Exploiting Nanobodies' Singular Traits.

The unique class of heavy chain-only antibodies, present in Camelidae, can be shrunk to just the variable region of the heavy chain to yield VHHs, also called nanobodies. About one-tenth the size of their full-size counterparts, nanobodies can serve in applications similar to those for conventional antibodies, but they come with a number of signature advantages that find increasing application in biology. They not only function as crystallization chaperones but also can be expressed inside cells as such, or fused to other proteins to perturb the function of their targets, for example, by enforcing their localization or degradation. Their small size also affords advantages when applied in vivo, for example, in imaging applications. Here we review such applications, with particular emphasis on those areas where conventional antibodies would face a more challenging environment.

Mitochondrial damage activates the NLRP10 inflammasome.

Upon detecting pathogens or cell stress, several NOD-like receptors (NLRs) form inflammasome complexes with the adapter ASC and caspase-1, inducing gasdermin D (GSDMD)-dependent cell death and maturation and release of IL-1ß and IL-18. The triggers and activation mechanisms of several inflammasome-forming sensors are not well understood. Here we show that mitochondrial damage activates the NLRP10 inflammasome, leading to ASC speck formation and caspase-1-dependent cytokine release. While the AIM2 inflammasome can also sense mitochondrial demise by detecting mitochondrial DNA (mtDNA) in the cytosol, NLRP10 monitors mitochondrial integrity in an mtDNA-independent manner, suggesting the recognition of distinct molecular entities displayed by the damaged organelles. NLRP10 is highly expressed in differentiated human keratinocytes, in which it can also assemble an inflammasome. Our study shows that this inflammasome surveils mitochondrial integrity. These findings might also lead to a better understanding of mitochondria-linked inflammatory diseases.

Early IFN-α signatures and persistent dysfunction are distinguishing features of NK cells in severe COVID-19.

Longitudinal analyses of the innate immune system, including the earliest time points, are essential to understand the immunopathogenesis and clinical course of coronavirus disease (COVID-19). Here, we performed a detailed characterization of natural killer (NK) cells in 205 patients (403 samples; days 2 to 41 after symptom onset) from four independent cohorts using single-cell transcriptomics and proteomics together with functional studies. We found elevated interferon (IFN)-α plasma levels in early severe COVD-19 alongside increased NK cell expression of IFN-stimulated genes (ISGs) and genes involved in IFN-α signaling, while upregulation of tumor necrosis factor (TNF)-induced genes was observed in moderate diseases. NK cells exert anti-SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) activity but are functionally impaired in severe COVID-19. Further, NK cell dysfunction may be relevant for the development of fibrotic lung disease in severe COVID-19, as NK cells exhibited impaired anti-fibrotic activity. Our study indicates preferential IFN-α and TNF responses in severe and moderate COVID-19, respectively, and associates a prolonged IFN-α-induced NK cell response with poorer disease outcome.

Brain endothelial GSDMD activation mediates inflammatory BBB breakdown.

The blood-brain barrier (BBB) protects the central nervous system from infections or harmful substances1; its impairment can lead to or exacerbate various diseases of the central nervous system2-4. However, the mechanisms of BBB disruption during infection and inflammatory conditions5,6 remain poorly defined. Here we find that activation of the pore-forming protein GSDMD by the cytosolic lipopolysaccharide (LPS) sensor caspase-11 (refs. 7-9), but not by TLR4-induced cytokines, mediates BBB breakdown in response to circulating LPS or during LPS-induced sepsis. Mice deficient in the LBP-CD14 LPS transfer and internalization pathway10-12 resist BBB disruption. Single-cell RNA-sequencing analysis reveals that brain endothelial cells (bECs), which express high levels of GSDMD, have a prominent response to circulating LPS. LPS acting on bECs primes Casp11 and Cd14 expression and induces GSDMD-mediated plasma membrane permeabilization and pyroptosis in vitro and in mice. Electron microscopy shows that this features ultrastructural changes in the disrupted BBB, including pyroptotic endothelia, abnormal appearance of tight junctions and vasculature detachment from the basement membrane. Comprehensive mouse genetic analyses, combined with a bEC-targeting adeno-associated virus system, establish that GSDMD activation in bECs underlies BBB disruption by LPS. Delivery of active GSDMD into bECs bypasses LPS stimulation and opens the BBB. In CASP4-humanized mice, Gram-negative Klebsiella pneumoniae infection disrupts the BBB; this is blocked by expression of a GSDMD-neutralizing nanobody in bECs. Our findings outline a mechanism for inflammatory BBB breakdown, and suggest potential therapies for diseases of the central nervous system associated with BBB impairment.

CD14-New Tricks of an Old Acquaintance.

Zanoni et al. (2017) show that the LPS receptor CD14 promotes internalization of oxidized phospholipids, a hallmark of dying cells, triggering hyperactivation of dendritic cells and macrophages. Their findings reveal CD14 as a regulator of responses to infection and damage, relaying context-dependent signals that determine inflammatory cell fate decisions.

A single-cell atlas identifies pretreatment features of primary imatinib resistance in chronic myeloid leukemia.

Primary resistance to tyrosine kinase inhibitors (TKIs) is a significant barrier to optimal outcomes in chronic myeloid leukemia (CML), but factors contributing to response heterogeneity remain unclear. Using single-cell RNA (scRNA) sequencing, we identified 8 statistically significant features in pretreatment bone marrow, which correlated with either sensitivity (major molecular response or MMR) or extreme resistance to imatinib (eventual blast crisis [BC] transformation). Employing machine-learning, we identified leukemic stem cell (LSC) and natural killer (NK) cell gene expression profiles predicting imatinib response with >80% accuracy, including no false positives for predicting BC. A canonical erythroid-specifying (TAL1/KLF1/GATA1) regulon was a hallmark of LSCs from patients with MMR and was associated with erythroid progenitor [ERP] expansion in vivo (P < .05), and a 2- to 10-fold (6.3-fold in group A vs 1.09-fold in group C) erythroid over myeloid bias in vitro. Notably, ERPs demonstrated exquisite TKI sensitivity compared with myeloid progenitors (P < .001). These LSC features were lost with progressive resistance, and MYC- and IRF1-driven inflammatory regulons were evident in patients who progressed to transformation. Patients with MMR also exhibited a 56-fold expansion (P < .01) of a normally rare subset of hyperfunctional adaptive-like NK cells, which diminished with progressive resistance, whereas patients destined for BC accumulated inhibitory NKG2A+ NK cells favoring NK cell tolerance. Finally, we developed antibody panels to validate our scRNA-seq findings. These panels may be useful for prospective studies of primary resistance, and in assessing the contribution of predetermined vs acquired factors in TKI response heterogeneity.

Epigenomic Profiling of Human CD4+ T Cells Supports a Linear Differentiation Model and Highlights Molecular Regulators of Memory Development.

The impact of epigenetics on the differentiation of memory T (Tmem) cells is poorly defined. We generated deep epigenomes comprising genome-wide profiles of DNA methylation, histone modifications, DNA accessibility, and coding and non-coding RNA expression in naive, central-, effector-, and terminally differentiated CD45RA+ CD4+ Tmem cells from blood and CD69+ Tmem cells from bone marrow (BM-Tmem). We observed a progressive and proliferation-associated global loss of DNA methylation in heterochromatic parts of the genome during Tmem cell differentiation. Furthermore, distinct gradually changing signatures in the epigenome and the transcriptome supported a linear model of memory development in circulating T cells, while tissue-resident BM-Tmem branched off with a unique epigenetic profile. Integrative analyses identified candidate master regulators of Tmem cell differentiation, including the transcription factor FOXP1. This study highlights the importance of epigenomic changes for Tmem cell biology and demonstrates the value of epigenetic data for the identification of lineage regulators.

Transcriptional licensing is required for Pyrin inflammasome activation in human macrophages and bypassed by mutations causing familial Mediterranean fever.

Pyrin is a cytosolic immune sensor that nucleates an inflammasome in response to inhibition of RhoA by bacterial virulence factors, triggering the release of inflammatory cytokines, including IL-1ß. Gain-of-function mutations in the MEFV gene encoding Pyrin cause autoinflammatory disorders, such as familial Mediterranean fever (FMF) and Pyrin-associated autoinflammation with neutrophilic dermatosis (PAAND). To precisely define the role of Pyrin in pathogen detection in human immune cells, we compared initiation and regulation of the Pyrin inflammasome response in monocyte-derived macrophages (hMDM). Unlike human monocytes and murine macrophages, we determined that hMDM failed to activate Pyrin in response to known Pyrin activators Clostridioides difficile (C. difficile) toxins A or B (TcdA or TcdB), as well as the bile acid analogue BAA-473. The Pyrin inflammasome response was enabled in hMDM by prolonged priming with either LPS or type I or II interferons and required an increase in Pyrin expression. Notably, FMF mutations lifted the requirement for prolonged priming for Pyrin activation in hMDM, enabling Pyrin activation in the absence of additional inflammatory signals. Unexpectedly, in the absence of a Pyrin response, we found that TcdB activated the NLRP3 inflammasome in hMDM. These data demonstrate that regulation of Pyrin activation in hMDM diverges from monocytes and highlights its dysregulation in FMF.

Widespread effects of DNA methylation and intra-motif dependencies revealed by novel transcription factor binding models.

Several studies suggested that transcription factor (TF) binding to DNA may be impaired or enhanced by DNA methylation. We present MeDeMo, a toolbox for TF motif analysis that combines information about DNA methylation with models capturing intra-motif dependencies. In a large-scale study using ChIP-seq data for 335 TFs, we identify novel TFs that show a binding behaviour associated with DNA methylation. Overall, we find that the presence of CpG methylation decreases the likelihood of binding for the majority of methylation-associated TFs. For a considerable subset of TFs, we show that intra-motif dependencies are pivotal for accurately modelling the impact of DNA methylation on TF binding. We illustrate that the novel methylation-aware TF binding models allow to predict differential ChIP-seq peaks and improve the genome-wide analysis of TF binding. Our work indicates that simplistic models that neglect the effect of DNA methylation on DNA binding may lead to systematic underperformance for methylation-associated TFs.

Transcriptional recording by CRISPR spacer acquisition from RNA.

The ability to record transcriptional events within a cell over time would help to elucidate how molecular events give rise to complex cellular behaviours and states. However, current molecular recording technologies capture only a small set of defined stimuli. Here we use CRISPR spacer acquisition to capture and convert intracellular RNAs into DNA, enabling DNA-based storage of transcriptional information. In Escherichia coli, we show that defined stimuli, such as an RNA virus or arbitrary sequences, as well as complex stimuli, such as oxidative stress, result in quantifiable transcriptional records that are stored within a population of cells. We demonstrate that the transcriptional records enable us to classify and describe complex cellular behaviours and to identify the precise genes that orchestrate differential cellular responses. In the future, CRISPR spacer acquisition-mediated recording of RNA followed by deep sequencing (Record-seq) could be used to reconstruct transcriptional histories that describe complex cell behaviours or pathological states.

The curvature quantification of wave I in auditory brainstem responses detects cochlear synaptopathy in human beings.

PURPOSE: Patients with age-related hearing loss complain often about reduced speech perception in adverse listening environment. Studies on animals have suggested that cochlear synaptopathy may be one of the primary mechanisms responsible for this phenomenon. A decreased wave I amplitude in supra-threshold auditory brainstem response (ABR) can diagnose this pathology non-invasively. However, the interpretation of the wave I amplitude in humans remains controversial. Recent studies in mice have established a robust and reliable mathematic algorithm, i.e., curve curvature quantification, for detecting cochlear synaptopathy. This study aimed to determine whether the curve curvature has sufficient test-retest reliability to detect cochlear synaptopathy in aging humans. METHODS: Healthy participants were recruited into this prospective study. All subjects underwent an audiogram examination with standard and extended high frequencies ranging from 0.125 to 16 kHz and an ABR with a stimulus of 80 dB nHL click. The peak amplitude, peak latency, curvature at the peak, and the area under the curve of wave I were calculated and analyzed. RESULTS: A total of 80 individuals with normal hearing, aged 18 to 61 years, participated in this study, with a mean age of 26.4 years. Pearson correlation analysis showed a significant negative correlation between curvature and age, as well as between curvature and extended high frequency (EHF) threshold (10-16 kHz). Additionally, the same correlation was observed between age and area as well as age and EHF threshold. The model comparison demonstrated that the curvature at the peak of wave I is the best metric to correlate with EHF threshold. CONCLUSION: The curvature at the peak of wave I is the most sensitive metric for detecting cochlear synaptopathy in humans  and may be applied in routine diagnostics to detect early degenerations of the auditory nerve.

Quantitative Tomographic Laser Absorption Imaging of Atomic Potassium during Combustion of Potassium Chloride Salt and Biomass.

Gaseous potassium (K) species play an important role in biomass combustion processes, and imaging techniques are powerful tools to investigate the related gas-phase chemistry. Here, laser absorption imaging of gaseous atomic K in flames is implemented using tunable diode laser absorption spectroscopy at 769.9 nm and a high-speed complementary metal oxide semiconductor (CMOS) camera recording at 30 kfps. Atomic K absorption spectra are acquired for each camera pixel in a field of view of 28 × 28 mm at a rate of 100 Hz. The technique is used to determine the spatial distribution of atomic K concentration during the conversion of potassium chloride (KCl) salt and wheat straw particles in a laminar premixed CH4/air flame with an image pixel resolution of up to 120 µm. Due to axisymmetry in setup geometry and, consequently, atomic K distributions, the radial atomic K concentration fields could be reconstructed by one-dimensional tomography. For the KCl sample, the K concentration field was in excellent agreement with previous point measurements. In the case of wheat straw, atomic K concentrations of around 3 ppm were observed in a cylindrical flame during devolatilization. In the char conversion phase, a spherical layer of atomic K, with concentrations reaching 25 ppm, was found within 5 mm of the particle surface, while the concentration rapidly decreased to sub-ppm levels along the vertical axis. In both cases, a thin (∼1 mm) layer without any atomic K was observed in close vicinity to the particle, suggesting that the potassium was initially not released in its atomic form.

The endogenous cellular protease inhibitor SPINT2 controls SARS-CoV-2 viral infection and is associated to disease severity.

COVID-19 outbreak is the biggest threat to human health in recent history. Currently, there are over 1.5 million related deaths and 75 million people infected around the world (as of 22/12/2020). The identification of virulence factors which determine disease susceptibility and severity in different cell types remains an essential challenge. The serine protease TMPRSS2 has been shown to be important for S protein priming and viral entry, however, little is known about its regulation. SPINT2 is a member of the family of Kunitz type serine protease inhibitors and has been shown to inhibit TMPRSS2. Here, we explored the existence of a co-regulation between SPINT2/TMPRSS2 and found a tightly regulated protease/inhibitor expression balance across tissues. We found that SPINT2 negatively correlates with SARS-CoV-2 expression in Calu-3 and Caco-2 cell lines and was down-regulated in secretory cells from COVID-19 patients. We validated our findings using Calu-3 cell lines and observed a strong increase in viral load after SPINT2 knockdown, while overexpression lead to a drastic reduction of the viral load. Additionally, we evaluated the expression of SPINT2 in datasets from comorbid diseases using bulk and scRNA-seq data. We observed its down-regulation in colon, kidney and liver tumors as well as in alpha pancreatic islets cells from diabetes Type 2 patients, which could have implications for the observed comorbidities in COVID-19 patients suffering from chronic diseases.

Impact of in vitro phytohormone treatments on the metabolome of the leafy liverwort Radula complanata (L.) Dumort.

INTRODUCTION: Liverworts are a group of non-vascular plants that possess unique metabolism not found in other plants. Many liverwort metabolites have interesting structural and biochemical characteristics, however the fluctuations of these metabolites in response to stressors is largely unknown. OBJECTIVES: To investigate the metabolic stress-response of the leafy liverwort Radula complanata. METHODS: Five phytohormones were applied exogenously to in vitro cultured R. complanata and an untargeted metabolomic analysis was conducted. Compound classification and identification was performed with CANOPUS and SIRIUS while statistical analyses including PCA, ANOVA, and variable selection using BORUTA were conducted to identify metabolic shifts. RESULTS: It was found that R. complanata was predominantly composed of carboxylic acids and derivatives, followed by benzene and substituted derivatives, fatty acyls, organooxygen compounds, prenol lipids, and flavonoids. The PCA revealed that samples grouped based on the type of hormone applied, and the variable selection using BORUTA (Random Forest) revealed 71 identified and/or classified features that fluctuated with phytohormone application. The stress-response treatments largely reduced the production of the selected primary metabolites while the growth treatments resulted in increased production of these compounds. 4-(3-Methyl-2-butenyl)-5-phenethylbenzene-1,3-diol was identified as a biomarker for the growth treatments while GDP-hexose was identified as a biomarker for the stress-response treatments. CONCLUSION: Exogenous phytohormone application caused clear metabolic shifts in Radula complanata that deviate from the responses of vascular plants. Further identification of the selected metabolite features can reveal metabolic biomarkers unique to liverworts and provide more insight into liverwort stress responses.

Integrative multi-omics landscape of fluoxetine action across 27 brain regions reveals global increase in energy metabolism and region-specific chromatin remodelling.

Depression and anxiety are major global health burdens. Although SSRIs targeting the serotonergic system are prescribed over 200 million times annually, they have variable therapeutic efficacy and side effects, and mechanisms of action remain incompletely understood. Here, we comprehensively characterise the molecular landscape of gene regulatory changes associated with fluoxetine, a widely-used SSRI. We performed multimodal analysis of SSRI response in 27 mammalian brain regions using 310 bulk RNA-seq and H3K27ac ChIP-seq datasets, followed by in-depth characterisation of two hippocampal regions using single-cell RNA-seq (20 datasets). Remarkably, fluoxetine induced profound region-specific shifts in gene expression and chromatin state, including in the nucleus accumbens shell, locus coeruleus and septal areas, as well as in more well-studied regions such as the raphe and hippocampal dentate gyrus. Expression changes were strongly enriched at GWAS loci for depression and antidepressant drug response, stressing the relevance to human phenotypes. We observed differential expression at dozens of signalling receptors and pathways, many of which are previously unknown. Single-cell analysis revealed stark differences in fluoxetine response between the dorsal and ventral hippocampal dentate gyri, particularly in oligodendrocytes, mossy cells and inhibitory neurons. Across diverse brain regions, integrative omics analysis consistently suggested increased energy metabolism via oxidative phosphorylation and mitochondrial changes, which we corroborated in vitro; this may thus constitute a shared mechanism of action of fluoxetine. Similarly, we observed pervasive chromatin remodelling signatures across the brain. Our study reveals unexpected regional and cell type-specific heterogeneity in SSRI action, highlights under-studied brain regions that may play a major role in antidepressant response, and provides a rich resource of candidate cell types, genes, gene regulatory elements and pathways for mechanistic analysis and identifying new therapeutic targets for depression and anxiety.

Integrative analysis of epigenetics data identifies gene-specific regulatory elements.

Understanding how epigenetic variation in non-coding regions is involved in distal gene-expression regulation is an important problem. Regulatory regions can be associated to genes using large-scale datasets of epigenetic and expression data. However, for regions of complex epigenomic signals and enhancers that regulate many genes, it is difficult to understand these associations. We present StitchIt, an approach to dissect epigenetic variation in a gene-specific manner for the detection of regulatory elements (REMs) without relying on peak calls in individual samples. StitchIt segments epigenetic signal tracks over many samples to generate the location and the target genes of a REM simultaneously. We show that this approach leads to a more accurate and refined REM detection compared to standard methods even on heterogeneous datasets, which are challenging to model. Also, StitchIt REMs are highly enriched in experimentally determined chromatin interactions and expression quantitative trait loci. We validated several newly predicted REMs using CRISPR-Cas9 experiments, thereby demonstrating the reliability of StitchIt. StitchIt is able to dissect regulation in superenhancers and predicts thousands of putative REMs that go unnoticed using peak-based approaches suggesting that a large part of the regulome might be uncharted water.

RCA2: a scalable supervised clustering algorithm that reduces batch effects in scRNA-seq data.

The transcriptomic diversity of cell types in the human body can be analysed in unprecedented detail using single cell (SC) technologies. Unsupervised clustering of SC transcriptomes, which is the default technique for defining cell types, is prone to group cells by technical, rather than biological, variation. Compared to de-novo (unsupervised) clustering, we demonstrate using multiple benchmarks that supervised clustering, which uses reference transcriptomes as a guide, is robust to batch effects and data quality artifacts. Here, we present RCA2, the first algorithm to combine reference projection (batch effect robustness) with graph-based clustering (scalability). In addition, RCA2 provides a user-friendly framework incorporating multiple commonly used downstream analysis modules. RCA2 also provides new reference panels for human and mouse and supports generation of custom panels. Furthermore, RCA2 facilitates cell type-specific QC, which is essential for accurate clustering of data from heterogeneous tissues. We demonstrate the advantages of RCA2 on SC data from human bone marrow, healthy PBMCs and PBMCs from COVID-19 patients. Scalable supervised clustering methods such as RCA2 will facilitate unified analysis of cohort-scale SC datasets.

[Recommendations of the S3 Guideline "Use of Extracorporeal Circulation (ECLS/ ECMO) for Cardiac and Circulatory Failure" of the Association of Scientific Medical Societies in Germany]. / Empfehlungen der S3-Leitlinie (AWMF) "Einsatz der extrakorporalen Zirkulation (ECLS/ECMO) bei Herz- und Kreislaufversagen".

In recent years, the use of mechanical support for patients with cardiac or circulatory failure has continuously increased, leading to 3,000 ECLS/ECMO (extracorporeal life support/extracorporeal membrane oxygenation) implantations annually in Germany. Due to the lack of guidelines, there is an urgent need for evidence-based recommendations addressing the central aspects of ECLS/ECMO therapy. In July 2015, the generation of a guideline level S3 according to the standards of the Association of the Scientific Medical Societies in Germany (AWMF) was announced by the German Society for Thoracic and Cardiovascular Surgery (GSTCVS). In a well-structured consensus process, involving experts from Germany, Austria and Switzerland, delegated by 16 scientific societies and the patients' representation, the guideline "Use of extracorporeal circulation (ECLS/ECMO) for cardiac and circulatory failure" was created under guidance of the GSTCVS, and published in February 2021. The guideline focuses on clinical aspects of initiation, continuation, weaning and aftercare, herein also addressing structural and economic issues. This article presents an overview on the methodology as well as the final recommendations.

Recessive NLRC4-Autoinflammatory Disease Reveals an Ulcerative Colitis Locus.

PURPOSE: NLRC4-associated autoinflammatory disease (NLRC4-AID) is an autosomal dominant condition presenting with a range of clinical manifestations which can include macrophage activation syndrome (MAS) and severe enterocolitis. We now report the first homozygous mutation in NLRC4 (c.478G > A, p.A160T) causing autoinflammatory disease with immune dysregulation and find that heterozygous carriers in the general population are at increased risk of developing ulcerative colitis. METHODS: Circulating immune cells and inflammatory markers were profiled and historical clinical data interrogated. DNA was extracted and sequenced using standard procedures. Inflammasome activation assays for ASC speck formation, pyroptosis, and IL-1ß/IL-18 secretion confirmed pathogenicity of the mutation in vitro. Genome-wide association of NLRC4 (A160T) with ulcerative colitis was examined using data from the IBD exomes portal. RESULTS: A 60-year-old Brazilian female patient was evaluated for recurrent episodes of systemic inflammation from six months of age. Episodes were characterized by recurrent low-grade fever, chills, oral ulceration, uveitis, arthralgia, and abdominal pain, followed by diarrhea with mucus and variable skin rash. High doses of corticosteroids were somewhat effective in controlling disease and anti-IL-1ß therapy partially controlled symptoms. While on treatment, serum IL-1ß and IL-18 levels remained elevated. Genetic investigations identified a homozygous mutation in NLRC4 (A160T), inherited in a recessive fashion. Increased ASC speck formation and IL-1ß/IL-18 secretion confirmed pathogenicity when NLRC4 (A160T) was analyzed in human cell lines. This allele is significantly enriched in patients with ulcerative colitis: OR 2.546 (95% 1.778-3.644), P = 0.01305. CONCLUSION: NLRC4 (A160T) can either cause recessively inherited autoinflammation and immune dysregulation, or function as a heterozygous risk factor for the development of ulcerative colitis.