alternative for intranasal administration and a refinement of murine pneumonia models for PK/PD assessments of novel antibacterial compounds allowing to study multiple readouts with the same sample material.

Improved prediction of bacterial CRISPRi guide efficiency from depletion screens through mixed-effect machine learning and data integration

CRISPR interference (CRISPRi) is the leading technique to silence gene expression in bacteria; however, design rules remain poorly defined. We develop a best-in-class prediction algorithm for guide silencing efficiency by systematically investigating factors influencing guide depletion in genome-wide essentiality screens, with the surprising discovery that gene-specific features substantially impact prediction. We develop a mixed-effect random forest regression model that provides better estimates of guide efficiency. We further apply methods from explainable AI to extract interpretable design rules from the model. This study provides a blueprint for predictive models for CRISPR technologies where only indirect measurements of guide activity are available.

Machine learning and phylogenetic analysis allow for predicting antibiotic resistance in M. tuberculosis

BACKGROUND

Antimicrobial resistance (AMR) poses a significant global health threat, and an accurate prediction of bacterial resistance patterns is critical for effective treatment and control strategies. In recent years, machine learning (ML) approaches have emerged as powerful tools for analyzing large-scale bacterial AMR data. However, ML methods often ignore evolutionary relationships among bacterial strains, which can greatly impact performance of the ML methods, especially if resistance-associated features are attempted to be detected. Genome-wide association studies (GWAS) methods like linear mixed models accounts for the evolutionary relationships in bacteria, but they uncover only highly significant variants which have already been reported in literature.

RESULTS

In this work, we introduce a novel phylogeny-related parallelism score (PRPS), which measures whether a certain feature is correlated with the population structure of a set of samples. We demonstrate that PRPS can be used, in combination with SVM- and random forest-based models, to reduce the number of features in the analysis, while simultaneously increasing models' performance. We applied our pipeline to publicly available AMR data from PATRIC database for Mycobacterium tuberculosis against six common antibiotics.

CONCLUSIONS

Using our pipeline, we re-discovered known resistance-associated mutations as well as new candidate mutations which can be related to resistance and not previously reported in the literature. We demonstrated that taking into account phylogenetic relationships not only improves the model performance, but also yields more biologically relevant predicted most contributing resistance markers.

Engraftment of essential functions through multiple fecal microbiota transplants in chronic antibiotic-resistant pouchitis-a case study using metatranscriptomics

BACKGROUND

Ileal pouch-anal anastomosis (IPAA) is the standard of care after total proctocolectomy for ulcerative colitis (UC). Around 50% of patients will experience pouchitis, an idiopathic inflammatory condition. Antibiotics are the backbone of treatment of pouchitis; however, antibiotic-resistant pouchitis develops in 5-10% of those patients. It has been shown that fecal microbiota transplantation (FMT) is an effective treatment for UC, but results for FMT antibiotic-resistant pouchitis are inconsistent.

METHODS

To uncover which metabolic activities were transferred to the recipients during FMT and helped the remission, we performed a longitudinal case study of the gut metatranscriptomes from three patients and their donors. The patients were treated by two to three FMTs, and stool samples were analyzed for up to 140 days.

RESULTS

Reduced expression in pouchitis patients compared to healthy donors was observed for genes involved in biosynthesis of amino acids, cofactors, and B vitamins. An independent metatranscriptome dataset of UC patients showed a similar result. Other functions including biosynthesis of butyrate, metabolism of bile acids, and tryptophan were also much lower expressed in pouchitis. After FMT, these activities transiently increased, and the overall metatranscriptome profiles closely mirrored those of the respective donors with notable fluctuations during the subsequent weeks. The levels of the clinical marker fecal calprotectin were concordant with the metatranscriptome data. Faecalibacterium prausnitzii represented the most active species contributing to butyrate synthesis via the acetyl-CoA pathway. Remission occurred after the last FMT in all patients and was characterized by a microbiota activity profile distinct from donors in two of the patients.

CONCLUSIONS

Our study demonstrates the clear but short-lived activity engraftment of donor microbiota, particularly the butyrate biosynthesis after each FMT. The data suggest that FMT triggers shifts in the activity of patient microbiota towards health which need to be repeated to reach critical thresholds. As a case study, these insights warrant cautious interpretation, and validation in larger cohorts is necessary for generalized applications. In the long run, probiotics with high taxonomic diversity consisting of well characterized strains could replace FMT to avoid the costly screening of donors and the risk of transferring unwanted genetic material. Video Abstract.

Seropositivity of Borrelia burgdorferi s.l. in Germany-an analysis across four German National Cohort (NAKO) study sites

Lyme borreliosis (LB) is caused by the transmission of Borrelia burgdorferi s.l. from ticks to humans. Climate affects tick abundance, and climate change is projected to promote shifts in abundance in Europe, potentially increasing human exposure. We analyzed serum samples collected between the years 2014-2019 from German National Cohort (NAKO) participants at four study sites (Augsburg, Berlin, Hanover, Münster) for immunoglobulin G (IgG) and immunoglobulin M (IgM) antibodies using an enzyme-linked immunosorbent assay (ELISA) and line blot immunoassay as confirmatory test for positive and equivocal ELISA samples. We reported crude and weighted seropositivity proportions for local estimates. We used mixed model analysis to investigate associated factors, such as age, sex, migration background, or animal contacts. We determined the serostatus of 14,207 participants. The weighted seropositivity proportions were 3.4% (IgG) and 0.4% (IgM) in Augsburg, 4.1% (IgG) and 0.6% (IgM) in northern Berlin, 3.0% (IgG) and 0.9% (IgM) in Hanover, and 2.7% (IgG) and 0.6% (IgM) in Münster. We found higher odds for IgG seropositivity with advancing age (p < 0.001), among males compared to females (p < 0.001) and reduced odds among participants with migration background compared to those without (p = 0.001). We did not find evidence for an association between serostatus and depression, children within the household, or animal contact, respectively. We found low seropositivity proportions and indications of differences across the study locations, although between-group comparisons did not yield significant results. Comparisons to earlier research are subject to important limitations; however, our results indicate no major increases in seropositivity over time. Nevertheless, monitoring of seropositivity remains critical in light of potential climate-related Borrelia exposure.

Association of known SARS-CoV-2 serostatus and adherence to personal protection measures and the impact of personal protective measures on seropositivity in a population-based cross-sectional study (MuSPAD) in Germany

BACKGROUND

In 2020/2021 in Germany, several non-pharmacological interventions were introduced to lower the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We investigated to what extent knowledge of prior infection with SARS-CoV-2 or vaccination status influenced the use of personal protection measures (PPM). Further, we were interested in the effect of compliance with PPM on SARS-CoV-2 serostatus.

METHODS

Data was based on a sequential, multilocal seroprevalence study (MuSPAD), carried out in eight locations from July 2020 to August 2021. We estimated the association between a known SARS-CoV-2 serostatus (reported positive PCR test or vaccination) and self-reported PPM behavior (hand hygiene, physical distancing, wearing face mask), just as the association of PPM compliance with seropositivity against nucleocapsid (NC), receptor-binding domain (RBD), and spike protein (S) antigens. We identified relevant variables and deduced adjustment sets with directed acyclic graphs (DAG), and applied mixed logistic regression.

RESULTS

Out of the 22,297 participants (median age: 54 years, 43% male), 781 were classified as SARS-CoV-2-infected and 3,877 had a vaccinated immune response. Vaccinated individuals were less likely to keep 1.5 m distance [OR = 0.74 (95% CI: 0.57-0.97)] and only partly physically distanced [OR = 0.71 (95% CI: 0.58-0.87)]. Participants with self-reported positive PCR test had a lower chance of adhering partly to physical distancing [OR = 0.70 (95% CI: 0.50-0.99)] in comparison to the reference group. Higher odds of additionally wearing a face mask was observed in vaccinated [OR = 1.28 (95% CI: 1.08-1.51)] even if it was not obligatory. Overall, among unvaccinated participants, we found little evidence of lower odds of seropositivity given mask wearing [OR: 0.91 (95% CI: 0.71-1.16)], physical distancing [OR: 0.84 (95% CI: 0.59-1.20)] and no evidence for completely adhering to hand cleaning [OR: 0.97 (95% CI: 0.29-3.22)].

CONCLUSIONS

A known confirmed prior infection and vaccination may have the potential to influence adherence to PPM.

Elevated phospholipids and acylcarnitines C4 and C5 in cerebrospinal fluid distinguish viral CNS infections from autoimmune neuroinflammation

BACKGROUND

Viral and autoimmune encephalitis may present with similar symptoms, but require different treatments. Thus, there is a need for biomarkers to improve diagnosis and understanding of pathogenesis. We hypothesized that virus-host cell interactions lead to different changes in central nervous system (CNS) metabolism than autoimmune processes and searched for metabolite biomarkers in cerebrospinal fluid (CSF) to distinguish between the two conditions.

METHODS

We applied a targeted metabolomic/lipidomic analysis to CSF samples from patients with viral CNS infections (n = 34; due to herpes simplex virus [n = 9], varicella zoster virus [n = 15], enteroviruses [n = 10]), autoimmune neuroinflammation (n = 25; autoimmune anti-NMDA-receptor encephalitis [n = 8], multiple sclerosis [n = 17), and non-inflamed controls (n = 31; Gilles de la Tourette syndrome [n = 20], Bell's palsy with normal CSF cell count [n = 11]). 85 metabolites passed quality screening and were evaluated as biomarkers. Standard diagnostic CSF parameters were assessed for comparison.

RESULTS

Of the standard CSF parameters, the best biomarkers were: CSF cell count for viral infections vs. controls (area under the ROC curve, AUC = 0.93), Q-albumin for viral infections vs. autoimmune neuroinflammation (AUC = 0.86), and IgG index for autoimmune neuroinflammation vs. controls (AUC = 0.90). Concentrations of 2 metabolites differed significantly (p < 0.05) between autoimmune neuroinflammation and controls, with proline being the best biomarker (AUC = 0.77). In contrast, concentrations of 67 metabolites were significantly higher in viral infections than controls, with SM.C16.0 being the best biomarker (AUC = 0.94). Concentrations of 68 metabolites were significantly higher in viral infections than in autoimmune neuroinflammation, and the 10 most accurate metabolite biomarkers (AUC = 0.89-0.93) were substantially better than Q-albumin (AUC = 0.86). These biomarkers comprised six phosphatidylcholines (AUC = 0.89-0.92), two sphingomyelins (AUC = 0.89, 0.91), and acylcarnitines isobutyrylcarnitine (C4, AUC = 0.92) and isovalerylcarnitine (C5, AUC = 0.93). Elevated C4 and C5 concentrations suggested dysfunctional mitochondrial β-oxidation and correlated only moderately with CSF cell count (Spearman ρ = 0.41 and 0.44), indicating that their increase is not primarily driven by inflammation.

CONCLUSIONS

Changes in CNS metabolism differ substantially between viral CNS infections and autoimmune neuroinflammation and reveal CSF metabolites as pathophysiologically relevant diagnostic biomarkers for the differentiation between the two conditions. In viral CNS infections, the observed higher concentrations of free phospholipids are consistent with disruption of host cell membranes, whereas the elevated short-chain acylcarnitines likely reflect compromised mitochondrial homeostasis and energy generation.

Myeloid-derived suppressor cells impair CD4+ T cell responses during chronic Staphylococcus aureus infection via lactate metabolism

Staphylococcus aureus is an important cause of chronic infections resulting from the failure of the host to eliminate the pathogen. Effective S. aureus clearance requires CD4+ T cell-mediated immunity. We previously showed that myeloid-derived suppressor cells (MDSC) expand during staphylococcal infections and support infection chronicity by inhibiting CD4+ T cell responses. The aim of this study was to elucidate the mechanisms underlying the suppressive effect exerted by MDSC on CD4+ T cells during chronic S. aureus infection. It is well known that activated CD4+ T cells undergo metabolic reprogramming from oxidative metabolism to aerobic glycolysis to meet their increased bioenergetic requirements. In this process, pyruvate is largely transformed into lactate by lactate dehydrogenase with the concomitant regeneration of NAD+, which is necessary for continued glycolysis. The by-product lactate needs to be excreted to maintain the glycolytic flux. Using SCENITH (single-cell energetic metabolism by profiling translation inhibition), we demonstrated here that MDSC inhibit CD4+ T cell responses by interfering with their metabolic activity. MDSC are highly glycolytic and excrete large amount of lactate in the local environment that alters the transmembrane concentration gradient and prevent removal of lactate by activated CD4+ T. Accumulation of endogenous lactate impedes the regeneration of NAD+, inhibit NAD-dependent glycolytic enzymes and stop glycolysis. Together, the results of this study have uncovered a role for metabolism on MDSC suppression of CD4+ T cell responses. Thus, reestablishment of their metabolic activity may represent a mean to improve the functionality of CD4+ T cells during chronic S. aureus infection.

Redisposition of apiosporous genera Induratia and Muscodor in the Xylariales, following the discovery of an authentic strain of Induratia apiospora

BACKGROUND

The genus Induratia is based on Induratia apiospora, a xylarialean pyrenomycete from New Zealand with clypeate uniperitheciate stromata, hyaline apiospores and a nodulisporium-like anamorph. However, because of the lack of DNA data from the generic type, its phylogenetic affinities have remained unresolved. Recently, two fungal species with teleomorphs strikingly similar to Induratia were discovered in Thailand. However, they did not produce an anamorph and were found to be phylogenetically close to the species classified within the hyphomycete genus Muscodor, which was described after Induratia. Therefore, in 2020 the species of Muscodor were transferred to Induratia, and a new family Induratiaceae was proposed.

RESULTS

We have encountered an unpublished ex-holotype strain of Induratia apiospora among the holdings of the ATCC collection, enabling detailed morphological and molecular phylogenetic investigations. We observed the characteristic nodulisporium-like anamorph described in the original publication. Phylogenetic analyses of multigene sequence data revealed a close relationship of Induratia apiospora to the Barrmaeliaceae, while a close relationship to the Induratia species formerly classified within Muscodor was rejected.

CONCLUSIONS

We here classify Induratia apiospora within the Barrmaeliaceae and consider Induratiaceae to be synonymous with the former. As the holotype specimen of Induratia apiospora is apparently lost, an isotype specimen from WSP is selected as lectotype. We also propose that the genus Muscodor is resurrected within the Xylariaceae, and formally transfer several Induratia species to Muscodor.

GlyLES: Grammar-based Parsing of Glycans from IUPAC-condensed to SMILES

Glycans are important polysaccharides on cellular surfaces that are bound to glycoproteins and glycolipids. These are one of the most common post-translational modifications of proteins in eukaryotic cells. They play important roles in protein folding, cell-cell interactions, and other extracellular processes. Changes in glycan structures may influence the course of different diseases, such as infections or cancer. Glycans are commonly represented using the IUPAC-condensed notation. IUPAC-condensed is a textual representation of glycans operating on the same topological level as the Symbol Nomenclature for Glycans (SNFG) that assigns colored, geometrical shapes to the main monomers. These symbols are then connected in tree-like structures, visualizing the glycan structure on a topological level. Yet for a representation on the atomic level, notations such as SMILES should be used. To our knowledge, there is no easy-to-use, general, open-source, and offline tool to convert the IUPAC-condensed notation to SMILES. Here, we present the open-access Python package GlyLES for the generalizable generation of SMILES representations out of IUPAC-condensed representations. GlyLES uses a grammar to read in the monomer tree from the IUPAC-condensed notation. From this tree, the tool can compute the atomic structures of each monomer based on their IUPAC-condensed descriptions. In the last step, it merges all monomers into the atomic structure of a glycan in the SMILES notation. GlyLES is the first package that allows conversion from the IUPAC-condensed notation of glycans to SMILES strings. This may have multiple applications, including straightforward visualization, substructure search, molecular modeling and docking, and a new featurization strategy for machine-learning algorithms. GlyLES is available at https://github.com/kalininalab/GlyLES.

Diminished neutralization responses towards SARS-CoV-2 Omicron VoC after mRNA or vector-based COVID-19 vaccinations

SARS-CoV-2 variants accumulating immune escape mutations provide a significant risk to vaccine-induced protection against infection. The novel variant of concern (VoC) Omicron BA.1 and its sub-lineages have the largest number of amino acid alterations in its Spike protein to date. Thus, they may efficiently escape recognition by neutralizing antibodies, allowing breakthrough infections in convalescent and vaccinated individuals in particular in those who have only received a primary immunization scheme. We analyzed neutralization activity of sera from individuals after vaccination with all mRNA-, vector- or heterologous immunization schemes currently available in Europe by in vitro neutralization assay at peak response towards SARS-CoV-2 B.1, Omicron sub-lineages BA.1, BA.2, BA.2.12.1, BA.3, BA.4/5, Beta and Delta pseudotypes and also provide longitudinal follow-up data from BNT162b2 vaccinees. All vaccines apart from Ad26.CoV2.S showed high levels of responder rates (96-100%) towards the SARS-CoV-2 B.1 isolate, and minor to moderate reductions in neutralizing Beta and Delta VoC pseudotypes. The novel Omicron variant and its sub-lineages had the biggest impact, both in terms of response rates and neutralization titers. Only mRNA-1273 showed a 100% response rate to Omicron BA.1 and induced the highest level of neutralizing antibody titers, followed by heterologous prime-boost approaches. Homologous BNT162b2 vaccination, vector-based AZD1222 and Ad26.CoV2.S performed less well with peak responder rates of 48%, 56% and 9%, respectively. However, Omicron responder rates in BNT162b2 recipients were maintained in our six month longitudinal follow-up indicating that individuals with cross-protection against Omicron maintain it over time. Overall, our data strongly argue for booster doses in individuals who were previously vaccinated with BNT162b2, or a vector-based primary immunization scheme.

Ten decadal advances in fungal biology leading towards human well-being

Fungi are an understudied resource possessing huge potential for developing products that can greatly improve human well-being. In the current paper, we highlight some important discoveries and developments in applied mycology and interdisciplinary Life Science research. These examples concern recently introduced drugs for the treatment of infections and neurological diseases; application of -OMICS techniques and genetic tools in medical mycology and the regulation of mycotoxin production; as well as some highlights of mushroom cultivaton in Asia. Examples for new diagnostic tools in medical mycology and the exploitation of new candidates for therapeutic drugs, are also given. In addition, two entries illustrating the latest developments in the use of fungi for biodegradation and fungal biomaterial production are provided. Some other areas where there have been and/or will be significant developments are also included. It is our hope that this paper will help realise the importance of fungi as a potential industrial resource and see the next two decades bring forward many new fungal and fungus-derived products.

Photobacterium arenosum WH24, Isolated from the Gill of Pacific Oyster Crassostrea gigas from the North Sea of Germany: Co-cultivation and Prediction of Virulence

Cream colored bacteria from marine agar, strain WH24, WH77, and WH80 were isolated from the gill of the Crassostrea gigas a Pacific oyster with a filter-feeding habit that compels accompanying bacteria to demonstrate a high metabolic capacity, has proven able to colonize locations with changing circumstances. Based on the 16S rRNA gene sequence, all strains had high similarity to Photobacterium arenosum CAU 1568^T (99.72%). This study involved phenotypic traits, phylogenetic analysis, antimicrobial activity evaluation, genome mining, Co-cultivation experiments, and chemical studies of crude extracts using HPLC and LC-HRESIMS. Photobacterium arenosum WH24 and Zooshikella harenae WH53^Twere co-cultivated for 3 days in a rotary shaker at 160 rpm at 30 °C, and LC-MS monitored the chemical profiles of the co-cultures on the third day. The UV chromatograms of the extracts of the co-cultivation experiments show that Zooshikella harenae WH53^T could be inhibited by strain WH24. The high virulence of Photobacterium arenosum WH24 was confirmed by genome analysis. Gene groups with high virulence potential were detected: tssA (ImpA), tssB (ImpB/vipA), tssC (ImpC/vipB), tssE, tssF (ImpG/vasA), tssG (ImpH/vasB), tssM (IcmF/vasK), tssJ (vasD), tssK (ImpJ/vasE), tssL (ImpK/vasF), clpV (tssH), vasH, hcp, lapP, plpD, and tpsB family.

Optimization of the production process for the anticancer lead compound illudin M: improving titers in shake-flasks

BACKGROUND

The fungal sesquiterpenes Illudin M and S are important base molecules for the development of new anticancer agents due to their strong activity against some resistant tumor cell lines. Due to nonspecific toxicity of the natural compounds, improvement of the pharmacophore is required. A semisynthetic derivative of illudin S (Irofulven) entered phase II clinical trials for the treatment of castration-resistant metastatic prostate cancer. Several semisynthetic illudin M derivatives showed increased in vitro selectivity and improved therapeutic index against certain tumor cell lines, encouraging further investigation. This requires a sustainable supply of the natural compound, which is produced by Basidiomycota of the genus Omphalotus. We aimed to develop a robust biotechnological process to deliver illudin M in quantities sufficient to support medicinal chemistry studies and future preclinical and clinical development. In this study, we report the initial steps towards this goal.

RESULTS

After establishing analytical workflows, different culture media and commercially available Omphalotus strains were screened for the production of illudin M.Omphalotus nidiformis cultivated in a medium containing corn steep solids reached ~ 38 mg L-1 setting the starting point for optimization. Improved seed preparation in combination with a simplified medium (glucose 13.5 g L-1; corn steep solids 7.0 g L- 1; Dox broth modified 35 mL), reduced cultivation time and enhanced titers significantly (~ 400 mg L-1). Based on a reproducible cultivation method, a feeding strategy was developed considering potential biosynthetic bottlenecks. Acetate and glucose were fed at 96 h (8.0 g L-1) and 120 h (6.0 g L-1) respectively, which resulted in final illudin M titer of ~ 940 mg L-1 after eight days. This is a 25 fold increase compared to the initial titer.

CONCLUSION

After strict standardization of seed-preparation and cultivation parameters, a combination of experimental design, empirical trials and additional supply of limiting biosynthetic precursors, led to a highly reproducible process in shake flasks with high titers of illudin M. These findings are the base for further work towards a scalable biotechnological process for a stable illudin M supply.

In vitro tools for orally inhaled drug products-state of the art for their application in pharmaceutical research and industry and regulatory challenges

The drug development process is a lengthy and expensive challenge for all involved players. Experience with the COVID-19 pandemic underlines the need for a rapid and effective approval for treatment options. As essential prerequisites for successful drug approval, a combination of high-quality studies and reliable research must be included. To this day, mainly in vivo data are requested and collected for assessing safety and efficacy and are therefore decisive for the pre-clinical evaluation of the respective drug. This review aims to summarize the current state of the art for safety and efficacy studies in pharmaceutical research and industry to address the relevant regulatory challenges and to provide an outlook on implementing more in vitro methods as alternative to animal testing. While the public demand for alternative methods is becoming louder, first examples have meanwhile found acceptance in relevant guidelines, e.g. the OECD guidelines for skin sensitizer. Besides ethically driven developments, also the rather low throughput and relatively high costs of animal experiments are forcing the industry towards the implementation of alternative methods. In this context, the development of orally inhaled drug products is particularly challenging due to the complexity of the lung as biological barrier and route of administration. The replacement of animal experiments with focus on the lungs requires special designed tools to achieve predictive data. New in vitro test systems of increasing complexity are presented in this review. Limits and advantages are discussed to provide some perspective for a future in vitro testing strategy for orally inhaled drug products.

Graphical abstract

Assessing excess mortality in times of pandemics based on principal component analysis of weekly mortality data-the case of COVID-19

The COVID-19 outbreak has called for renewed attention to the need for sound statistical analyses to monitor mortality patterns and trends over time. Excess mortality has been suggested as the most appropriate indicator to measure the overall burden of the pandemic in terms of mortality. As such, excess mortality has received considerable interest since the outbreak of COVID-19 began. Previous approaches to estimate excess mortality are somewhat limited, as they do not include sufficiently long-term trends, correlations among different demographic and geographic groups, or autocorrelations in the mortality time series. This might lead to biased estimates of excess mortality, as random mortality fluctuations may be misinterpreted as excess mortality. We propose a novel approach that overcomes the named limitations and draws a more realistic picture of excess mortality. Our approach is based on an established forecasting model that is used in demography, namely, the Lee-Carter model. We illustrate our approach by using the weekly age- and sex-specific mortality data for 19 countries and the current COVID-19 pandemic as a case study. Our findings show evidence of considerable excess mortality during 2020 in Europe, which affects different countries, age, and sex groups heterogeneously. Our proposed model can be applied to future pandemics as well as to monitor excess mortality from specific causes of death.

Haploflow: strain-resolved de novo assembly of viral genomes

With viral infections, multiple related viral strains are often present due to coinfection or within-host evolution. We describe Haploflow, a deBruijn graph-based assembler for de novo genome assembly of viral strains from mixed sequence samples using a novel flow algorithm. We assess Haploflow across multiple benchmark data sets of increasing complexity, showing that Haploflow is faster and more accurate than viral haplotype assemblers and generic metagenome assemblers not aiming to reconstruct strains. We show Haploflow reconstructs viral strain genomes from patient HCMV samples and SARS-CoV-2 wastewater samples identical to clinical isolates.

Integration of metabolomics, genomics, and immune phenotypes reveals the causal roles of metabolites in disease

BACKGROUND

Recent studies highlight the role of metabolites in immune diseases, but it remains unknown how much of this effect is driven by genetic and non-genetic host factors.

RESULT

We systematically investigate circulating metabolites in a cohort of 500 healthy subjects (500FG) in whom immune function and activity are deeply measured and whose genetics are profiled. Our data reveal that several major metabolic pathways, including the alanine/glutamate pathway and the arachidonic acid pathway, have a strong impact on cytokine production in response to ex vivo stimulation. We also examine the genetic regulation of metabolites associated with immune phenotypes through genome-wide association analysis and identify 29 significant loci, including eight novel independent loci. Of these, one locus (rs174584-FADS2) associated with arachidonic acid metabolism is causally associated with Crohn's disease, suggesting it is a potential therapeutic target.

CONCLUSION

This study provides a comprehensive map of the integration between the blood metabolome and immune phenotypes, reveals novel genetic factors that regulate blood metabolite concentrations, and proposes an integrative approach for identifying new disease treatment targets.

Effect modification of the association between comorbidities and severe course of COVID-19 disease by age of study participants: a systematic review and meta-analysis

BACKGROUND

Comprehensive evidence synthesis on the associations between comorbidities and behavioural factors with hospitalisation, intensive care unit (ICU) admission, and death due to COVID-19 is required for deriving national and international recommendations on primary targets for non-pharmacological interventions (NPI) and vaccination strategies.

METHODS

We performed a rapid systematic review and meta-analysis on studies and publicly accessible data to quantify associations between predisposing health conditions, demographics, behavioural factors on the one hand and hospitalisation, ICU admission, and death from COVID-19 on the other hand. We provide ranges of reported and calculated effect estimates and pooled relative risks derived from a meta-analysis and meta-regression.

RESULTS

Seventy-five studies were included in qualitative and 74 in quantitative synthesis, with study populations ranging from 19 to 44,672 COVID-19 cases. The risk of dying from COVID-19 was significantly associated with cerebrovascular [pooled relative risk (RR) 2.7 (95% CI 1.7-4.1)] and cardiovascular [RR 3.2 (CI 2.3-4.5)] diseases, hypertension [RR 2.6 (CI 2.0-3.4)], and renal disease [RR 2.5 (CI 1.8-3.4)], with high heterogeneity in pooled estimates, partly but not solely explained by age of study participants. For some comorbidities, our meta-regression showed a decrease in effect on the severity of disease with a higher median age of the study population. Compared to death, associations between several comorbidities and hospitalisation and ICU admission were less pronounced.

CONCLUSIONS

We obtained robust estimates on the magnitude of risk for COVID-19 hospitalisation, ICU admission, and death associated with comorbidities, demographic, and behavioural risk factors and show that these estimates are modified by age of study participants. This interaction is an important finding to be kept in mind for current vaccination strategies and for the protection of individuals with high risk for a severe COVID-19 course.

Blood transcriptome analysis of patients with uncomplicated bacterial infection and sepsis

OBJECTIVES

Hospitalized patients who presented within the last 24 h with a bacterial infection were recruited. Participants were assigned into sepsis and uncomplicated infection groups. In addition, healthy volunteers were recruited as controls. RNA was prepared from whole blood, depleted from beta-globin mRNA and sequenced. This dataset represents a highly valuable resource to better understand the biology of sepsis and to identify biomarkers for severe sepsis in humans.

DATA DESCRIPTION

The data presented here consists of raw and processed transcriptome data obtained by next generation RNA sequencing from 105 peripheral blood samples from patients with uncomplicated infections, patients who developed sepsis, septic shock patients, and healthy controls. It is provided as raw sequenced reads and as normalized log2 transformed relative expression levels. This data will allow performing detailed analyses of gene expression changes between uncomplicated infections and sepsis patients, such as identification of differentially expressed genes, co-regulated modules as well as pathway activation studies.

Development of the reproduction number from coronavirus SARS-CoV-2 case data in Germany and implications for political measures

BACKGROUND

SARS-CoV-2 has induced a worldwide pandemic and subsequent non-pharmaceutical interventions (NPIs) to control the spread of the virus. As in many countries, the SARS-CoV-2 pandemic in Germany has led to a consecutive roll-out of different NPIs. As these NPIs have (largely unknown) adverse effects, targeting them precisely and monitoring their effectiveness are essential. We developed a compartmental infection dynamics model with specific features of SARS-CoV-2 that allows daily estimation of a time-varying reproduction number and published this information openly since the beginning of April 2020. Here, we present the transmission dynamics in Germany over time to understand the effect of NPIs and allow adaptive forecasts of the epidemic progression.

METHODS

We used a data-driven estimation of the evolution of the reproduction number for viral spreading in Germany as well as in all its federal states using our model. Using parameter estimates from literature and, alternatively, with parameters derived from a fit to the initial phase of COVID-19 spread in different regions of Italy, the model was optimized to fit data from the Robert Koch Institute.

RESULTS

The time-varying reproduction number (Rt) in Germany decreased to <1 in early April 2020, 2-3 weeks after the implementation of NPIs. Partial release of NPIs both nationally and on federal state level correlated with moderate increases in Rt until August 2020. Implications of state-specific Rt on other states and on national level are characterized. Retrospective evaluation of the model shows excellent agreement with the data and usage of inpatient facilities well within the healthcare limit. While short-term predictions may work for a few weeks, long-term projections are complicated by unpredictable structural changes.

CONCLUSIONS

The estimated fraction of immunized population by August 2020 warns of a renewed outbreak upon release of measures. A low detection rate prolongs the delay reaching a low case incidence number upon release, showing the importance of an effective testing-quarantine strategy. We show that real-time monitoring of transmission dynamics is important to evaluate the extent of the outbreak, short-term projections for the burden on the healthcare system, and their response to policy changes.