ISG15 blocks cardiac glycolysis and ensures sufficient mitochondrial energy production during Coxsackievirus B3 infection

AIMS

Virus infection triggers inflammation and, may impose nutrient shortage to the heart. Supported by type I interferon (IFN) signalling, cardiomyocytes counteract infection by various effector processes, with the IFN-stimulated gene of 15 kDa (ISG15) system being intensively regulated and protein modification with ISG15 protecting mice Coxsackievirus B3 (CVB3) infection. The underlying molecular aspects how the ISG15 system affects the functional properties of respective protein substrates in the heart are unknown.

METHODS AND RESULTS

Based on the protective properties due to protein ISGylation, we set out a study investigating CVB3-infected mice in depth and found cardiac atrophy with lower cardiac output in ISG15-/- mice. By mass spectrometry, we identified the protein targets of the ISG15 conjugation machinery in heart tissue and explored how ISGylation affects their function. The cardiac ISGylome showed a strong enrichment of ISGylation substrates within glycolytic metabolic processes. Two control enzymes of the glycolytic pathway, hexokinase 2 (HK2) and phosphofructokinase muscle form (PFK1), were identified as bona fide ISGylation targets during infection. In an integrative approach complemented with enzymatic functional testing and structural modelling, we demonstrate that protein ISGylation obstructs the activity of HK2 and PFK1. Seahorse-based investigation of glycolysis in cardiomyocytes revealed that, by conjugating proteins, the ISG15 system prevents the infection-/IFN-induced up-regulation of glycolysis. We complemented our analysis with proteomics-based advanced computational modelling of cardiac energy metabolism. Our calculations revealed an ISG15-dependent preservation of the metabolic capacity in cardiac tissue during CVB3 infection. Functional profiling of mitochondrial respiration in cardiomyocytes and mouse heart tissue by Seahorse technology showed an enhanced oxidative activity in cells with a competent ISG15 system.

CONCLUSION

Our study demonstrates that ISG15 controls critical nodes in cardiac metabolism. ISG15 reduces the glucose demand, supports higher ATP production capacity in the heart, despite nutrient shortage in infection, and counteracts cardiac atrophy and dysfunction.

Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast

Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level. While the protein coexpression network recapitulates major biological functions, differential expression patterns reveal proteomic signatures related to specific populations. Comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3%). Our results demonstrate that transcriptome and proteome are governed by distinct genetic bases, likely explained by protein turnover. It also highlights the importance of integrating these different levels of gene expression to better understand the genotype-phenotype relationship.

SARS-CoV-2 tropism to intestinal but not gastric epithelial cells is defined by limited ACE2 expression

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection primarily affects the lung but can also cause gastrointestinal (GI) symptoms. In vitro experiments confirmed that SARS-CoV-2 robustly infects intestinal epithelium. However, data on infection of adult gastric epithelium are sparse and a side-by-side comparison of the infection in the major segments of the GI tract is lacking. We provide this direct comparison in organoid-derived monolayers and demonstrate that SARS-CoV-2 robustly infects intestinal epithelium, while gastric epithelium is resistant to infection. RNA sequencing and proteome analysis pointed to angiotensin-converting enzyme 2 (ACE2) as a critical factor, and, indeed, ectopic expression of ACE2 increased susceptibility of gastric organoid-derived monolayers to SARS-CoV-2. ACE2 expression pattern in GI biopsies of patients mirrors SARS-CoV-2 infection levels in monolayers. Thus, local ACE2 expression limits SARS-CoV-2 expression in the GI tract to the intestine, suggesting that the intestine, but not the stomach, is likely to be important in viral replication and possibly transmission.

The metabolic domestication syndrome of budding yeast

Cellular metabolism evolves through changes in the structure and quantitative states of metabolic networks. Here, we explore the evolutionary dynamics of metabolic states by focusing on the collection of metabolite levels, the metabolome, which captures key aspects of cellular physiology. Using a phylogenetic framework, we profiled metabolites in 27 populations of nine budding yeast species, providing a graduated view of metabolic variation across multiple evolutionary time scales. Metabolite levels evolve more rapidly and independently of changes in the metabolic network's structure, providing complementary information to enzyme repertoire. Although metabolome variation accumulates mainly gradually over time, it is profoundly affected by domestication. We found pervasive signatures of convergent evolution in the metabolomes of independently domesticated clades of Saccharomyces cerevisiae. Such recurring metabolite differences between wild and domesticated populations affect a substantial part of the metabolome, including rewiring of the TCA cycle and several amino acids that influence aroma production, likely reflecting adaptation to human niches. Overall, our work reveals previously unrecognized diversity in central metabolism and the pervasive influence of human-driven selection on metabolite levels in yeasts.

Proteomic and transcriptomic profiling of brainstem, cerebellum and olfactory tissues in early- and late-phase COVID-19

Neurological symptoms, including cognitive impairment and fatigue, can occur in both the acute infection phase of coronavirus disease 2019 (COVID-19) and at later stages, yet the mechanisms that contribute to this remain unclear. Here we profiled single-nucleus transcriptomes and proteomes of brainstem tissue from deceased individuals at various stages of COVID-19. We detected an inflammatory type I interferon response in acute COVID-19 cases, which resolves in the late disease phase. Integrating single-nucleus RNA sequencing and spatial transcriptomics, we could localize two patterns of reaction to severe systemic inflammation, one neuronal with a direct focus on cranial nerve nuclei and a separate diffuse pattern affecting the whole brainstem. The latter reflects a bystander effect of the respiratory infection that spreads throughout the vascular unit and alters the transcriptional state of mainly oligodendrocytes, microglia and astrocytes, while alterations of the brainstem nuclei could reflect the connection of the immune system and the central nervous system via, for example, the vagus nerve. Our results indicate that even without persistence of severe acute respiratory syndrome coronavirus 2 in the central nervous system, local immune reactions are prevailing, potentially causing functional disturbances that contribute to neurological complications of COVID-19.

Oxonium ion scanning mass spectrometry for large-scale plasma glycoproteomics

Protein glycosylation, a complex and heterogeneous post-translational modification that is frequently dysregulated in disease, has been difficult to analyse at scale. Here we report a data-independent acquisition technique for the large-scale mass-spectrometric quantification of glycopeptides in plasma samples. The technique, which we named 'OxoScan-MS', identifies oxonium ions as glycopeptide fragments and exploits a sliding-quadrupole dimension to generate comprehensive and untargeted oxonium ion maps of precursor masses assigned to fragment ions from non-enriched plasma samples. By applying OxoScan-MS to quantify 1,002 glycopeptide features in the plasma glycoproteomes from patients with COVID-19 and healthy controls, we found that severe COVID-19 induces differential glycosylation in IgA, haptoglobin, transferrin and other disease-relevant plasma glycoproteins. OxoScan-MS may allow for the quantitative mapping of glycoproteomes at the scale of hundreds to thousands of samples.

Monogenic Disorders of ROS Production and the Primary Anti-Oxidative Defense

Oxidative stress, characterized by an imbalance between the production of reactive oxygen species (ROS) and the cellular anti-oxidant defense mechanisms, plays a critical role in the pathogenesis of various human diseases. Redox metabolism, comprising a network of enzymes and genes, serves as a crucial regulator of ROS levels and maintains cellular homeostasis. This review provides an overview of the most important human genes encoding for proteins involved in ROS generation, ROS detoxification, and production of reduced nicotinamide adenine dinucleotide phosphate (NADPH), and the genetic disorders that lead to dysregulation of these vital processes. Insights gained from studies on inherited monogenic metabolic diseases provide valuable basic understanding of redox metabolism and signaling, and they also help to unravel the underlying pathomechanisms that contribute to prevalent chronic disorders like cardiovascular disease, neurodegeneration, and cancer.

Fast proteomics with dia-PASEF and analytical flow-rate chromatography

Increased throughput in proteomic experiments can improve accessibility of proteomic platforms, reduce costs, and facilitate new approaches in systems biology and biomedical research. Here we propose combination of analytical flow rate chromatography with ion mobility separation of peptide ions, data-independent acquisition, and data analysis with the DIA-NN software suite, to achieve high-quality proteomic experiments from limited sample amounts, at a throughput of up to 400 samples per day. For instance, when benchmarking our workflow using a 500-μL/min flow rate and 3-min chromatographic gradients, we report the quantification of 5211 proteins from 2 μg of a mammalian cell-line standard at high quantitative accuracy and precision. We further used this platform to analyze blood plasma samples from a cohort of COVID-19 inpatients, using a 3-min chromatographic gradient and alternating column regeneration on a dual pump system. The method delivered a comprehensive view of the COVID-19 plasma proteome, allowing classification of the patients according to disease severity and revealing plasma biomarker candidates.

Metabolic exchanges are ubiquitous in natural microbial communities

Microbial communities drive global biogeochemical cycles and shape the health of plants and animals-including humans. Their structure and function are determined by ecological and environmental interactions that govern the assembly, stability and evolution of microbial communities. A widely held view is that antagonistic interactions such as competition predominate in microbial communities and are ecologically more important than synergistic interactions-for example, mutualism or commensalism. Over the past decade, however, a more nuanced picture has emerged, wherein bacteria, archaea and fungi exist within interactive networks in which they exchange essential and non-essential metabolites. These metabolic interactions profoundly impact not only the physiology, ecology and evolution of the strains involved, but are also central to the functioning of many, if not all, microbiomes. Therefore, we advocate for a balanced view of microbiome ecology that encompasses both synergistic and antagonistic interactions as key forces driving the structure and dynamics within microbial communities.

90K/LGALS3BP expression is upregulated in COVID-19 but may not restrict SARS-CoV-2 infection

Glycoprotein 90K, encoded by the interferon-stimulated gene LGALS3BP, displays broad antiviral activity. It reduces HIV-1 infectivity by interfering with Env maturation and virion incorporation, and increases survival of Influenza A virus-infected mice via antiviral innate immune signaling. Its antiviral potential in SARS-CoV-2 infection remains largely unknown. Here, we analyzed the expression of 90K/LGALS3BP in 44 hospitalized COVID-19 patients at multiple levels. We quantified 90K protein concentrations in serum and PBMCs as well as LGALS3BP mRNA levels. Complementary, we analyzed two single cell RNA-sequencing datasets for expression of LGALS3BP in respiratory specimens and PBMCs from COVID-19 patients. Finally, we analyzed the potential of 90K to interfere with SARS-CoV-2 infection of HEK293T/ACE2, Calu-3 and Caco-2 cells using authentic virus. 90K protein serum concentrations were significantly elevated in COVID-19 patients compared to uninfected sex- and age-matched controls. Furthermore, PBMC-associated concentrations of 90K protein were overall reduced by SARS-CoV-2 infection in vivo, suggesting enhanced secretion into the extracellular space. Mining of published PBMC scRNA-seq datasets uncovered monocyte-specific induction of LGALS3BP mRNA expression in COVID-19 patients. In functional assays, neither 90K overexpression in susceptible cell lines nor exogenous addition of purified 90K consistently inhibited SARS-CoV-2 infection. Our data suggests that 90K/LGALS3BP contributes to the global type I IFN response during SARS-CoV-2 infection in vivo without displaying detectable antiviral properties in vitro.

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

INTRODUCTION

The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures.

METHODS

In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025.

FINDINGS

Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2-6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5-5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4-10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32-4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23-11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation.

INTERPRETATION

After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification.

FUNDING

UK Research and Innovation and National Institute for Health Research.

Interkingdom interactions between Pseudomonas aeruginosa and Candida albicans affect clinical outcomes and antimicrobial responses

Infections that involve interkingdom microbial communities, such as those between bacteria and yeast pathogens, are difficult to treat, associated with worse patient outcomes, and may be a source of antimicrobial resistance. In this review, we address co-occurrence and co-infections of Candida albicans and Pseudomonas aeruginosa, two pathogens that occupy multiple infection niches in the human body, especially in immunocompromised patients. The interaction between the pathogen species influences microbe-host interactions, the effectiveness of antimicrobials and even infection outcomes, and may thus require adapted treatment strategies. However, the molecular details of bacteria-fungal interactions both inside and outside the infection sites, are insufficiently characterised. We argue that comprehensively understanding the P. aeruginosa-C. albicans interaction network through integrated systems biology approaches will capture the highly dynamic and complex nature of these polymicrobial infections and lead to a more comprehensive understanding of clinical observations such as reshaped immune defences and low antimicrobial treatment efficacy.

Addressing Global Environmental Challenges to Mental Health Using Population Neuroscience: A Review

Importance

Climate change, pollution, urbanization, socioeconomic inequality, and psychosocial effects of the COVID-19 pandemic have caused massive changes in environmental conditions that affect brain health during the life span, both on a population level as well as on the level of the individual. How these environmental factors influence the brain, behavior, and mental illness is not well known.

Observations

A research strategy enabling population neuroscience to contribute to identify brain mechanisms underlying environment-related mental illness by leveraging innovative enrichment tools for data federation, geospatial observation, climate and pollution measures, digital health, and novel data integration techniques is described. This strategy can inform innovative treatments that target causal cognitive and molecular mechanisms of mental illness related to the environment. An example is presented of the environMENTAL Project that is leveraging federated cohort data of over 1.5 million European citizens and patients enriched with deep phenotyping data from large-scale behavioral neuroimaging cohorts to identify brain mechanisms related to environmental adversity underlying symptoms of depression, anxiety, stress, and substance misuse.

Conclusions and Relevance

This research will lead to the development of objective biomarkers and evidence-based interventions that will significantly improve outcomes of environment-related mental illness.

Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast

Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level. While the protein co-expression network recapitulates major biological functions, differential expression patterns reveal proteomic signatures related to specific populations. Comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3.6%). Our results demonstrate that transcriptome and proteome are governed by distinct genetic bases, likely explained by protein turnover. It also highlights the importance of integrating these different levels of gene expression to better understand the genotype-phenotype relationship.

Highlights

At the level of individual genes, the abundance of transcripts and proteins is weakly correlated within a species ( ρ = 0.165). While the proteome is not imprinted by population structure, co-expression patterns recapitulate the cellular functional landscapeWild populations exhibit a higher abundance of respiration-related proteins compared to domesticated populationsLoci that influence protein abundance differ from those that impact transcript levels, likely because of protein turnover.

Cystatin C is glucocorticoid responsive, directs recruitment of Trem2+ macrophages, and predicts failure of cancer immunotherapy

Cystatin C (CyC), a secreted cysteine protease inhibitor, has unclear biological functions. Many patients exhibit elevated plasma CyC levels, particularly during glucocorticoid (GC) treatment. This study links GCs with CyC's systemic regulation by utilizing genome-wide association and structural equation modeling to determine CyC production genetics in the UK Biobank. Both CyC production and a polygenic score (PGS) capturing predisposition to CyC production were associated with increased all-cause and cancer-specific mortality. We found that the GC receptor directly targets CyC, leading to GC-responsive CyC secretion in macrophages and cancer cells. CyC-knockout tumors displayed significantly reduced growth and diminished recruitment of TREM2+ macrophages, which have been connected to cancer immunotherapy failure. Furthermore, the CyC-production PGS predicted checkpoint immunotherapy failure in 685 patients with metastatic cancer from combined clinical trial cohorts. In conclusion, CyC may act as a GC effector pathway via TREM2+ macrophage recruitment and may be a potential target for combination cancer immunotherapy.

The pentose phosphate pathway in health and disease

The pentose phosphate pathway (PPP) is a glucose-oxidizing pathway that runs in parallel to upper glycolysis to produce ribose 5-phosphate and nicotinamide adenine dinucleotide phosphate (NADPH). Ribose 5-phosphate is used for nucleotide synthesis, while NADPH is involved in redox homoeostasis as well as in promoting biosynthetic processes, such as the synthesis of tetrahydrofolate, deoxyribonucleotides, proline, fatty acids and cholesterol. Through NADPH, the PPP plays a critical role in suppressing oxidative stress, including in certain cancers, in which PPP inhibition may be therapeutically useful. Conversely, PPP-derived NADPH also supports purposeful cellular generation of reactive oxygen species (ROS) and reactive nitrogen species (RNS) for signalling and pathogen killing. Genetic deficiencies in the PPP occur relatively commonly in the committed pathway enzyme glucose-6-phosphate dehydrogenase (G6PD). G6PD deficiency typically manifests as haemolytic anaemia due to red cell oxidative damage but, in severe cases, also results in infections due to lack of leucocyte oxidative burst, highlighting the dual redox roles of the pathway in free radical production and detoxification. This Review discusses the PPP in mammals, covering its roles in biochemistry, physiology and disease.

MSBooster: improving peptide identification rates using deep learning-based features

Peptide identification in liquid chromatography-tandem mass spectrometry (LC-MS/MS) experiments relies on computational algorithms for matching acquired MS/MS spectra against sequences of candidate peptides using database search tools, such as MSFragger. Here, we present a new tool, MSBooster, for rescoring peptide-to-spectrum matches using additional features incorporating deep learning-based predictions of peptide properties, such as LC retention time, ion mobility, and MS/MS spectra. We demonstrate the utility of MSBooster, in tandem with MSFragger and Percolator, in several different workflows, including nonspecific searches (immunopeptidomics), direct identification of peptides from data independent acquisition data, single-cell proteomics, and data generated on an ion mobility separation-enabled timsTOF MS platform. MSBooster is fast, robust, and fully integrated into the widely used FragPipe computational platform.

The yeast RNA methylation complex consists of conserved yet reconfigured components with m6A-dependent and independent roles

N6-methyladenosine (m6A), the most abundant mRNA modification, is deposited in mammals/insects/plants by m6A methyltransferase complexes (MTC) comprising a catalytic subunit and at least five additional proteins. The yeast MTC is critical for meiosis and was known to comprise three proteins, of which two were conserved. We uncover three novel MTC components (Kar4/Ygl036w-Vir1/Dyn2). All MTC subunits, except for Dyn2, are essential for m6A deposition and have corresponding mammalian MTC orthologues. Unlike the mammalian bipartite MTC, the yeast MTC is unipartite, yet multifunctional. The mRNA interacting module, comprising Ime4, Mum2, Vir1, and Kar4, exerts the MTC's m6A-independent function, while Slz1 enables the MTC catalytic function in m6A deposition. Both functions are critical for meiotic progression. Kar4 also has a mechanistically separate role from the MTC during mating. The yeast MTC constituents play distinguishable m6A-dependent, MTC-dependent, and MTC-independent functions, highlighting their complexity and paving the path towards dissecting multi-layered MTC functions in mammals.

The Impact of Acute Nutritional Interventions on the Plasma Proteome

CONTEXT

Humans respond profoundly to changes in diet, while nutrition and environment have a great impact on population health. It is therefore important to deeply characterize the human nutritional responses.

OBJECTIVE

Endocrine parameters and the metabolome of human plasma are rapidly responding to acute nutritional interventions such as caloric restriction or a glucose challenge. It is less well understood whether the plasma proteome would be equally dynamic, and whether it could be a source of corresponding biomarkers.

METHODS

We used high-throughput mass spectrometry to determine changes in the plasma proteome of i) 10 healthy, young, male individuals in response to 2 days of acute caloric restriction followed by refeeding; ii) 200 individuals of the Ely epidemiological study before and after a glucose tolerance test at 4 time points (0, 30, 60, 120 minutes); and iii) 200 random individuals from the Generation Scotland study. We compared the proteomic changes detected with metabolome data and endocrine parameters.

RESULTS

Both caloric restriction and the glucose challenge substantially impacted the plasma proteome. Proteins responded across individuals or in an individual-specific manner. We identified nutrient-responsive plasma proteins that correlate with changes in the metabolome, as well as with endocrine parameters. In particular, our study highlights the role of apolipoprotein C1 (APOC1), a small, understudied apolipoprotein that was affected by caloric restriction and dominated the response to glucose consumption and differed in abundance between individuals with and without type 2 diabetes.

CONCLUSION

Our study identifies APOC1 as a dominant nutritional responder in humans and highlights the interdependency of acute nutritional response proteins and the endocrine system.

Fighting Post-COVID and ME/CFS - development of curative therapies

The sequela of COVID-19 include a broad spectrum of symptoms that fall under the umbrella term post-COVID-19 condition or syndrome (PCS). Immune dysregulation, autoimmunity, endothelial dysfunction, viral persistence, and viral reactivation have been identified as potential mechanisms. However, there is heterogeneity in expression of biomarkers, and it is unknown yet whether these distinguish different clinical subgroups of PCS. There is an overlap of symptoms and pathomechanisms of PCS with postinfectious myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). No curative therapies are available for ME/CFS or PCS. The mechanisms identified so far provide targets for therapeutic interventions. To accelerate the development of therapies, we propose evaluating drugs targeting different mechanisms in clinical trial networks using harmonized diagnostic and outcome criteria and subgrouping patients based on a thorough clinical profiling including a comprehensive diagnostic and biomarker phenotyping.

Spontaneously established syntrophic yeast communities improve bioproduction

Nutritional codependence (syntrophy) has underexplored potential to improve biotechnological processes by using cooperating cell types. So far, design of yeast syntrophic communities has required extensive genetic manipulation, as the co-inoculation of most eukaryotic microbial auxotrophs does not result in cooperative growth. Here we employ high-throughput phenotypic screening to systematically test pairwise combinations of auxotrophic Saccharomyces cerevisiae deletion mutants. Although most coculture pairs do not enter syntrophic growth, we identify 49 pairs that spontaneously form syntrophic, synergistic communities. We characterized the stability and growth dynamics of nine cocultures and demonstrated that a pair of tryptophan auxotrophs grow by exchanging a pathway intermediate rather than end products. We then introduced a malonic semialdehyde biosynthesis pathway split between different pairs of auxotrophs, which resulted in increased production. Our results report the spontaneous formation of stable syntrophy in S. cerevisiae auxotrophs and illustrate the biotechnological potential of dividing labor in a cooperating intraspecies community.

The proteomic landscape of genome-wide genetic perturbations

Functional genomic strategies have become fundamental for annotating gene function and regulatory networks. Here, we combined functional genomics with proteomics by quantifying protein abundances in a genome-scale knockout library in Saccharomyces cerevisiae, using data-independent acquisition mass spectrometry. We find that global protein expression is driven by a complex interplay of (1) general biological properties, including translation rate, protein turnover, the formation of protein complexes, growth rate, and genome architecture, followed by (2) functional properties, such as the connectivity of a protein in genetic, metabolic, and physical interaction networks. Moreover, we show that functional proteomics complements current gene annotation strategies through the assessment of proteome profile similarity, protein covariation, and reverse proteome profiling. Thus, our study reveals principles that govern protein expression and provides a genome-spanning resource for functional annotation.

RECAST: Study protocol for an observational study for the understanding of the increased REsilience of Children compared to Adults in SARS-CoV-2 infecTion

INTRODUCTION

The SARS-CoV-2 pandemic remains a threat to public health. Soon after its outbreak, it became apparent that children are less severely affected. Indeed, opposing clinical manifestations between children and adults are observed for other infections. The SARS-CoV-2 outbreak provides the unique opportunity to study the underlying mechanisms. This protocol describes the methods of an observational study that aims to characterise age dependent differences in immune responses to primary respiratory infections using SARS-CoV-2 as a model virus and to assess age differences in clinical outcomes including lung function.

METHODS AND ANALYSIS

The study aims to recruit at least 120 children and 60 adults that are infected with SARS-CoV-2 and collect specimen for a multiomics analysis, including single cell RNA sequencing of nasal epithelial cells and peripheral blood mononuclear cells, mass cytometry of whole blood samples and nasal cells, mass spectrometry-based serum and plasma proteomics, nasal epithelial cultures with functional in vitro analyses, SARS-CoV-2 antibody testing, sequencing of the viral genome and lung function testing. Data obtained from this multiomics approach are correlated with medical history and clinical data. Recruitment started in October 2020 and is ongoing.

ETHICS AND DISSEMINATION

The study was reviewed and approved by the Ethics Committee of Charité - Universitätsmedizin Berlin (EA2/066/20). All collected specimens are stored in the central biobank of Charité - Universitätsmedizin Berlin and are made available to all participating researchers and on request.

TRIAL REGISTRATION NUMBER

DRKS00025715, pre-results publication.

Mass spectrometry-based high-throughput proteomics and its role in biomedical studies and systems biology

There are multiple reasons why the next generation of biological and medical studies require increasing numbers of samples. Biological systems are dynamic, and the effect of a perturbation depends on the genetic background and environment. As a consequence, many conditions need to be considered to reach generalizable conclusions. Moreover, human population and clinical studies only reach sufficient statistical power if conducted at scale and with precise measurement methods. Finally, many proteins remain without sufficient functional annotations, because they have not been systematically studied under a broad range of conditions. In this review, we discuss the latest technical developments in mass spectrometry (MS)-based proteomics that facilitate large-scale studies by fast and efficient chromatography, fast scanning mass spectrometers, data-independent acquisition (DIA), and new software. We further highlight recent studies which demonstrate how high-throughput (HT) proteomics can be applied to capture biological diversity, to annotate gene functions or to generate predictive and prognostic models for human diseases.

The GAPDH redox switch safeguards reductive capacity and enables survival of stressed tumour cells

Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) is known to contain an active-site cysteine residue undergoing oxidation in response to hydrogen peroxide, leading to rapid inactivation of the enzyme. Here we show that human and mouse cells expressing a GAPDH mutant lacking this redox switch retain catalytic activity but are unable to stimulate the oxidative pentose phosphate pathway and enhance their reductive capacity. Specifically, we find that anchorage-independent growth of cells and spheroids is limited by an elevation of endogenous peroxide levels and is largely dependent on a functional GAPDH redox switch. Likewise, tumour growth in vivo is limited by peroxide stress and suppressed when the GAPDH redox switch is disabled in tumour cells. The induction of additional intratumoural oxidative stress by chemo- or radiotherapy synergized with the deactivation of the GAPDH redox switch. Mice lacking the GAPDH redox switch exhibit altered fatty acid metabolism in kidney and heart, apparently in compensation for the lack of the redox switch. Together, our findings demonstrate the physiological and pathophysiological relevance of oxidative GAPDH inactivation in mammals.

Quantitative protein biomarker panels: a path to improved clinical practice through proteomics

The utilisation of protein biomarker panels, rather than individual protein biomarkers, offers a more comprehensive representation of human physiology. It thus has the potential to improve diagnosis, prognosis and the differentiation of responders from nonresponders in the context of precision medicine. Although several proteomic techniques exist for measuring biomarker panels, the integration of proteomics into clinical practice has been limited. In this Commentary, we highlight the significance of quantitative protein biomarker panels in clinical medicine and outline the challenges that must be addressed in order to identify the most promising panels and implement them in clinical routines to realise their medical potential. Furthermore, we argue that the absolute quantification of protein panels through targeted mass spectrometric assays remains the most promising technology for translating proteomics into routine clinical applications due to its high flexibility, low sample costs, independence from affinity reagents and low entry barriers for its integration into existing laboratory workflows.

Metabolic heterogeneity and cross-feeding within isogenic yeast populations captured by DILAC

Genetically identical cells are known to differ in many physiological parameters such as growth rate and drug tolerance. Metabolic specialization is believed to be a cause of such phenotypic heterogeneity, but detection of metabolically divergent subpopulations remains technically challenging. We developed a proteomics-based technology, termed differential isotope labelling by amino acids (DILAC), that can detect producer and consumer subpopulations of a particular amino acid within an isogenic cell population by monitoring peptides with multiple occurrences of the amino acid. We reveal that young, morphologically undifferentiated yeast colonies contain subpopulations of lysine producers and consumers that emerge due to nutrient gradients. Deconvoluting their proteomes using DILAC, we find evidence for in situ cross-feeding where rapidly growing cells ferment and provide the more slowly growing, respiring cells with ethanol. Finally, by combining DILAC with fluorescence-activated cell sorting, we show that the metabolic subpopulations diverge phenotypically, as exemplified by a different tolerance to the antifungal drug amphotericin B. Overall, DILAC captures previously unnoticed metabolic heterogeneity and provides experimental evidence for the role of metabolic specialization and cross-feeding interactions as a source of phenotypic heterogeneity in isogenic cell populations.

The brain reacting to COVID-19: analysis of the cerebrospinal fluid proteome, RNA and inflammation

Patients with COVID-19 can have a variety of neurological symptoms, but the active involvement of central nervous system (CNS) in COVID-19 remains unclear. While routine cerebrospinal fluid (CSF) analyses in patients with neurological manifestations of COVID-19 generally show no or only mild inflammation, more detailed data on inflammatory mediators in the CSF of patients with COVID-19 are scarce. We studied the inflammatory response in paired CSF and serum samples of patients with COVID-19 (n = 38). Patients with herpes simplex virus encephalitis (HSVE, n = 10) and patients with non-inflammatory, non-neurodegenerative neurological diseases (n = 28) served as controls. We used proteomics, enzyme-linked immunoassays, and semiquantitative cytokine arrays to characterize inflammatory proteins. Autoantibody screening was performed with cell-based assays and native tissue staining. RNA sequencing of long-non-coding RNA and circular RNA was done to study the transcriptome. Proteomics on single protein level and subsequent pathway analysis showed similar yet strongly attenuated inflammatory changes in the CSF of COVID-19 patients compared to HSVE patients with, e.g., downregulation of the apolipoproteins and extracellular matrix proteins. Protein upregulation of the complement system, the serpin proteins pathways, and other proteins including glycoproteins alpha-2 and alpha-1 acid. Importantly, calculation of interleukin-6, interleukin-16, and CXCL10 CSF/serum indices suggest that these inflammatory mediators reach the CSF from the systemic circulation, rather than being produced within the CNS. Antibody screening revealed no pathological levels of known neuronal autoantibodies. When stratifying COVID-19 patients into those with and without bacterial superinfection as indicated by elevated procalcitonin levels, inflammatory markers were significantly (p < 0.01) higher in those with bacterial superinfection. RNA sequencing in the CSF revealed 101 linear RNAs comprising messenger RNAs, and two circRNAs being significantly differentially expressed in COVID-19 than in non-neuroinflammatory controls and neurodegenerative patients. Our findings may explain the absence of signs of intrathecal inflammation upon routine CSF testing despite the presence of SARS-CoV2 infection-associated neurological symptoms. The relevance of blood-derived mediators of inflammation in the CSF for neurological COVID-19 and post-COVID-19 symptoms deserves further investigation.

Cell-cell metabolite exchange creates a pro-survival metabolic environment that extends lifespan

Metabolism is deeply intertwined with aging. Effects of metabolic interventions on aging have been explained with intracellular metabolism, growth control, and signaling. Studying chronological aging in yeast, we reveal a so far overlooked metabolic property that influences aging via the exchange of metabolites. We observed that metabolites exported by young cells are re-imported by chronologically aging cells, resulting in cross-generational metabolic interactions. Then, we used self-establishing metabolically cooperating communities (SeMeCo) as a tool to increase metabolite exchange and observed significant lifespan extensions. The longevity of the SeMeCo was attributable to metabolic reconfigurations in methionine consumer cells. These obtained a more glycolytic metabolism and increased the export of protective metabolites that in turn extended the lifespan of cells that supplied them with methionine. Our results establish metabolite exchange interactions as a determinant of cellular aging and show that metabolically cooperating cells can shape the metabolic environment to extend their lifespan.

Increasing the throughput of sensitive proteomics by plexDIA

Current mass spectrometry methods enable high-throughput proteomics of large sample amounts, but proteomics of low sample amounts remains limited in depth and throughput. To increase the throughput of sensitive proteomics, we developed an experimental and computational framework, called plexDIA, for simultaneously multiplexing the analysis of peptides and samples. Multiplexed analysis with plexDIA increases throughput multiplicatively with the number of labels without reducing proteome coverage or quantitative accuracy. By using three-plex non-isobaric mass tags, plexDIA enables quantification of threefold more protein ratios among nanogram-level samples. Using 1-hour active gradients, plexDIA quantified ~8,000 proteins in each sample of labeled three-plex sets and increased data completeness, reducing missing data more than twofold across samples. Applied to single human cells, plexDIA quantified ~1,000 proteins per cell and achieved 98% data completeness within a plexDIA set while using ~5 minutes of active chromatography per cell. These results establish a general framework for increasing the throughput of sensitive and quantitative protein analysis.

Functional proteomic profiling links deficient DNA clearance with increased mortality in individuals with severe COVID-19 pneumonia

The factors that influence survival during severe infection are unclear. Extracellular chromatin drives pathology, but the mechanisms enabling its accumulation remain elusive. Here, we show that in murine sepsis models, splenocyte death interferes with chromatin clearance through the release of the DNase I inhibitor actin. Actin-mediated inhibition was compensated by upregulation of DNase I or the actin scavenger gelsolin. Splenocyte death and neutrophil extracellular trap (NET) clearance deficiencies were prevalent in individuals with severe COVID-19 pneumonia or microbial sepsis. Activity tracing by plasma proteomic profiling uncovered an association between low NET clearance and increased COVID-19 pathology and mortality. Low NET clearance activity with comparable proteome associations was prevalent in healthy donors with low-grade inflammation, implicating defective chromatin clearance in the development of cardiovascular disease and linking COVID-19 susceptibility to pre-existing conditions. Hence, the combination of aberrant chromatin release with defects in protective clearance mechanisms lead to poor survival outcomes.

Intestinal epithelial c-Maf expression determines enterocyte differentiation and nutrient uptake in mice

The primary function of the small intestine (SI) is to absorb nutrients to maintain whole-body energy homeostasis. Enterocytes are the major epithelial cell type facilitating nutrient sensing and uptake. However, the molecular regulators governing enterocytes have remained undefined. Here, we identify c-Maf as an enterocyte-specific transcription factor within the SI epithelium. c-Maf expression was determined by opposing Noggin/BMP signals and overlapped with the zonated enrichment of nutrient transporters in the mid-villus region. Functionally, enterocytes required c-Maf to appropriately differentiate along the villus axis. Specifically, gene programs controlling carbohydrate and protein absorption were c-Maf-dependent. Consequently, epithelial cell-specific c-Maf deletion resulted in impaired enterocyte maturation and nutrient uptake, including defects in the adaptation to different nutrient availability. Concomitantly, intraepithelial lymphocytes were less abundant, while commensal epithelial cell-attaching SFB overgrew in a c-Maf-deficient environment, highlighting the close interdependence between the intestinal epithelium, immune system, and microbiota. Collectively, our data identified c-Maf as a key regulator of SI enterocyte differentiation and function, essential for nutrient, immune, and microbial homeostasis.

Inorganic sulfur fixation via a new homocysteine synthase allows yeast cells to cooperatively compensate for methionine auxotrophy

The assimilation, incorporation, and metabolism of sulfur is a fundamental process across all domains of life, yet how cells deal with varying sulfur availability is not well understood. We studied an unresolved conundrum of sulfur fixation in yeast, in which organosulfur auxotrophy caused by deletion of the homocysteine synthase Met17p is overcome when cells are inoculated at high cell density. In combining the use of self-establishing metabolically cooperating (SeMeCo) communities with proteomic, genetic, and biochemical approaches, we discovered an uncharacterized gene product YLL058Wp, herein named Hydrogen Sulfide Utilizing-1 (HSU1). Hsu1p acts as a homocysteine synthase and allows the cells to substitute for Met17p by reassimilating hydrosulfide ions leaked from met17Δ cells into O-acetyl-homoserine and forming homocysteine. Our results show that cells can cooperate to achieve sulfur fixation, indicating that the collective properties of microbial communities facilitate their basic metabolic capacity to overcome sulfur limitation.

Repeated colonization of alpine habitats by Arabidopsis arenosa viewed through freezing resistance and ice management strategies

Success or failure of plants to cope with freezing temperatures can critically influence plant distribution and adaptation to new habitats. Especially in alpine environments, frost is a likely major selective force driving adaptation. In Arabidopsis arenosa (L.) Lawalrée, alpine populations have evolved independently in different mountain ranges, enabling studying mechanisms of acclimation and adaptation to alpine environments. We tested for heritable, parallel differentiation in freezing resistance, cold acclimation potential and ice management strategies using eight alpine and eight foothill populations. Plants from three European mountain ranges (Niedere Tauern, Făgăraș and Tatra Mountains) were grown from seeds of tetraploid populations in four common gardens, together with diploid populations from the Tatra Mountains. Freezing resistance was assessed using controlled freezing treatments and measuring effective quantum yield of photosystem II, and ice management strategies by infrared video thermography and cryomicroscopy. The alpine ecotype had a higher cold acclimation potential than the foothill ecotype, whereby this differentiation was more pronounced in tetraploid than diploid populations. However, no ecotypic differentiation was found in one region (Făgăraș), where the ancient lineage had a different evolutionary history. Upon freezing, an ice lens within a lacuna between the palisade and spongy parenchyma tissues was formed by separation of leaf tissues, a mechanism not previously reported for herbaceous species. The dynamic adjustment of freezing resistance to temperature conditions may be particularly important in alpine environments characterized by large temperature fluctuations. Furthermore, the formation of an extracellular ice lens may be a useful strategy to avoid tissue damage during freezing.

The human host response to monkeypox infection: a proteomic case series study

The rapid rise of monkeypox (MPX) cases outside previously endemic areas prompts for a better understanding of the disease. We studied the plasma proteome of a group of MPX patients with a similar infection history and clinical manifestation typical for the current outbreak. We report that MPX in this case series is associated with a strong plasma proteomic response among nutritional and acute phase response proteins. Moreover, we report a correlation between plasma proteins and disease severity. Contrasting the MPX host response with that of COVID‐19, we find a range of similarities, but also important differences. For instance, CFHR1 is induced in COVID‐19, but suppressed in MPX, reflecting the different roles of the complement system in the two infectious diseases. Of note, the spatial overlap in response proteins suggested that a COVID‐19 biomarker panel assay could be repurposed for MPX. Applying a targeted protein panel assay provided encouraging results and distinguished MPX cases from healthy controls. Hence, our results provide a first proteomic characterization of the MPX human host response and encourage further research on protein‐panel assays in emerging infectious diseases.

Integration of protein context improves protein-based COVID-19 patient stratification

BACKGROUND

Classification of disease severity is crucial for the management of COVID-19. Several studies have shown that individual proteins can be used to classify the severity of COVID-19. Here, we aimed to investigate whether integrating four types of protein context data, namely, protein complexes, stoichiometric ratios, pathways and network degrees will improve the severity classification of COVID-19.

METHODS

We performed machine learning based on three previously published datasets. The first was a SWATH (sequential window acquisition of all theoretical fragment ion spectra) MS (mass spectrometry) based proteomic dataset. The second was a TMTpro 16plex labeled shotgun proteomics dataset. The third was a SWATH dataset of an independent patient cohort.

RESULTS

Besides twelve proteins, machine learning also prioritized two complexes, one stoichiometric ratio, five pathways, and five network degrees, resulting a 25-feature panel. As a result, a model based on the 25 features led to effective classification of severe cases with an AUC of 0.965, outperforming the models with proteins only. Complement component C9, transthyretin (TTR) and TTR-RBP (transthyretin-retinol binding protein) complex, the stoichiometric ratio of SAA2 (serum amyloid A proteins 2)/YLPM1 (YLP Motif Containing 1), and the network degree of SIRT7 (Sirtuin 7) and A2M (alpha-2-macroglobulin) were highlighted as potential markers by this classifier. This classifier was further validated with a TMT-based proteomic data set from the same cohort (test dataset 1) and an independent SWATH-based proteomic data set from Germany (test dataset 2), reaching an AUC of 0.900 and 0.908, respectively. Machine learning models integrating protein context information achieved higher AUCs than models with only one feature type.

CONCLUSION

Our results show that the integration of protein context including protein complexes, stoichiometric ratios, pathways, network degrees, and proteins improves phenotype prediction.

Clinical characteristics with inflammation profiling of long COVID and association with 1-year recovery following hospitalisation in the UK: a prospective observational study

BACKGROUND

No effective pharmacological or non-pharmacological interventions exist for patients with long COVID. We aimed to describe recovery 1 year after hospital discharge for COVID-19, identify factors associated with patient-perceived recovery, and identify potential therapeutic targets by describing the underlying inflammatory profiles of the previously described recovery clusters at 5 months after hospital discharge.

METHODS

The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a prospective, longitudinal cohort study recruiting adults (aged ≥18 years) discharged from hospital with COVID-19 across the UK. Recovery was assessed using patient-reported outcome measures, physical performance, and organ function at 5 months and 1 year after hospital discharge, and stratified by both patient-perceived recovery and recovery cluster. Hierarchical logistic regression modelling was performed for patient-perceived recovery at 1 year. Cluster analysis was done using the clustering large applications k-medoids approach using clinical outcomes at 5 months. Inflammatory protein profiling was analysed from plasma at the 5-month visit. This study is registered on the ISRCTN Registry, ISRCTN10980107, and recruitment is ongoing.

FINDINGS

2320 participants discharged from hospital between March 7, 2020, and April 18, 2021, were assessed at 5 months after discharge and 807 (32·7%) participants completed both the 5-month and 1-year visits. 279 (35·6%) of these 807 patients were women and 505 (64·4%) were men, with a mean age of 58·7 (SD 12·5) years, and 224 (27·8%) had received invasive mechanical ventilation (WHO class 7-9). The proportion of patients reporting full recovery was unchanged between 5 months (501 [25·5%] of 1965) and 1 year (232 [28·9%] of 804). Factors associated with being less likely to report full recovery at 1 year were female sex (odds ratio 0·68 [95% CI 0·46-0·99]), obesity (0·50 [0·34-0·74]) and invasive mechanical ventilation (0·42 [0·23-0·76]). Cluster analysis (n=1636) corroborated the previously reported four clusters: very severe, severe, moderate with cognitive impairment, and mild, relating to the severity of physical health, mental health, and cognitive impairment at 5 months. We found increased inflammatory mediators of tissue damage and repair in both the very severe and the moderate with cognitive impairment clusters compared with the mild cluster, including IL-6 concentration, which was increased in both comparisons (n=626 participants). We found a substantial deficit in median EQ-5D-5L utility index from before COVID-19 (retrospective assessment; 0·88 [IQR 0·74-1·00]), at 5 months (0·74 [0·64-0·88]) to 1 year (0·75 [0·62-0·88]), with minimal improvements across all outcome measures at 1 year after discharge in the whole cohort and within each of the four clusters.

INTERPRETATION

The sequelae of a hospital admission with COVID-19 were substantial 1 year after discharge across a range of health domains, with the minority in our cohort feeling fully recovered. Patient-perceived health-related quality of life was reduced at 1 year compared with before hospital admission. Systematic inflammation and obesity are potential treatable traits that warrant further investigation in clinical trials.

FUNDING

UK Research and Innovation and National Institute for Health Research.

Cystatin C is associated with adverse COVID-19 outcomes in diverse populations

COVID-19 has highly variable clinical courses. The search for prognostic host factors for COVID-19 outcome is a priority. We performed logistic regression for ICU admission against a polygenic score (PGS) for Cystatin C (CyC) production in patients with COVID-19. We analyzed the predictive value of longitudinal plasma CyC levels in an independent cohort of patients hospitalized with COVID-19. In four cohorts spanning European and African ancestry populations, we identified a significant association between CyC-production PGS and odds of critical illness (n cases=2,319), with the strongest association captured in the UKB cohort (OR 2.13, 95% CI 1.58-2.87, p=7.12e-7). Plasma proteomics from an independent cohort of hospitalized COVID-19 patients (n cases = 131) demonstrated that CyC production was associated with COVID-specific mortality (p=0.0007). Our findings suggest that CyC may be useful for stratification of patients and it has functional role in the host response to COVID-19.

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Cystatin C varies independently of renal function in COVID-19

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A polygenic score for cystatin C production predicts critical COVID-19 illness

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Elevated serum cystatin C is associated with COVID-19 mortality

Global analysis of cytosine and adenine DNA modifications across the tree of life

Interpreting the function and metabolism of enzymatic DNA modifications requires both position-specific and global quantities. Sequencing-based techniques that deliver the former have become broadly accessible, but analytical methods for the global quantification of DNA modifications have thus far been applied mostly to individual problems. We established a mass spectrometric method for the sensitive and accurate quantification of multiple enzymatic DNA modifications. Then, we isolated DNA from 124 archean, bacterial, fungal, plant, and mammalian species, and several tissues and created a resource of global DNA modification quantities. Our dataset provides insights into the general nature of enzymatic DNA modifications, reveals unique biological cases, and provides complementary quantitative information to normalize and assess the accuracy of sequencing-based detection of DNA modifications. We report that only three of the studied DNA modifications, methylcytosine (5mdC), methyladenine (N6mdA) and hydroxymethylcytosine (5hmdC), were detected above a picomolar detection limit across species, and dominated in higher eukaryotes (5mdC), in bacteria (N6mdA), or the vertebrate central nervous systems (5hmdC). All three modifications were detected simultaneously in only one of the tested species, Raphanus sativus. In contrast, these modifications were either absent or detected only at trace quantities, across all yeasts and insect genomes studied. Further, we reveal interesting biological cases. For instance, in Allium cepa, Helianthus annuus, or Andropogon gerardi, more than 35% of cytosines were methylated. Additionally, next to the mammlian CNS, 5hmdC was also detected in plants like Lepidium sativum and was found on 8% of cytosines in the Garra barreimiae brain samples. Thus, identifying unexpected levels of DNA modifications in several wild species, our resource underscores the need to address biological diversity for studying DNA modifications.

dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts

The dia-PASEF technology uses ion mobility separation to reduce signal interferences and increase sensitivity in proteomic experiments. Here we present a two-dimensional peak-picking algorithm and generation of optimized spectral libraries, as well as take advantage of neural network-based processing of dia-PASEF data. Our computational platform boosts proteomic depth by up to 83% compared to previous work, and is specifically beneficial for fast proteomic experiments and those with low sample amounts. It quantifies over 5300 proteins in single injections recorded at 200 samples per day throughput using Evosep One chromatography system on a timsTOF Pro mass spectrometer and almost 9000 proteins in single injections recorded with a 93-min nanoflow gradient on timsTOF Pro 2, from 200 ng of HeLa peptides. A user-friendly implementation is provided through the incorporation of the algorithms in the DIA-NN software and by the FragPipe workflow for spectral library generation.

Spermidine reduces neuroinflammation and soluble amyloid beta in an Alzheimer's disease mouse model

Background

Deposition of amyloid beta (Aβ) and hyperphosphorylated tau along with glial cell-mediated neuroinflammation are prominent pathogenic hallmarks of Alzheimer’s disease (AD). In recent years, impairment of autophagy has been identified as another important feature contributing to AD progression. Therefore, the potential of the autophagy activator spermidine, a small body-endogenous polyamine often used as dietary supplement, was assessed on Aβ pathology and glial cell-mediated neuroinflammation.

Results

Oral treatment of the amyloid prone AD-like APPPS1 mice with spermidine reduced neurotoxic soluble Aβ and decreased AD-associated neuroinflammation. Mechanistically, single nuclei sequencing revealed AD-associated microglia to be the main target of spermidine. This microglia population was characterized by increased AXL levels and expression of genes implicated in cell migration and phagocytosis. A subsequent proteome analysis of isolated microglia confirmed the anti-inflammatory and cytoskeletal effects of spermidine in APPPS1 mice. In primary microglia and astrocytes, spermidine-induced autophagy subsequently affected TLR3- and TLR4-mediated inflammatory processes, phagocytosis of Aβ and motility. Interestingly, spermidine regulated the neuroinflammatory response of microglia beyond transcriptional control by interfering with the assembly of the inflammasome.

Conclusions

Our data highlight that the autophagy activator spermidine holds the potential to enhance Aβ degradation and to counteract glia-mediated neuroinflammation in AD pathology.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02534-7.

A multiplex protein panel assay for severity prediction and outcome prognosis in patients with COVID-19: An observational multi-cohort study

BACKGROUND

Global healthcare systems continue to be challenged by the COVID-19 pandemic, and there is a need for clinical assays that can help optimise resource allocation, support treatment decisions, and accelerate the development and evaluation of new therapies.

METHODS

We developed a multiplexed proteomics assay for determining disease severity and prognosis in COVID-19. The assay quantifies up to 50 peptides, derived from 30 known and newly introduced COVID-19-related protein markers, in a single measurement using routine-lab compatible analytical flow rate liquid chromatography and multiple reaction monitoring (LC-MRM). We conducted two observational studies in patients with COVID-19 hospitalised at Charité - Universitätsmedizin Berlin, Germany before (from March 1 to 26, 2020, n=30) and after (from April 4 to November 19, 2020, n=164) dexamethasone became standard of care. The study is registered in the German and the WHO International Clinical Trials Registry (DRKS00021688).

FINDINGS

The assay produces reproducible (median inter-batch CV of 10.9%) absolute quantification of 47 peptides with high sensitivity (median LLOQ of 143 ng/ml) and accuracy (median 96.8%). In both studies, the assay reproducibly captured hallmarks of COVID-19 infection and severity, as it distinguished healthy individuals, mild, moderate, and severe COVID-19. In the post-dexamethasone cohort, the assay predicted survival with an accuracy of 0.83 (108/130), and death with an accuracy of 0.76 (26/34) in the median 2.5 weeks before the outcome, thereby outperforming compound clinical risk assessments such as SOFA, APACHE II, and ABCS scores.

INTERPRETATION

Disease severity and clinical outcomes of patients with COVID-19 can be stratified and predicted by the routine-applicable panel assay that combines known and novel COVID-19 biomarkers. The prognostic value of this assay should be prospectively assessed in larger patient cohorts for future support of clinical decisions, including evaluation of sample flow in routine setting. The possibility to objectively classify COVID-19 severity can be helpful for monitoring of novel therapies, especially in early clinical trials.

FUNDING

This research was funded in part by the European Research Council (ERC) under grant agreement ERC-SyG-2020 951475 (to M.R) and by the Wellcome Trust (IA 200829/Z/16/Z to M.R.). The work was further supported by the Ministry of Education and Research (BMBF) as part of the National Research Node 'Mass Spectrometry in Systems Medicine (MSCoresys)', under grant agreements 031L0220 and 161L0221. J.H. was supported by a Swiss National Science Foundation (SNSF) Postdoc Mobility fellowship (project number 191052). This study was further supported by the BMBF grant NaFoUniMedCOVID-19 - NUM-NAPKON, FKZ: 01KX2021. The study was co-funded by the UK's innovation agency, Innovate UK, under project numbers 75594 and 56328.

Optimization of Microflow LC Coupled with Scanning SWATH and Its Application in Hepatocellular Carcinoma Tissues

Scanning SWATH coupled with normal-flow LC has been recently introduced for high-content, high-throughput proteomics analysis, which requires a relatively large amount of sample injection. Here we established the microflow LC coupled with Scanning SWATH for samples with relatively small quantities. First, we optimized several key parameters of the LC and MS settings, including C18 particle size for the analytical column, LC gradient and flow rate, as well as effective ion accumulation time and isolation window width for MS acquisition. We then compared the optimized Scanning SWATH method with the conventional variable window SWATH (referred to as SWATH) method. Results showed that the total ion chromatogram signals in Scanning SWATH were 10 times higher than that of SWATH, and Scanning SWATH identified 12.2-22.2% more peptides than SWATH. Finally, we employed 120 min Scanning SWATH to acquire the proteomes of 62 formalin-fixed, paraffin-embedded (FFPE) tissue samples from 31 patients with hepatocellular carcinoma (HCC). Altogether, 92 334 peptides and 8516 proteins were quantified. Besides the reported biomarkers, including ANXA2, MCM7, SUOX, and AKR1B10, we identified new potential HCC biomarkers such as CST5, TP53, CEBPB, and E2F4. Taken together, we present an optimal workflow integrating microflow LC and Scanning SWATH that effectively improves the protein identification and quantitation.

Microbial communities form rich extracellular metabolomes that foster metabolic interactions and promote drug tolerance

Microbial communities are composed of cells of varying metabolic capacity, and regularly include auxotrophs that lack essential metabolic pathways. Through analysis of auxotrophs for amino acid biosynthesis pathways in microbiome data derived from >12,000 natural microbial communities obtained as part of the Earth Microbiome Project (EMP), and study of auxotrophic–prototrophic interactions in self-establishing metabolically cooperating yeast communities (SeMeCos), we reveal a metabolically imprinted mechanism that links the presence of auxotrophs to an increase in metabolic interactions and gains in antimicrobial drug tolerance. As a consequence of the metabolic adaptations necessary to uptake specific metabolites, auxotrophs obtain altered metabolic flux distributions, export more metabolites and, in this way, enrich community environments in metabolites. Moreover, increased efflux activities reduce intracellular drug concentrations, allowing cells to grow in the presence of drug levels above minimal inhibitory concentrations. For example, we show that the antifungal action of azoles is greatly diminished in yeast cells that uptake metabolites from a metabolically enriched environment. Our results hence provide a mechanism that explains why cells are more robust to drug exposure when they interact metabolically.

Using microbiome data analysis and a self-establishing metabolically cooperating yeast community model, the authors show that the presence of auxotrophs in a microbial community increases metabolic interactions between cells and fosters antimicrobial drug tolerance.

Pre-activated antiviral innate immunity in the upper airways controls early SARS-CoV-2 infection in children

Children have reduced severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection rates and a substantially lower risk for developing severe coronavirus disease 2019 compared with adults. However, the molecular mechanisms underlying protection in younger age groups remain unknown. Here we characterize the single-cell transcriptional landscape in the upper airways of SARS-CoV-2-negative (n = 18) and age-matched SARS-CoV-2-positive (n = 24) children and corresponding samples from adults (n = 44), covering an age range of 4 weeks to 77 years. Children displayed higher basal expression of relevant pattern recognition receptors such as MDA5 (IFIH1) and RIG-I (DDX58) in upper airway epithelial cells, macrophages and dendritic cells, resulting in stronger innate antiviral responses upon SARS-CoV-2 infection than in adults. We further detected distinct immune cell subpopulations including KLRC1 (NKG2A)+ cytotoxic T cells and a CD8+ T cell population with a memory phenotype occurring predominantly in children. Our study provides evidence that the airway immune cells of children are primed for virus sensing, resulting in a stronger early innate antiviral response to SARS-CoV-2 infection than in adults.