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The transcriptomic classification of primary colorectal cancer (CRC) into distinct consensus molecular subtypes (CMSs) is a well‐described strategy for patient stratification. However, the molecular nature of CRC metastases remains poorly investigated. To this end, this study aimed to identify and compare organotropic CMS frequencies in CRC liver and brain metastases. Compared to reported CMS frequencies in primary CRC, liver metastases from CRC patients were CMS4‐enriched and CMS3‐depleted, whereas brain metastases mainly clustered as CMS3 and rarely as CMS4. Regarding overall survival rates, CMS4 was the most favorable subtype for patients with hepatic lesions, followed by CMS1 and CMS2. The survival of patients with brain metastases did not correlate with CMS. However, we identified a CMS3‐related metabolic gene signature, specifically upregulated in central nervous system (CNS)‐infiltrating CRC, as a negative prognostic marker and potential tumor progressor. In summary, subtyping of CRC metastases revealed an organotropic CMS distribution in liver and brain with impact on patient survival. CNS‐infiltrating CRC samples were enriched for CMS3 and predictive metabolic biomarkers, suggesting metabolic dysregulation of CRC cells as a prerequisite for metastatic colonization of the brain. Colorectal cancer (CRC) metastases in liver and brain exhibited organ‐specific frequencies of consensus molecular subtypes (CMS). In terms of overall survival, CMS4 was the most beneficial subtype for patients with CRC metastases in the liver. Brain metastases were enriched for the metabolic subtype (CMS3) and certain metabolic markers that correlated with a poor overall survival of CRC patients.

Elemental stoichiometry constitutes an inherent link between biogeochemistry and the structure and processes within food webs, and thus is at the core of ecosystem functioning. Stoichiometry allows for spanning different levels of biological organization, from cellular metabolism to ecosystem structure and nutrient cycling, and is therefore particularly useful for establishing links between different ecosystem compartments. We review elemental carbon : nitrogen : phosphorus (C:N:P) ratios in terrestrial ecosystems (from vegetation, leaf litter, woody debris, and dead roots, to soil microbes and organic matter). While the stoichiometry of the plant, litter, and soil compartments of ecosystems is well understood, heterotrophic microbial communities, which dominate the soil food web and drive nutrient cycling, have received increasing interest in recent years. This review highlights the effects of resource stoichiometry on soil microorganisms and decomposition, specifically on the structure and function of heterotrophic microbial communities and suggests several general patterns. First, latitudinal gradients of soil and litter stoichiometry are reflected in microbial community structure and function. Second, resource stoichiometry may cause changes in microbial interactions and community dynamics that lead to feedbacks in nutrient availability. Third, global change alters the C:N, C:P, and N:P ratios of primary producers, with repercussions for microbial decomposer communities and critical ecosystem services such as soil fertility. We argue that ecological stoichiometry provides a framework to analyze and predict such global change effects at various scales.

Single-cell open chromatin profiling via scATAC-seq has become a mainstream measurement of open chromatin in single-cells. Here we present epiAneufinder, an algorithm that exploits the read count information from scATAC-seq data to extract genome-wide copy number alterations (CNAs) for individual cells, allowing the study of CNA heterogeneity present in a sample at the single-cell level. Using different cancer scATAC-seq datasets, we show that epiAneufinder can identify intratumor clonal heterogeneity in populations of single cells based on their CNA profiles. We demonstrate that these profiles are concordant with the ones inferred from single-cell whole genome sequencing data for the same samples. EpiAneufinder allows the inference of single-cell CNA information from scATAC-seq data, without the need of additional experiments, unlocking a layer of genomic variation which is otherwise unexplored. 'Here the authors present epiAneufinder, an algorithm for the identification of single-cell copy number alterations from scATAC-seq data, and explore the clonal heterogeneity in cell populations.

Microbial nitrogen use efficiency (NUE) describes the partitioning of organic N taken up between growth and the release of inorganic N to the environment (that is, N mineralization), and is thus central to our understanding of N cycling. Here we report empirical evidence that microbial decomposer communities in soil and plant litter regulate their NUE. We find that microbes retain most immobilized organic N (high NUE), when they are N limited, resulting in low N mineralization. However, when the metabolic control of microbial decomposers switches from N to C limitation, they release an increasing fraction of organic N as ammonium (low NUE). We conclude that the regulation of NUE is an essential strategy of microbial communities to cope with resource imbalances, independent of the regulation of microbial carbon use efficiency, with significant effects on terrestrial N cycling. Nitrogen availability in soils is predominantly controlled by microorganisms, yet our understanding of their organic nitrogen use is limited. Mooshammer et al. show that microbial nitrogen use efficiency is dependent on resource stoichiometry and substrate type.

Copy number variations (CNVs), the gain or loss of genomic regions, are associated with disease, especially cancer. Single cell technologies offer new possibilities to capture within-sample heterogeneity of CNVs and identify subclones relevant for tumor progression and treatment outcome. Several computational tools have been developed to identify CNVs from scRNA-seq data. However, an independent benchmarking of them is lacking. Here, we evaluate six popular methods in their ability to correctly identify ground truth CNVs, euploid cells and subclonal structures in 21 scRNA-seq datasets. We discover dataset-specific factors influencing the performance, including dataset size, the number and type of CNVs in the sample and the choice of the reference dataset. Methods which include allelic information perform more robustly for large droplet-based datasets, but require higher runtime. Furthermore, the methods differ in their additional functionalities. We offer a benchmarking pipeline to identify the optimal method for new datasets, and improve methods’ performance. Several computational tools have now been developed to identify copy number variations (CNVs) from scRNA-seq data. Here authors benchmark these methods, showing that performance is affected by dataset quality, CNV type and reference dataset, with methods including allelic information being more robust in large datasets.

Resource stoichiometry (C:N:P) is an important determinant of litter decomposition. However, the effect of elemental stoichiometry on the gross rates of microbial N and P cycling processes during litter decomposition is unknown. In a mesocosm experiment, beech ( Fagus sylvatica L.) litter with natural differences in elemental stoichiometry (C:N:P) was incubated under constant environmental conditions. After three and six months, we measured various aspects of nitrogen and phosphorus cycling. We found that gross protein depolymerization, N mineralization (ammonification), and nitrification rates were negatively related to litter C:N. Rates of P mineralization were negatively correlated with litter C:P. The negative correlations with litter C:N were stronger for inorganic N cycling processes than for gross protein depolymerization, indicating that the effect of resource stoichiometry on intracellular processes was stronger than on processes catalyzed by extracellular enzymes. Consistent with this, extracellular protein depolymerization was mainly limited by substrate availability and less so by the amount of protease. Strong positive correlations between the interconnected N and P pools and the respective production and consumption processes pointed to feed-forward control of microbial litter N and P cycling. A negative relationship between litter C:N and phosphatase activity (and between litter C:P and protease activity) demonstrated that microbes tended to allocate carbon and nutrients in ample supply into the production of extracellular enzymes to mine for the nutrient that is more limiting. Overall, the study demonstrated a strong effect of litter stoichiometry (C:N:P) on gross processes of microbial N and P cycling in decomposing litter; mineralization of N and P were tightly coupled to assist in maintaining cellular homeostasis of litter microbial communities.

Delirium is recognized as a severe complication of coronavirus-disease-2019 (COVID-19). COVID-19-associated delirium has been linked to worse patient outcomes and is considered to be of multifactorial origin. Here we sought to evaluate the incidence and risk factors of delirium in hospitalized COVID-19 patients, along with its impact on clinical outcome. Consecutive adult COVID-19 patients admitted to a tertiary academic referral hospital between March 1st and December 31st, 2020 were included. Potential risk factors for delirium were evaluated, including: age, gender, disease severity (as per the highest WHO grading reached during admission), laboratory parameters for infection and renal function (as per their most extreme values), and presence of comorbidities. To assess the relative strength of risk factors for predicting the occurrence of delirium, we performed a random-forest survival analysis. 347 patients with positive COVID-19 PCR test and median age 68.2 [IQR 55.5, 80.5] years were included. Of those, 79 patients (22.8%) developed delirium, 81 (23.3%) were transferred to ICU, 58 (16.7%) died. 163 (73.8%) patients were discharged home, 13 (5.9%) to another hospital, 32 (14.5%) to nursing homes, 13 (5.9%) to rehabilitation with an overall median admission-to-discharge time of 53 [IQR 14, 195] days. The strongest predictors for the occurrence of delirium were blood urea nitrogen (minimal depth value (MD): 3.33), age (MD: 3.75), disease severity (as captured by WHO grading; MD: 3.93), leukocyte count (MD: 4.22), the presence of a neurodegenerative history (MD: 4.43), ferritin (MD: 4.46) and creatinine (MD: 4.59) levels. The risk of delirium in COVID-19 can be stratified based on COVID-19 disease severity and-similar to delirium associated with other respiratory infections-the factors advanced age, neurodegenerative disease history, and presence of elevated infection and renal-retention parameters. Screening for these risk factors may facilitate early identification of patients at high-risk for COVID-19-associated delirium.

While Early Live Adversity (ELA) is a known risk factor for mental and physical diseases, the investigation into the mechanisms behind this connection is ongoing. In the present study, we investigated whether ELA blunts the relaxation response in healthy adults. Using a within-subjects design, we employed a paced breathing exercise (four seconds inhale, six seconds exhale) and a 360° nature video as relaxation interventions while measuring physiological relaxation using heart rate variability and subjective relaxation using the Relaxation State Questionnaire. A total of 103 participants (63.11% female; age mean  = 22.73 ± 3.43 years) completed the Parental Bonding Instrument and the Childhood Trauma Questionnaire to assess ELA retrospectively. For subjective relaxation, a blunted relaxation reaction was associated with lower scores of paternal care and higher scores of paternal overprotection, physical abuse, physical neglect, and emotional abuse. For heart rate variability emotional abuse in interaction with nicotine consumption was related to a blunted relaxation response. This indicates that experiencing ELA negatively affects the relaxation capability in a healthy sample and emphasizes the importance of assessing relaxation at a physiological and subjective level.

A hallmark of obesity is a pathological expansion of white adipose tissue (WAT), accompanied by marked tissue dysfunction and fibrosis. Autophagy promotes adipocyte differentiation and lipid homeostasis, but its role in obese adipocytes and adipose tissue dysfunction remains incompletely understood. Using a mouse model, we demonstrate that autophagy is a key tissue-specific regulator of WAT remodelling in diet-induced obesity. Importantly, loss of adipocyte autophagy substantially exacerbates pericellular fibrosis in visceral WAT. Change in WAT architecture correlates with increased infiltration of macrophages with tissue-reparative, fibrotic features. We uncover that autophagy restrains purine nucleoside metabolism in obese adipocytes. This ultimately leads to a reduced release of the purine catabolites xanthine and hypoxanthine. Purines signal cell-extrinsically for fibrosis by driving macrophage polarisation towards a tissue reparative phenotype. Our findings in mice reveal a role for adipocyte autophagy in regulating tissue purine nucleoside metabolism, thereby limiting obesity-associated fibrosis and maintaining the functional integrity of visceral WAT. Purine signals may serve as a critical balance checkpoint and therapeutic target in fibrotic diseases. The study shows that autophagy in fat cells protects against obesity-induced fibrosis. Autophagy limits the release of purines, a metabolic product, that signals to immune cells to initiate the fibrosis. Purines might be a potential target for reducing tissue fibrosis.

SNURPORTIN-1, encoded by SNUPN , plays a central role in the nuclear import of spliceosomal small nuclear ribonucleoproteins. However, its physiological function remains unexplored. In this study, we investigate 18 children from 15 unrelated families who present with atypical muscular dystrophy and neurological defects. Nine hypomorphic SNUPN biallelic variants, predominantly clustered in the last coding exon, are ascertained to segregate with the disease. We demonstrate that mutant SPN1 failed to oligomerize leading to cytoplasmic aggregation in patients’ primary fibroblasts and CRISPR/Cas9-mediated mutant cell lines. Additionally, mutant nuclei exhibit defective spliceosomal maturation and breakdown of Cajal bodies. Transcriptome analyses reveal splicing and mRNA expression dysregulation, particularly in sarcolemmal components, causing disruption of cytoskeletal organization in mutant cells and patient muscle tissues. Our findings establish SNUPN deficiency as the genetic etiology of a previously unrecognized subtype of muscular dystrophy and provide robust evidence of the role of SPN1 for muscle homeostasis. SNURPORTIN-1, encoded by the SNUPN gene, plays a key role in the nuclear import of spliceosomal small nuclear ribonucleoproteins, however its physiological function remains unclear. Here the authors report that recessive SNUPN mutations cause a distinct subtype of childhood muscular dystrophy and reveal SNURPORTIN-1’s role in muscle homeostasis, offering insights for new therapeutic strategies.