SpatialData: an open and universal data framework for spatial omics

Spatially resolved omics technologies are transforming our understanding of biological tissues. However, the handling of uni- and multimodal spatial omics datasets remains a challenge owing to large data volumes, heterogeneity of data types and the lack of flexible, spatially aware data structures. Here we introduce SpatialData, a framework that establishes a unified and extensible multiplatform file-format, lazy representation of larger-than-memory data, transformations and alignment to common coordinate systems. SpatialData facilitates spatial annotations and cross-modal aggregation and analysis, the utility of which is illustrated in the context of multiple vignettes, including integrative analysis on a multimodal Xenium and Visium breast cancer study.

Multimodal and spatially resolved profiling identifies distinct patterns of T cell infiltration in nodal B cell lymphoma entities

The redirection of T cells has emerged as an attractive therapeutic principle in B cell non-Hodgkin lymphoma (B-NHL). However, a detailed characterization of lymphoma-infiltrating T cells across B-NHL entities is missing. Here we present an in-depth T cell reference map of nodal B-NHL, based on cellular indexing of transcriptomes and epitopes, T cell receptor sequencing, flow cytometry and multiplexed immunofluorescence applied to 101 lymph nodes from patients with diffuse large B cell, mantle cell, follicular or marginal zone lymphoma, and from healthy controls. This multimodal resource revealed quantitative and spatial aberrations of the T cell microenvironment across and within B-NHL entities. Quantitative differences in PD1+ TCF7- cytotoxic T cells, T follicular helper cells or IKZF3+ regulatory T cells were linked to their clonal expansion. The abundance of PD1+ TCF7- cytotoxic T cells was associated with poor survival. Our study portrays lymphoma-infiltrating T cells with unprecedented comprehensiveness and provides a unique resource for the investigation of lymphoma biology and prognosis.

In situ analysis of osmolyte mechanisms of proteome thermal stabilization

Organisms use organic molecules called osmolytes to adapt to environmental conditions. In vitro studies indicate that osmolytes thermally stabilize proteins, but mechanisms are controversial, and systematic studies within the cellular milieu are lacking. We analyzed Escherichia coli and human protein thermal stabilization by osmolytes in situ and across the proteome. Using structural proteomics, we probed osmolyte effects on protein thermal stability, structure and aggregation, revealing common mechanisms but also osmolyte- and protein-specific effects. All tested osmolytes (trimethylamine N-oxide, betaine, glycerol, proline, trehalose and glucose) stabilized many proteins, predominantly via a preferential exclusion mechanism, and caused an upward shift in temperatures at which most proteins aggregated. Thermal profiling of the human proteome provided evidence for intrinsic disorder in situ but also identified potential structure in predicted disordered regions. Our analysis provides mechanistic insight into osmolyte function within a complex biological matrix and sheds light on the in situ prevalence of intrinsically disordered regions.

Improved discovery of RNA-binding protein binding sites in eCLIP data using DEWSeq

Enhanced crosslinking and immunoprecipitation (eCLIP) sequencing is a method for transcriptome-wide detection of binding sites of RNA-binding proteins (RBPs). However, identified crosslink sites can deviate from experimentally established functional elements of even well-studied RBPs. Current peak-calling strategies result in low replication and high false positive rates. Here, we present the R/Bioconductor package DEWSeq that makes use of replicate information and size-matched input controls. We benchmarked DEWSeq on 107 RBPs for which both eCLIP data and RNA sequence motifs are available and were able to more than double the number of motif-containing binding regions relative to standard eCLIP processing. The improvement not only relates to the number of binding sites (3.1-fold with known motifs for RBFOX2), but also their subcellular localization (1.9-fold of mitochondrial genes for FASTKD2) and structural targets (2.2-fold increase of stem-loop regions for SLBP. On several orthogonal CLIP-seq datasets, DEWSeq recovers a larger number of motif-containing binding sites (3.3-fold). DEWSeq is a well-documented R/Bioconductor package, scalable to adequate numbers of replicates, and tends to substantially increase the proportion and total number of RBP binding sites containing biologically relevant features.

Ex vivo drug response profiling for response and outcome prediction in hematologic malignancies: the prospective non-interventional SMARTrial

Ex vivo drug response profiling is a powerful tool to study genotype-drug response associations and is being explored as a tool set for precision medicine in cancer. Here we conducted a prospective non-interventional trial to investigate feasibility of ex vivo drug response profiling for treatment guidance in hematologic malignancies (SMARTrial, NCT03488641 ). The primary endpoint to provide drug response profiling reports within 7 d was met in 91% of all study participants (N = 80). Secondary endpoint analysis revealed that ex vivo resistance to chemotherapeutic drugs predicted chemotherapy treatment failure in vivo. We confirmed the predictive value of ex vivo response to chemotherapy in a validation cohort of 95 individuals with acute myeloid leukemia treated with daunorubicin and cytarabine. Ex vivo drug response profiles improved ELN-22 risk stratification in individuals with adverse risk. We conclude that ex vivo drug response profiling is clinically feasible and has the potential to predict chemotherapy response in individuals with hematologic malignancies beyond clinically established genetic markers.

The changing career paths of PhDs and postdocs trained at EMBL

Individuals with PhDs and postdoctoral experience in the life sciences can pursue a variety of career paths. Many PhD students and postdocs aspire to a permanent research position at a university or research institute, but competition for such positions has increased. Here, we report a time-resolved analysis of the career paths of 2284 researchers who completed a PhD or a postdoc at the European Molecular Biology Laboratory (EMBL) between 1997 and 2020. The most prevalent career outcome was Academia: Principal Investigator (636/2284=27.8% of alumni), followed by Academia: Other (16.8%), Science-related Non-research (15.3%), Industry Research (14.5%), Academia: Postdoc (10.7%) and Non-science-related (4%); we were unable to determine the career path of the remaining 10.9% of alumni. While positions in Academia (Principal Investigator, Postdoc and Other) remained the most common destination for more recent alumni, entry into Science-related Non-research, Industry Research and Non-science-related positions has increased over time, and entry into Academia: Principal Investigator positions has decreased. Our analysis also reveals information on a number of factors - including publication records - that correlate with the career paths followed by researchers.

Systematic analysis of drug combinations against Gram-positive bacteria

Drug combinations can expand options for antibacterial therapies but have not been systematically tested in Gram-positive species. We profiled ~8,000 combinations of 65 antibacterial drugs against the model species Bacillus subtilis and two prominent pathogens, Staphylococcus aureus and Streptococcus pneumoniae. Thereby, we recapitulated previously known drug interactions, but also identified ten times more novel interactions in the pathogen S. aureus, including 150 synergies. We showed that two synergies were equally effective against multidrug-resistant S. aureus clinical isolates in vitro and in vivo. Interactions were largely species-specific and synergies were distinct from those of Gram-negative species, owing to cell surface and drug uptake differences. We also tested 2,728 combinations of 44 commonly prescribed non-antibiotic drugs with 62 drugs with antibacterial activity against S. aureus and identified numerous antagonisms that might compromise the efficacy of antimicrobial therapies. We identified even more synergies and showed that the anti-aggregant ticagrelor synergized with cationic antibiotics by modifying the surface charge of S. aureus. All data can be browsed in an interactive interface ( https://apps.embl.de/combact/ ).

Comparing the value of mono- vs coculture for high-throughput compound screening in hematological malignancies

Large-scale compound screens are a powerful model system for understanding variability of treatment response and discovering druggable tumor vulnerabilities of hematological malignancies. However, as mostly performed in a monoculture of tumor cells, these assays disregard modulatory effects of the in vivo microenvironment. It is an open question whether and to what extent coculture with bone marrow stromal cells could improve the biological relevance of drug testing assays over monoculture. Here, we established a high-throughput platform to measure ex vivo sensitivity of 108 primary blood cancer samples to 50 drugs in monoculture and coculture with bone marrow stromal cells. Stromal coculture conferred resistance to 52% of compounds in chronic lymphocytic leukemia (CLL) and 36% of compounds in acute myeloid leukemia (AML), including chemotherapeutics, B-cell receptor inhibitors, proteasome inhibitors, and Bromodomain and extraterminal domain inhibitors. Only the JAK inhibitors ruxolitinib and tofacitinib exhibited increased efficacy in AML and CLL stromal coculture. We further confirmed the importance of JAK-STAT signaling for stroma-mediated resistance by showing that stromal cells induce phosphorylation of STAT3 in CLL cells. We genetically characterized the 108 cancer samples and found that drug-gene associations strongly correlated between monoculture and coculture. However, effect sizes were lower in coculture, with more drug-gene associations detected in monoculture than in coculture. Our results justify a 2-step strategy for drug perturbation testing, with large-scale screening performed in monoculture, followed by focused evaluation of potential stroma-mediated resistances in coculture.

MsQuality: an interoperable open-source package for the calculation of standardized quality metrics of mass spectrometry data

MOTIVATION

Multiple factors can impact accuracy and reproducibility of mass spectrometry data. There is a need to integrate quality assessment and control into data analytic workflows.

RESULTS

The MsQuality package calculates 43 low-level quality metrics based on the controlled mzQC vocabulary defined by the HUPO-PSI on a single mass spectrometry-based measurement of a sample. It helps to identify low-quality measurements and track data quality. Its use of community-standard quality metrics facilitates comparability of quality assessment and control (QA/QC) criteria across datasets.

AVAILABILITY AND IMPLEMENTATION

The R package MsQuality is available through Bioconductor at https://bioconductor.org/packages/MsQuality.

Subgroup-specific gene expression profiles and mixed epistasis in chronic lymphocytic leukemia

Understanding the molecular and phenotypic heterogeneity of cancer is a prerequisite for effective treatment. For chronic lymphocytic leukemia (CLL), recurrent genetic driver events have been extensively cataloged, but this does not suffice to explain the disease's diverse course. Here, we performed RNA sequencing on 184 CLL patient samples. Unsupervised analysis revealed two major, orthogonal axes of gene expression variation: the first one represented the mutational status of the immunoglobulin heavy variable (IGHV) genes, and concomitantly, the three-group stratification of CLL by global DNA methylation. The second axis aligned with trisomy 12 status and affected chemokine, MAPK and mTOR signaling. We discovered non-additive effects (epistasis) of IGHV mutation status and trisomy 12 on multiple phenotypes, including the expression of 893 genes. Multiple types of epistasis were observed, including synergy, buffering, suppression and inversion, suggesting that molecular understanding of disease heterogeneity requires studying such genetic events not only individually but in combination. We detected strong differentially expressed gene signatures associated with major gene mutations and copy number aberrations including SF3B1, BRAF and TP53, as well as del(17)(p13), del(13)(q14) and del(11)(q22.3) beyond dosage effect. Our study reveals previously underappreciated gene expression signatures for the major molecular subtypes in CLL and the presence of epistasis between them.

Comparison of transformations for single-cell RNA-seq data

The count table, a numeric matrix of genes × cells, is the basic input data structure in the analysis of single-cell RNA-sequencing data. A common preprocessing step is to adjust the counts for variable sampling efficiency and to transform them so that the variance is similar across the dynamic range. These steps are intended to make subsequent application of generic statistical methods more palatable. Here, we describe four transformation approaches based on the delta method, model residuals, inferred latent expression state and factor analysis. We compare their strengths and weaknesses and find that the latter three have appealing theoretical properties; however, in benchmarks using simulated and real-world data, it turns out that a rather simple approach, namely, the logarithm with a pseudo-count followed by principal-component analysis, performs as well or better than the more sophisticated alternatives. This result highlights limitations of current theoretical analysis as assessed by bottom-line performance benchmarks.

Deep thermal profiling for detection of functional proteoform groups

The complexity of the functional proteome extends considerably beyond the coding genome, resulting in millions of proteoforms. Investigation of proteoforms and their functional roles is important to understand cellular physiology and its deregulation in diseases but challenging to perform systematically. Here we applied thermal proteome profiling with deep peptide coverage to detect functional proteoform groups in acute lymphoblastic leukemia cell lines with different cytogenetic aberrations. We detected 15,846 proteoforms, capturing differently spliced, cleaved and post-translationally modified proteins expressed from 9,290 genes. We identified differential co-aggregation of proteoform pairs and established links to disease biology. Moreover, we systematically made use of measured biophysical proteoform states to find specific biomarkers of drug sensitivity. Our approach, thus, provides a powerful and unique tool for systematic detection and functional annotation of proteoform groups.

Pre-analytical processing of plasma and serum samples for combined proteome and metabolome analysis

Metabolomic and proteomic analyses of human plasma and serum samples harbor the power to advance our understanding of disease biology. Pre-analytical factors may contribute to variability and bias in the detection of analytes, especially when multiple labs are involved, caused by sample handling, processing time, and differing operating procedures. To better understand the impact of pre-analytical factors that are relevant to implementing a unified proteomic and metabolomic approach in a clinical setting, we assessed the influence of temperature, sitting times, and centrifugation speed on the plasma and serum metabolomes and proteomes from six healthy volunteers. We used targeted metabolic profiling (497 metabolites) and data-independent acquisition (DIA) proteomics (572 proteins) on the same samples generated with well-defined pre-analytical conditions to evaluate criteria for pre-analytical SOPs for plasma and serum samples. Time and temperature showed the strongest influence on the integrity of plasma and serum proteome and metabolome. While rapid handling and low temperatures (4°C) are imperative for metabolic profiling, the analyzed proteomics data set showed variability when exposed to temperatures of 4°C for more than 2 h, highlighting the need for compromises in a combined analysis. We formalized a quality control scoring system to objectively rate sample stability and tested this score using external data sets from other pre-analytical studies. Stringent and harmonized standard operating procedures (SOPs) are required for pre-analytical sample handling when combining proteomics and metabolomics of clinical samples to yield robust and interpretable data on a longitudinal scale and across different clinics. To ensure an adequate level of practicability in a clinical routine for metabolomics and proteomics studies, we suggest keeping blood samples up to 2 h on ice (4°C) prior to snap-freezing as a compromise between stability and operability. Finally, we provide the methodology as an open-source R package allowing the systematic scoring of proteomics and metabolomics data sets to assess the stability of plasma and serum samples.

Extravascular lung water levels are associated with mortality: a systematic review and meta-analysis

Background

The prognostic value of extravascular lung water (EVLW) measured by transpulmonary thermodilution (TPTD) in critically ill patients is debated. We performed a systematic review and meta-analysis of studies assessing the effects of TPTD-estimated EVLW on mortality in critically ill patients.

Methods

Cohort studies published in English from Embase, MEDLINE, and the Cochrane Database of Systematic Reviews from 1960 to 1 June 2021 were systematically searched. From eligible studies, the values of the odds ratio (OR) of EVLW as a risk factor for mortality, and the value of EVLW in survivors and non-survivors were extracted. Pooled OR were calculated from available studies. Mean differences and standard deviation of the EVLW between survivors and non-survivors were calculated. A random effects model was computed on the weighted mean differences across the two groups to estimate the pooled size effect. Subgroup analyses were performed to explore the possible sources of heterogeneity.

Results

Of the 18 studies included (1296 patients), OR could be extracted from 11 studies including 905 patients (464 survivors vs. 441 non-survivors), and 17 studies reported EVLW values of survivors and non-survivors, including 1246 patients (680 survivors vs. 566 non-survivors). The pooled OR of EVLW for mortality from eleven studies was 1.69 (95% confidence interval (CI) [1.22; 2.34], p < 0.0015). EVLW was significantly lower in survivors than non-survivors, with a mean difference of −4.97 mL/kg (95% CI [−6.54; −3.41], p < 0.001). The results regarding OR and mean differences were consistent in subgroup analyses.

Conclusions

The value of EVLW measured by TPTD is associated with mortality in critically ill patients and is significantly higher in non-survivors than in survivors. This finding may also be interpreted as an indirect confirmation of the reliability of TPTD for estimating EVLW at the bedside. Nevertheless, our results should be considered cautiously due to the high risk of bias of many studies included in the meta-analysis and the low rating of certainty of evidence.

Trial registration the study protocol was prospectively registered on PROSPERO: CRD42019126985.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-022-04061-6.

htseq-clip: a toolset for the preprocessing of eCLIP/iCLIP datasets

SUMMARY

Transcriptome-wide detection of binding sites of RNA-binding proteins is achieved using Individual-nucleotide crosslinking and immunoprecipitation (iCLIP) and its derivative enhanced CLIP (eCLIP) sequencing methods. Here, we introduce htseq-clip, a python package developed for preprocessing, extracting and summarizing crosslink site counts from i/eCLIP experimental data. The package delivers crosslink site count matrices along with other metrics, which can be directly used for filtering and downstream analyses such as the identification of differential binding sites.

AVAILABILITY AND IMPLEMENTATION

The Python package htseq-clip is available via pypi (python package index), bioconda and the Galaxy Tool Shed under the open source MIT License. The code is hosted at https://github.com/EMBL-Hentze-group/htseq-clip and documentation is available under https://htseq-clip.readthedocs.io/en/latest.

Proteogenomics refines the molecular classification of chronic lymphocytic leukemia

Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic-based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterize the proteome and transcriptome alongside genetic and ex-vivo drug response profiling in a clinically annotated CLL discovery cohort (n = 68). Unsupervised clustering of the proteome data reveals six subgroups. Five of these proteomic groups are associated with genetic features, while one group is only detectable at the proteome level. This new group is characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). Classifiers developed to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n = 165, n = 169) confirm that ASB-CLL comprises about 20% of CLL patients. The inferior overall survival in ASB-CLL is also independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling.

Metabolic balance in colorectal cancer is maintained by optimal Wnt signaling levels

Wnt pathways are important for the modulation of tissue homeostasis, and their deregulation is linked to cancer development. Canonical Wnt signaling is hyperactivated in many human colorectal cancers due to genetic alterations of the negative Wnt regulator APC. However, the expression levels of Wnt-dependent targets vary between tumors, and the mechanisms of carcinogenesis concomitant with this Wnt signaling dosage have not been understood. In this study, we integrate whole-genome CRISPR/Cas9 screens with large-scale multi-omic data to delineate functional subtypes of cancer. We engineer APC loss-of-function mutations and thereby hyperactivate Wnt signaling in cells with low endogenous Wnt activity and find that the resulting engineered cells have an unfavorable metabolic equilibrium compared with cells which naturally acquired Wnt hyperactivation. We show that the dosage level of oncogenic Wnt hyperactivation impacts the metabolic equilibrium and the mitochondrial phenotype of a given cell type in a context-dependent manner. These findings illustrate the impact of context-dependent genetic interactions on cellular phenotypes of a central cancer driver mutation and expand our understanding of quantitative modulation of oncogenic signaling in tumorigenesis.

Drug-microenvironment perturbations reveal resistance mechanisms and prognostic subgroups in CLL

The tumour microenvironment and genetic alterations collectively influence drug efficacy in cancer, but current evidence is limited and systematic analyses are lacking. Using chronic lymphocytic leukaemia (CLL) as a model disease, we investigated the influence of 17 microenvironmental stimuli on 12 drugs in 192 genetically characterised patient samples. Based on microenvironmental response, we identified four subgroups with distinct clinical outcomes beyond known prognostic markers. Response to multiple microenvironmental stimuli was amplified in trisomy 12 samples. Trisomy 12 was associated with a distinct epigenetic signature. Bromodomain inhibition reversed this epigenetic profile and could be used to target microenvironmental signalling in trisomy 12 CLL. We quantified the impact of microenvironmental stimuli on drug response and their dependence on genetic alterations, identifying interleukin 4 (IL4) and Toll‐like receptor (TLR) stimulation as the strongest actuators of drug resistance. IL4 and TLR signalling activity was increased in CLL‐infiltrated lymph nodes compared with healthy samples. High IL4 activity correlated with faster disease progression. The publicly available dataset can facilitate the investigation of cell‐extrinsic mechanisms of drug resistance and disease progression.

Systematic discovery of biomolecular condensate-specific protein phosphorylation

Reversible protein phosphorylation is an important mechanism for regulating (dis)assembly of biomolecular condensates. However, condensate-specific phosphosites remain largely unknown, thereby limiting our understanding of the underlying mechanisms. Here, we combine solubility proteome profiling with phosphoproteomics to quantitatively map several hundred phosphosites enriched in either soluble or condensate-bound protein subpopulations, including a subset of phosphosites modulating protein–RNA interactions. We show that multi-phosphorylation of the C-terminal disordered segment of heteronuclear ribonucleoprotein A1 (HNRNPA1), a key RNA-splicing factor, reduces its ability to locate to nuclear clusters. For nucleophosmin 1 (NPM1), an essential nucleolar protein, we show that phosphorylation of S254 and S260 is crucial for lowering its partitioning to the nucleolus and additional phosphorylation of distal sites enhances its retention in the nucleoplasm. These phosphorylation events decrease RNA and protein interactions of NPM1 to regulate its condensation. Our dataset is a rich resource for systematically uncovering the phosphoregulation of biomolecular condensates.

A combination of solubility proteome profiling with phosphoproteomics enables systematic analysis of the phosphorylation status of proteins in soluble and condensate-bound pools.

Prediction of Outcome in Acute Pancreatitis by the qSOFA and the New ERAP Score

BACKGROUND

Early identification of patients with acute severe pancreatitis is important for prompt and adequate treatment. Existing scores for pancreatitis are often laborious or require serial patient evaluation, whereas the qSOFA score, that was established to predict outcome in patients with suspected infection, is simple to perform.

AIMS AND METHODS

In this cohort study, we analyse the potential of the qSOFA score to predict outcome of patients with acute pancreatitis and refine the qSOFA score by rapid available laboratory parameters to the emergency room assessment of acute pancreatitis (ERAP) score. Validation was performed in a separate patient cohort.

RESULTS

In total 203 patients with acute pancreatitis were recruited. The qSOFA score has the potential to predict ICU admission (AUC = 0.730, p = 0.002) and organ failure (AUC = 0.799, p = 0.013) in acute pancreatitis. Respiratory rate, mental status, blood urea nitrogen and C-reactive protein are the rapid available parameters with the highest individual impact in binary logistic regression analyses. Their combination to the ERAP score can predict severity of acute pancreatitis according to the revised Atlanta classification (AUC = 0.689 ± 0.041, p < 0.001), ICU admission (AUC = 0.789 ± 0.067, p < 0.001), multi-organ dysfunction syndrome (AUC = 0.963 ± 0.024, p < 0.001) and mortality (AUC = 0.952 ± 0.028, p = 0.001). The performance and prognostic validity for organ failure and mortality were validated in an independent patient cohort.

CONCLUSION

The qSOFA is a rapidly available prognostic score in acute pancreatitis with limited prognostic validity. A combination with the laboratory parameters BUN and CRP results in the new ERAP score with outstanding prognostic validity for multi-organ dysfunction syndrome and mortality.

MatrixQCvis: shiny-based interactive data quality exploration for omics data

MOTIVATION

First-line data quality assessment and exploratory data analysis are integral parts of any data analysis workflow. In high-throughput quantitative omics experiments (e.g. transcriptomics, proteomics and metabolomics), after initial processing, the data are typically presented as a matrix of numbers (feature IDs × samples). Efficient and standardized data quality metrics calculation and visualization are key to track the within-experiment quality of these rectangular data types and to guarantee for high-quality datasets and subsequent biological question-driven inference.

RESULTS

We present MatrixQCvis, which provides interactive visualization of data quality metrics at the per-sample and per-feature level using R's shiny framework. It provides efficient and standardized ways to analyze data quality of quantitative omics data types that come in a matrix-like format (features IDs × samples). MatrixQCvis builds upon the Bioconductor SummarizedExperiment S4 class and thus facilitates the integration into existing workflows.

AVAILABILITY AND IMPLEMENTATION

MatrixQCVis is implemented in R. It is available via Bioconductor and released under the GPL v3.0 license.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Pairwise effects between lipid GWAS genes modulate lipid plasma levels and cellular uptake

Complex traits are characterized by multiple genes and variants acting simultaneously on a phenotype. However, studying the contribution of individual pairs of genes to complex traits has been challenging since human genetics necessitates very large population sizes, while findings from model systems do not always translate to humans. Here, we combine genetics with combinatorial RNAi (coRNAi) to systematically test for pairwise additive effects (AEs) and genetic interactions (GIs) between 30 lipid genome-wide association studies (GWAS) genes. Gene-based burden tests from 240,970 exomes show that in carriers with truncating mutations in both, APOB and either PCSK9 or LPL ("human double knock-outs") plasma lipid levels change additively. Genetics and coRNAi identify overlapping AEs for 12 additional gene pairs. Overlapping GIs are observed for TOMM40/APOE with SORT1 and NCAN. Our study identifies distinct gene pairs that modulate plasma and cellular lipid levels primarily via AEs and nominates putative drug target pairs for improved lipid-lowering combination therapies.

Multi-omics reveals clinically relevant proliferative drive associated with mTOR-MYC-OXPHOS activity in chronic lymphocytic leukemia

Chronic Lymphocytic Leukemia (CLL) has a complex pattern of driver mutations and much of its clinical diversity remains unexplained. We devised a method for simultaneous subgroup discovery across multiple data types and applied it to genomic, transcriptomic, DNA methylation and ex-vivo drug response data from 217 Chronic Lymphocytic Leukemia (CLL) cases. We uncovered a biological axis of heterogeneity strongly associated with clinical behavior and orthogonal to the known biomarkers. We validated its presence and clinical relevance in four independent cohorts (n=547 patients). We find that this axis captures the proliferative drive (PD) of CLL cells, as it associates with lymphocyte doubling rate, global hypomethylation, accumulation of driver aberrations and response to pro-proliferative stimuli. CLL-PD was linked to the activation of mTOR-MYC-oxidative phosphorylation (OXPHOS) through transcriptomic, proteomic and single cell resolution analysis. CLL-PD is a key determinant of disease outcome in CLL. Our multi-table integration approach may be applicable to other tumors whose inter-individual differences are currently unexplained.

Extracorporeal carbon dioxide Removal (ECCO2 R) with the Advanced Organ Support (ADVOS) system in critically ill COVID-19 patients

Disturbed oxygenation is foremost the leading clinical presentation in COVID‐19 patients. However, a small proportion also develop carbon dioxide removal problems. The Advanced Organ Support (ADVOS) therapy (ADVITOS GmbH, Munich, Germany) uses a less invasive approach by combining extracorporeal CO₂‐removal and multiple organ support for the liver and the kidneys in a single hemodialysis device. The aim of our study is to evaluate the ADVOS system as treatment option in‐COVID‐19 patients with multi‐organ failure and carbon dioxide removal problems. COVID‐19 patients suffering from severe respiratory insufficiency, receiving at least two treatments with the ADVOS multi system (ADVITOS GmbH, Munich, Germany), were eligible for study inclusion. Briefly, these included patients with acute kidney injury (AKI) according to KDIGO guidelines, and moderate or severe ARDS according to the Berlin definition, who were on invasive mechanical ventilation for more than 72 hours. In total, nine COVID‐19 patients (137 ADVOS treatment sessions with a median of 10 treatments per patient) with moderate to severe ARDS and carbon dioxide removal problems were analyzed. During the ADVOS treatments, a rapid correction of acid‐base balance and a continuous CO₂ removal could be observed. We observed a median continuous CO₂ removal of 49.2 mL/min (IQR: 26.9‐72.3 mL/min) with some treatments achieving up to 160 mL/min. The CO₂ removal significantly correlated with blood flow (Pearson 0.421; P < .001), PaCO₂ (0.341, P < .001) and HCO3‐ levels (0.568, P < .001) at the start of the treatment. The continuous treatment led to a significant reduction in PaCO₂ from baseline to the last ADVOS treatment. In conclusion, it was feasible to remove CO₂ using the ADVOS system in our cohort of COVID‐19 patients with acute respiratory distress syndrome and multiorgan failure. This efficient removal of CO₂ was achieved at blood flows up to 300 mL/min using a conventional hemodialysis catheter and without a membrane lung or a gas phase.

Timer-based proteomic profiling of the ubiquitin-proteasome system reveals a substrate receptor of the GID ubiquitin ligase

Selective protein degradation by the ubiquitin-proteasome system (UPS) is involved in all cellular processes. However, the substrates and specificity of most UPS components are not well understood. Here we systematically characterized the UPS in Saccharomyces cerevisiae. Using fluorescent timers, we determined how loss of individual UPS components affects yeast proteome turnover, detecting phenotypes for 76% of E2, E3, and deubiquitinating enzymes. We exploit this dataset to gain insights into N-degron pathways, which target proteins carrying N-terminal degradation signals. We implicate Ubr1, an E3 of the Arg/N-degron pathway, in targeting mitochondrial proteins processed by the mitochondrial inner membrane protease. Moreover, we identify Ylr149c/Gid11 as a substrate receptor of the glucose-induced degradation-deficient (GID) complex, an E3 of the Pro/N-degron pathway. Our results suggest that Gid11 recognizes proteins with N-terminal threonines, expanding the specificity of the GID complex. This resource of potential substrates and relationships between UPS components enables exploring functions of selective protein degradation.

Penetration of Isavuconazole in Ascites Fluid of Critically Ill Patients

Fungal peritonitis is a life-threatening condition which is not only difficult to diagnose, but also to treat. Following recent guidelines, echinocandins and azoles are the recommended antimycotics for the management of intra-abdominal Candida spp. infections, with a favor for echinocandins in critically ill patients. However, the new extended spectrum triazole isavuconazole also has a broad spectrum against Candida spp. Data on its target-site penetration are sparse. Therefore, we assessed isavuconazole concentrations and penetration ratios in ascites fluid of critically ill patients. Obtaining of Isavuconazole plasma and ascites fluid levels as well penetration ratios using paracentesis in critically ill patients. Isavuconazole concentrations were quantified in human plasma and ascites by a liquid chromatography/tandem mass spectrometry (LC-MS/MS) method. Isavuconazole concentrations in plasma and ascites fluid were measured in sixteen critically ill patients. Isavuconazol levels in ascites fluid (1.06 µg/mL) were lower than plasma levels (3.08 µg/mL). Penetration ratio was 36%. In two out of sixteen patients, Candida spp., in detail C. glabrata and C. tropicalis, could be isolated. Cmax/MIC Ratio in plasma of 560 for C. glabrata and 2166 for C. tropicalis could be observed. Following our results, isavuconazole penetrates into ascites. Successful treatment in Candida spp. peritonitis depends on pathogen susceptibility.

glmGamPoi: fitting Gamma-Poisson generalized linear models on single cell count data

Motivation

The Gamma-Poisson distribution is a theoretically and empirically motivated model for the sampling variability of single cell RNA-sequencing counts and an essential building block for analysis approaches including differential expression analysis, principal component analysis and factor analysis. Existing implementations for inferring its parameters from data often struggle with the size of single cell datasets, which can comprise millions of cells; at the same time, they do not take full advantage of the fact that zero and other small numbers are frequent in the data. These limitations have hampered uptake of the model, leaving room for statistically inferior approaches such as logarithm(-like) transformation.

Results

We present a new R package for fitting the Gamma-Poisson distribution to data with the characteristics of modern single cell datasets more quickly and more accurately than existing methods. The software can work with data on disk without having to load them into RAM simultaneously.

Availabilityand implementation

The package glmGamPoi is available from Bioconductor for Windows, macOS and Linux, and source code is available on github.com/const-ae/glmGamPoi under a GPL-3 license. The scripts to reproduce the results of this paper are available on github.com/const-ae/glmGamPoi-Paper.

Supplementary information

Supplementary data are available at Bioinformatics online.

Control of PD-L1 expression in CLL-cells by stromal triggering of the Notch-c-Myc-EZH2 oncogenic signaling axis

Chronic lymphocytic leukemia (CLL) is the most common leukemia in adults. Emerging data suggest that CLL-cells efficiently evade immunosurveillance. T-cell deficiencies in CLL include immuno(metabolic) exhaustion that is achieved by inhibitory molecules, with programmed cell death 1/programmed cell death ligand 1 (PD-L1) signaling emerging as a major underlying mechanism. Moreover, CLL-cells are characterized by a close and recurrent interaction with their stromal niches in the bone marrow and lymph nodes. Here, they receive nurturing signals within a well-protected environment. We could previously show that the interaction of CLL-cells with stroma leads to c-Myc activation that is followed by metabolic adaptations. Recent data indicate that c-Myc also controls expression of the immune checkpoint molecule PD-L1. Therefore, we sought out to determine the role of stromal contact for the CLL-cells' PD-L1 expression and thus their immuno-evasive phenotype.To do so, we analyzed PD-L1 expression on CLL cell (subsets) in untreated patients and on healthy donor-derived B-cells. Impact of stromal contact on PD-L1 expression on CLL-cells and the underlying signaling pathways were assessed in well-established in vitro niche models. Ex vivo and in vitro findings were validated in the Eµ-TCL1 transgenic CLL mouse model.We found increased PD-L1 expression on CLL-cells as compared with B-cells that was further enhanced in a cell-to-cell contact-dependent manner by stromal cells. In fact, circulating recent stromal-niche emigrants displayed higher PD-L1 levels than long-time circulating CLL-cells. Using our in vitro niche model, we show that a novel Notch-c-Myc-enhancer of zeste homolog 2 (EZH2) signaling axis controls PD-L1 upregulation. Ultimately, elevated PD-L1 levels conferred increased resistance towards activated autologous T-cells.In summary, our findings support the notion that the CLL microenvironment contributes to immune escape variants. In addition, several targetable molecules (eg, Notch or EZH2) could be exploited in view of improving immune responses in patients with CLL, which warrants further in-depth investigation.

Invasive pulmonary aspergillosis in critically ill patients with severe COVID-19 pneumonia: Results from the prospective AspCOVID-19 study

Background

Superinfections, including invasive pulmonary aspergillosis (IPA), are well-known complications of critically ill patients with severe viral pneumonia. Aim of this study was to evaluate the incidence, risk factors and outcome of IPA in critically ill patients with severe COVID-19 pneumonia.

Methods

We prospectively screened 32 critically ill patients with severe COVID-19 pneumonia for a time period of 28 days using a standardized study protocol for oberservation of developement of COVID-19 associated invasive pulmonary aspergillosis (CAPA). We collected laboratory, microbiological, virological and clinical parameters at defined timepoints in combination with galactomannan-antigen-detection from nondirected bronchial lavage (NBL). We used logistic regression analyses to assess if COVID-19 was independently associated with IPA and compared it with matched controls.

Findings

CAPA was diagnosed at a median of 4 days after ICU admission in 11/32 (34%) of critically ill patients with severe COVID-19 pneumonia as compared to 8% in the control cohort. In the COVID-19 cohort, mean age, APACHE II score and ICU mortality were higher in patients with CAPA than in patients without CAPA (36% versus 9.5%; p<0.001). ICU stay (21 versus 17 days; p = 0.340) and days of mechanical ventilation (20 versus 15 days; p = 0.570) were not different between both groups. In regression analysis COVID-19 and APACHE II score were independently associated with IPA.

Interpretation

CAPA is highly prevalent and associated with a high mortality rate. COVID-19 is independently associated with invasive pulmonary aspergillosis. A standardized screening and diagnostic approach as presented in our study can help to identify affected patients at an early stage.

Analysis of nonleukemic cellular subcompartments reconstructs clonal evolution of acute myeloid leukemia and identifies therapy-resistant preleukemic clones

To acquire a better understanding of clonal evolution of acute myeloid leukemia (AML) and to identify the clone(s) responsible for disease recurrence, we have comparatively studied leukemia-specific mutations by whole-exome-sequencing (WES) of both the leukemia and the nonleukemia compartments derived from the bone marrow of AML patients. The T-lymphocytes, B-lymphocytes and the functionally normal hematopoietic stem cells (HSC), that is, CD34⁺ /CD38^- /ALDH⁺ cells for AML with rare-ALDH⁺ blasts (<1.9% ALDH⁺ cells) were defined as the nonleukemia compartments. WES identified 62 point-mutations in the leukemia compartment derived from 12 AML-patients at the time of diagnosis and 73 mutations in 3 matched relapse cases. Most patients (8/12) showed 4 to 6 point-mutations per sample at diagnosis. Other than the mutations in the recurrently mutated genes such as DNMT3A, NRAS and KIT, we were able to identify novel point-mutations that have not yet been described in AML. Some leukemia-specific mutations and cytogenetic abnormalities including DNMT3A(R882H), EZH2(I146T) and inversion(16) were also detectable in the respective T-lymphocytes, B-lymphocytes and HSC in 5/12 patients, suggesting that preleukemia HSC might represent the source of leukemogenesis for these cases. The leukemic evolution was reconstructed for five cases with detectable preleukemia clones, which were tracked in follow-up and relapse samples. Four of the five patients with detectable preleukemic mutations developed relapse. The presence of leukemia-specific mutations in these nonleukemia compartments, especially after chemotherapy or after allogeneic stem cell transplantation, is highly relevant, as these could be responsible for relapse. This discovery may facilitate the identification of novel targets for long-term cure.

Comparison of global end-diastolic volume index derived from jugular and femoral indicator injection: a prospective observational study in patients equipped with both a PiCCO-2 and an EV-1000-device

Transpulmonary thermodilution (TPTD)-derived global end-diastolic volume index (GEDVI) is a static marker of preload which better predicted volume responsiveness compared to filling pressures in several studies. GEDVI can be generated with at least two devices: PiCCO and EV-1000. Several studies showed that uncorrected indicator injection into a femoral central venous catheter (CVC) results in a significant overestimation of GEDVI by the PiCCO-device. Therefore, the most recent PiCCO-algorithm corrects for femoral indicator injection. However, there are no systematic data on the impact of femoral indicator injection for the EV-1000 device. Furthermore, the correction algorithm of the PiCCO is poorly validated. Therefore, we prospectively analyzed 14 datasets from 10 patients with TPTD-monitoring undergoing central venous catheter (CVC)- and arterial line exchange. PiCCO was replaced by EV-1000, femoral CVCs were replaced by jugular/subclavian CVCs and vice-versa. For PiCCO, jugular and femoral indicator injection derived GEDVI was comparable when the correct information about femoral catheter site was given (p = 0.251). By contrast, GEDVI derived from femoral indicator injection using the EV-1000 was obviously not corrected and was substantially higher than jugular GEDVI measured by the EV-1000 (846 ± 250 vs. 712 ± 227 ml/m²; p = 0.001). Furthermore, measurements of GEDVI were not comparable between PiCCO and EV-1000 even in case of jugular indicator injection (p = 0.003). This is most probably due to different indexations of the raw value GEDV. EV-1000 could not be recommended to measure GEDVI in case of a femoral CVC. Furthermore, different indexations used by EV-1000 and PiCCO should be considered even in case of a jugular CVC when comparing GEDVI derived from PiCCO and EV-1000.

A computational method for detection of ligand-binding proteins from dose range thermal proteome profiles

Detecting ligand-protein interactions in living cells is a fundamental challenge in molecular biology and drug research. Proteome-wide profiling of thermal stability as a function of ligand concentration promises to tackle this challenge. However, current data analysis strategies use preset thresholds that can lead to suboptimal sensitivity/specificity tradeoffs and limited comparability across datasets. Here, we present a method based on statistical hypothesis testing on curves, which provides control of the false discovery rate. We apply it to several datasets probing epigenetic drugs and a metabolite. This leads us to detect off-target drug engagement, including the finding that the HDAC8 inhibitor PCI-34051 and its analog BRD-3811 bind to and inhibit leucine aminopeptidase 3. An implementation is available as an R package from Bioconductor (https://bioconductor.org/packages/TPP2D). We hope that our method will facilitate prioritizing targets from thermal profiling experiments.

2D-thermal proteome profiling (2D-TPP) is a powerful assay for probing interactions of proteins with small molecules in their native context. Here the authors provide a statistical method for false discovery rate controlled analysis for 2D-TPP applications.

B-Lines Scores Derived From Lung Ultrasound Provide Accurate Prediction of Extravascular Lung Water Index: An Observational Study in Critically Ill Patients

Introduction:

Visualization of B-lines via lung ultrasound provides a non-invasive estimation of pulmonary hydration. Extravascular lung water index (EVLWI) and pulmonary vascular permeability index (PVPI) assessed by transpulmonary thermodilution (TPTD) represent the most validated parameters of lung water and alveolocapillary permeability, but measurement is invasive and expensive. This study aimed to compare the correlations of B-lines scores from extensive 28-sector and simplified 4-sector chest scan with EVLWI and PVPI derived from TPTD in the setting of intensive care unit (primary endpoint).

Methods:

We performed scoring of 28-sector and 4-sector B-Lines in 50 critically ill patients. TPTD was carried out with the PiCCO-2-device (Pulsion Medical Systems SE, Maquet Getinge Group). Median time exposure for ultrasound procedure was 12 minutes for 28-sector and 4 minutes for 4-sector scan.

Results:

Primarily, we found close correlations of 28-sector as well as 4-sector B-Lines scores with EVLWI (R² = 0.895 vs. R² = 0.880) and PVPI (R² = 0.760 vs. R² = 0.742). Both B-lines scores showed high accuracy to identify patients with specific levels of EVLWI and PVPI. The extensive 28-sector B-lines score revealed a moderate advantage compared to simplified 4-sector scan in detecting a normal EVLWI ≤ 7 (28-sector scan: sensitivity = 81.8%, specificity = 94.9%, AUC = 0.939 versus 4-sector scan: sensitivity = 81.8%, specificity = 82.1%, AUC = 0.902). Both protocols were approximately equivalent in prediction of lung edema with EVLWI ≥ 10 (28-sector scan: sensitivity = 88.9%, specificity = 95.7%, AUC = 0.977 versus 4-sector scan: sensitivity = 81.5%, specificity = 91.3%, AUC = 0.958) or severe pulmonary edema with EVLWI ≥ 15 (28-sector scan: sensitivity = 91.7%, specificity = 97.4%, AUC = 0.995 versus 4-sector scan: sensitivity = 91.7%, specificity = 92.1%, AUC = 0.978). As secondary endpoints, our evaluations resulted in significant associations of 28-sector as well as simplified 4-sector B-Lines score with parameters of respiratory function.

Conclusion:

Both B-line protocols provide accurate non-invasive evaluation of lung water in critically ill patients. The 28-sector scan offers a marginal advantage in prediction of pulmonary edema, but needs substantially more time than 4-sector scan.

Developmental Gene Expression Differences between Humans and Mammalian Models

Identifying the molecular programs underlying human organ development and how they differ from model species is key for understanding human health and disease. Developmental gene expression profiles provide a window into the genes underlying organ development and a direct means to compare them across species. We use a transcriptomic resource covering the development of seven organs to characterize the temporal profiles of human genes associated with distinct disease classes and to determine, for each human gene, the similarity of its spatiotemporal expression with its orthologs in rhesus macaque, mouse, rat, and rabbit. We find clear associations between spatiotemporal profiles and the phenotypic manifestations of diseases. We also find that half of human genes differ from their mouse orthologs in their temporal trajectories in at least one of the organs. These include more than 200 genes associated with brain, heart, and liver disease for which mouse models should undergo extra scrutiny.

Title: Cytokine release syndrome is not usually caused by secondary hemophagocytic lymphohistiocytosis in a cohort of 19 critically ill COVID-19 patients

Severe COVID-19 associated respiratory failure, poses the one challenge of our days. Assessment and treatment of COVID-19 associated hyperinflammation may be key to improve outcomes. It was speculated that in subgroups of patients secondary hemophagocytic lymphohistiocytosis (sHLH) or cytokine release syndrome (CRS) with features of macrophage activation syndrome might drive severe disease trajectories. If confirmed, profound immunosuppressive therapy would be a rationale treatment approach. Over a median observation period of 11 (IQR: 8; 16) days, 19 consecutive confirmed severe COVID-19-patients admitted to our intensive-care-unit were tested for presence of sHLH by two independent experts. HScores and 2004-HLH diagnostic criteria were assessed. Patients were grouped according to short-term clinical courses: discharge from ICU versus ongoing ARDS or death at time of analysis. The median HScore at admission was 157 (IQR: 98;180), without the key clinical triad of HLH, i.e. progressive cytopenia, persistent fever and organomegaly. Independent expert chart review revealed the absence of sHLH in all cases. No patient reached more than 3/6 of modified HLH 2004 criteria. Nevertheless, patients presented hyperinflammation with peripheral neutrophilic signatures (neutrophil/lymphocyte-ratio > 3.5). The latter best paralleled their short-term clinical courses, with declining relative neutrophil numbers prior to extubation (4.4, [IQR: 2.5;6.3]; n = 8) versus those with unfavourable courses (7.6, [IQR: 5.2;31], n = 9). Our study rules out virus induced sHLH as the leading cause of most severe-COVID-19 trajectories. Instead, an associated innate neutrophilic hyperinflammatory response or virus-associated-CRS appears dominant in patients with an unfavourable clinical course. Therapeutic implications are discussed.

Transparency and reproducibility in artificial intelligence

Breakthroughs in artificial intelligence (AI) hold enormous potential as it can automate complex tasks and go even beyond human performance. In their study, McKinney et al. showed the high potential of AI for breast cancer screening. However, the lack of methods’ details and algorithm code undermines its scientific value. Here, we identify obstacles hindering transparent and reproducible AI research as faced by McKinney et al., and provide solutions to these obstacles with implications for the broader field.

Extracorporeal multiorgan support including CO2-removal with the ADVanced Organ Support (ADVOS) system for COVID-19: A case report

A substantial part of COVID-19-patients suffers from multi-organ failure (MOF). We report on an 80-year old patient with pulmonary, renal, circulatory, and hepatic failure. We decided against the use of extracorporeal membrane oxygenation (ECMO) due to old age and a SOFA-score of 13. However, the patient was continuously treated with the extracorporeal multi-organ- “ADVanced Organ Support” (ADVOS) device (ADVITOS GmbH, Munich, Germany). During eight 24h-treatment-sessions blood flow (100–300 mL/min), dialysate flow (160–320 mL/min) and dialysate pH (7.6–9.0) were adapted to optimize arterial PaCO₂ and pH. Effective CO₂ removal and correction of acidosis could be demonstrated by mean arterial- versus post-dialyzer values of pCO₂ (68.7 ± 13.8 vs. 26.9 ± 11.6 mmHg; p < 0.001). The CO₂-elimination rate was 48 ± 23mL/min. The initial vasopressor requirement could be reduced in parallel to pH-normalization. Interruptions of ADVOS-treatment repeatedly resulted in reversible deteriorations of p_aCO₂ and pH. After 95 h of continuous extracorporeal decarboxylating therapy the patient had markedly improved circulatory parameters compared to baseline. In the context of secondary pulmonary infection and progressive liver failure, the patient had a sudden cardiac arrest. In accordance with the presumed patient will, we decided against mechanical resuscitation. Irrespective of the outcome we conclude that extracorporeal CO₂ removal and multiorgan-support were feasible in this COVID-19-patient. Combined and less invasive approaches such as ADVOS might be considered in old-age-COVID-19 patients with MOF.

Ascitic Interleukin 6 Is Associated with Poor Outcome and Spontaneous Bacterial Peritonitis: A Validation in Critically Ill Patients with Decompensated Cirrhosis

Decompensated cirrhosis predisposes to infectious diseases and acute-on-chronic liver failure (ACLF) in critically ill patients. Infections like spontaneous bacterial peritonitis (SBP) are frequently associated with multi-organ failure and increased mortality. Consequently, reliable predictors of outcome and early diagnostic markers of infection are needed to improve individualized therapy. This study evaluates the prognostic role of ascitic interleukin 6 in 64 patients with cirrhosis admitted to our intensive care unit (ICU). In addition, we analysed the diagnostic ability of ascitic interleukin 6 in a subgroup of 19 patients with SBP. Baseline ascitic interleukin 6 performed well in predicting 3-month mortality in patients with decompensated cirrhosis (area under curve (AUC) = 0.802), as well as in patients fulfilling ACLF-criteria (AUC = 0.807). Ascitic interleukin 6 showed a moderate prognostic advantage compared with common clinical scores and proinflammatory parameters. Moreover, ascitic interleukin 6 had a sufficient diagnostic ability to detect SBP (AUC = 0.901) and was well correlated with ascitic polymorphonuclear neutrophils in SBP (p = 0.002). Interestingly, ascitic interleukin 6 revealed a high predictive value to rule out apparent infections on admission to ICU (AUC = 0.904) and to identify patients with “culture-positive SBP” (AUC = 0.856). Ascitic interleukin 6 is an easily-applicable proinflammatory biomarker with high prognostic and diagnostic relevance in critically ill patients with liver cirrhosis.

Aspergillus fumigatus cholangitis in a patient with cholangiocarcinoma: case report and review of the literature

Aspergillus spp. cholangitis is an uncommon presentation of invasive aspergillosis. Only few cases are described in the literature affecting severely immunocompromised patients or patients following biliary surgery. Especially, invasive aspergillosis in non-haematological patients is associated with high mortality rates, caused by atypical presentations, which is associated with a delay in diagnosis and therapy. We report a 72-year-old man with primary diagnosis of cholangiocarcinoma and stent implantation by endoscopic retrograde cholangiopancreatography (ERCP) for biliary decompression who developed severe cholangitis with invasive aspergillosis. The patient had no history of prior hospitalisation, no immunosuppressive therapy and no preceding biliary surgery. Furthermore, in this exceptional case of extrapulmonary aspergillosis, there were no signs of pulmonary involvement. From the literature review, only three cases of Aspergillus cholangitis could be identified. Clinical manifestations of invasive aspergillosis can be variable and classical risk factors such as immunosuppression are not mandatorily present. Clinical awareness of these rare cases is of vital importance for initiation of correct therapy.

Miniaturized Drug Sensitivity and Resistance Test on Patient-Derived Cells Using Droplet-Microarray

Testing the sensitivity of patient-derived tumor cells ex vivo can potentially help determining the appropriate treatment for each patient and spot the development of resistance to a given therapy. The number of cells obtainable from a biopsy is, however, often insufficient for performing ex vivo tests in conventional microtiter plates. Here, we introduce a novel Droplet-Microarray platform based on a hydrophilic-superhydrophobic patterned surface that enables screenings using only 100 cells and 30 picomoles of a drug per individual nanoliter-sized droplet. We demonstrate that the dose-response of as few as 100 primary patient-derived chronic lymphocytic leukemia (CLL) cells to anticancer compounds on the Droplet-Microarray platform resembles the dose-response obtained in 384-well plates requiring 20,000 tumor cells per experiment. The extremely miniaturized Droplet-Microarray platform thus carries great potential for ex vivo drug sensitivity and resistance tests on patient-derived tumor cells and potentially for implementing such tests in medical practice of precision medicine.

Reduced proteasome activity in the aging brain results in ribosome stoichiometry loss and aggregation

A progressive loss of protein homeostasis is characteristic of aging and a driver of neurodegeneration. To investigate this process quantitatively, we characterized proteome dynamics during brain aging in the short-lived vertebrate Nothobranchius furzeri combining transcriptomics and proteomics. We detected a progressive reduction in the correlation between protein and mRNA, mainly due to post-transcriptional mechanisms that account for over 40% of the age-regulated proteins. These changes cause a progressive loss of stoichiometry in several protein complexes, including ribosomes, which show impaired assembly/disassembly and are enriched in protein aggregates in old brains. Mechanistically, we show that reduction of proteasome activity is an early event during brain aging and is sufficient to induce proteomic signatures of aging and loss of stoichiometry in vivo. Using longitudinal transcriptomic data, we show that the magnitude of early life decline in proteasome levels is a major risk factor for mortality. Our work defines causative events in the aging process that can be targeted to prevent loss of protein homeostasis and delay the onset of age-related neurodegeneration.

Intensive Care Risk Estimation in COVID-19 Pneumonia Based on Clinical and Imaging Parameters: Experiences from the Munich Cohort

The evolving dynamics of coronavirus disease 2019 (COVID-19) and the increasing infection numbers require diagnostic tools to identify patients at high risk for a severe disease course. Here we evaluate clinical and imaging parameters for estimating the need of intensive care unit (ICU) treatment. We collected clinical, laboratory and imaging data from 65 patients with confirmed COVID-19 infection based on polymerase chain reaction (PCR) testing. Two radiologists evaluated the severity of findings in computed tomography (CT) images on a scale from 1 (no characteristic signs of COVID-19) to 5 (confluent ground glass opacities in over 50% of the lung parenchyma). The volume of affected lung was quantified using commercially available software. Machine learning modelling was performed to estimate the risk for ICU treatment. Patients with a severe course of COVID-19 had significantly increased interleukin (IL)-6, C-reactive protein (CRP), and leukocyte counts and significantly decreased lymphocyte counts. The radiological severity grading was significantly increased in ICU patients. Multivariate random forest modelling showed a mean ± standard deviation sensitivity, specificity and accuracy of 0.72 ± 0.1, 0.86 ± 0.16 and 0.80 ± 0.1 and a receiver operating characteristic-area under curve (ROC-AUC) of 0.79 ± 0.1. The need for ICU treatment is independently associated with affected lung volume, radiological severity score, CRP, and IL-6.

Reporting p Values

Cell Systems Editorial Board member Wolfgang Huber demonstrates how he thinks about small p values.