Analyses of long-term fungal degradation of spruce bark reveals varying potential for catabolism of polysaccharides and extractive compounds.

The bark represents the outer protective layer of trees. It contains high concentrations of antimicrobial extractives, in addition to regular wood polymers. It represents a huge underutilized side stream in forestry, but biotechnological valorization is hampered by a lack of knowledge on microbial bark degradation. Many fungi are efficient lignocellulose degraders, and here, spruce bark degradation by five species, Dichomitus squalens, Rhodonia placenta, Penicillium crustosum, Trichoderma sp. B1, and Trichoderma reesei, was mapped, by continuously analyzing chemical changes in the bark over six months. The study reveals how fungi from different phyla degrade bark using diverse strategies, regarding both wood polymers and extractives, where toxic resin acids were degraded by Basidiomycetes but unmodified/tolerated by Ascomycetes. Proteome analyses of the white-rot D. squalens revealed several proteins, with both known and unknown functions, that were specifically upregulated during growth on bark. This knowledge can accelerate improved utilization of an abundant renewable resource.

Integrative common and rare variant analyses provide insights into the genetic architecture of liver cirrhosis.

We report a multi-ancestry genome-wide association study on liver cirrhosis and its associated endophenotypes, alanine aminotransferase (ALT) and γ-glutamyl transferase. Using data from 12 cohorts, including 18,265 cases with cirrhosis, 1,782,047 controls, up to 1 million individuals with liver function tests and a validation cohort of 21,689 cases and 617,729 controls, we identify and validate 14 risk associations for cirrhosis. Many variants are located near genes involved in hepatic lipid metabolism. One of these, PNPLA3 p.Ile148Met, interacts with alcohol intake, obesity and diabetes on the risk of cirrhosis and hepatocellular carcinoma (HCC). We develop a polygenic risk score that associates with the progression from cirrhosis to HCC. By focusing on prioritized genes from common variant analyses, we find that rare coding variants in GPAM associate with lower ALT, supporting GPAM as a potential target for therapeutic inhibition. In conclusion, this study provides insights into the genetic underpinnings of cirrhosis.

Genetics and epidemiology of mutational barcode-defined clonal hematopoiesis.

Clonal hematopoiesis (CH) arises when a substantial proportion of mature blood cells is derived from a single hematopoietic stem cell lineage. Using whole-genome sequencing of 45,510 Icelandic and 130,709 UK Biobank participants combined with a mutational barcode method, we identified 16,306 people with CH. Prevalence approaches 50% in elderly participants. Smoking demonstrates a dosage-dependent impact on risk of CH. CH associates with several smoking-related diseases. Contrary to published claims, we find no evidence that CH is associated with cardiovascular disease. We provide evidence that CH is driven by genes that are commonly mutated in myeloid neoplasia and implicate several new driver genes. The presence and nature of a driver mutation alters the risk profile for hematological disorders. Nevertheless, most CH cases have no known driver mutations. A CH genome-wide association study identified 25 loci, including 19 not implicated previously in CH. Splicing, protein and expression quantitative trait loci were identified for CD164 and TCL1A.

Phonon Signatures in Photon Correlations.

We show that the second-order, two-time correlation functions for phonons and photons emitted from a vibronic molecule in a thermal bath result in bunching and antibunching (a purely quantum effect), respectively. Signatures relating to phonon exchange with the environment are revealed in photon-photon correlations. We demonstrate that cross-correlation functions have a strong dependence on the order of detection giving insight into how phonon dynamics influences the emission of light. This work offers new opportunities to investigate quantum effects in condensed-phase molecular systems.

Large-scale plasma proteomics comparisons through genetics and disease associations.

High-throughput proteomics platforms measuring thousands of proteins in plasma combined with genomic and phenotypic information have the power to bridge the gap between the genome and diseases. Here we performed association studies of Olink Explore 3072 data generated by the UK Biobank Pharma Proteomics Project1 on plasma samples from more than 50,000 UK Biobank participants with phenotypic and genotypic data, stratifying on British or Irish, African and South Asian ancestries. We compared the results with those of a SomaScan v4 study on plasma from 36,000 Icelandic people2, for 1,514 of whom Olink data were also available. We found modest correlation between the two platforms. Although cis protein quantitative trait loci were detected for a similar absolute number of assays on the two platforms (2,101 on Olink versus 2,120 on SomaScan), the proportion of assays with such supporting evidence for assay performance was higher on the Olink platform (72% versus 43%). A considerable number of proteins had genomic associations that differed between the platforms. We provide examples where differences between platforms may influence conclusions drawn from the integration of protein levels with the study of diseases. We demonstrate how leveraging the diverse ancestries of participants in the UK Biobank helps to detect novel associations and refine genomic location. Our results show the value of the information provided by the two most commonly used high-throughput proteomics platforms and demonstrate the differences between them that at times provides useful complementarity.

Complex effects of sequence variants on lipid levels and coronary artery disease.

Many sequence variants have additive effects on blood lipid levels and, through that, on the risk of coronary artery disease (CAD). We show that variants also have non-additive effects and interact to affect lipid levels as well as affecting variance and correlations. Variance and correlation effects are often signatures of epistasis or gene-environmental interactions. These complex effects can translate into CAD risk. For example, Trp154Ter in FUT2 protects against CAD among subjects with the A1 blood group, whereas it associates with greater risk of CAD in others. His48Arg in ADH1B interacts with alcohol consumption to affect lipid levels and CAD. The effect of variants in TM6SF2 on blood lipids is greatest among those who never eat oily fish but absent from those who often do. This work demonstrates that variants that affect variance of quantitative traits can allow for the discovery of epistasis and interactions of variants with the environment.

Evaluation of Large-Scale Proteomics for Prediction of Cardiovascular Events.

Importance: Whether protein risk scores derived from a single plasma sample could be useful for risk assessment for atherosclerotic cardiovascular disease (ASCVD), in conjunction with clinical risk factors and polygenic risk scores, is uncertain. Objective: To develop protein risk scores for ASCVD risk prediction and compare them to clinical risk factors and polygenic risk scores in primary and secondary event populations. Design, Setting, and Participants: The primary analysis was a retrospective study of primary events among 13 540 individuals in Iceland (aged 40-75 years) with proteomics data and no history of major ASCVD events at recruitment (study duration, August 23, 2000 until October 26, 2006; follow-up through 2018). We also analyzed a secondary event population from a randomized, double-blind lipid-lowering clinical trial (2013-2016), consisting of individuals with stable ASCVD receiving statin therapy and for whom proteomic data were available for 6791 individuals. Exposures: Protein risk scores (based on 4963 plasma protein levels and developed in a training set in the primary event population); polygenic risk scores for coronary artery disease and stroke; and clinical risk factors that included age, sex, statin use, hypertension treatment, type 2 diabetes, body mass index, and smoking status at the time of plasma sampling. Main Outcomes and Measures: Outcomes were composites of myocardial infarction, stroke, and coronary heart disease death or cardiovascular death. Performance was evaluated using Cox survival models and measures of discrimination and reclassification that accounted for the competing risk of non-ASCVD death. Results: In the primary event population test set (4018 individuals [59.0% women]; 465 events; median follow-up, 15.8 years), the protein risk score had a hazard ratio (HR) of 1.93 per SD (95% CI, 1.75 to 2.13). Addition of protein risk score and polygenic risk scores significantly increased the C index when added to a clinical risk factor model (C index change, 0.022 [95% CI, 0.007 to 0.038]). Addition of the protein risk score alone to a clinical risk factor model also led to a significantly increased C index (difference, 0.014 [95% CI, 0.002 to 0.028]). Among White individuals in the secondary event population (6307 participants; 432 events; median follow-up, 2.2 years), the protein risk score had an HR of 1.62 per SD (95% CI, 1.48 to 1.79) and significantly increased C index when added to a clinical risk factor model (C index change, 0.026 [95% CI, 0.011 to 0.042]). The protein risk score was significantly associated with major adverse cardiovascular events among individuals of African and Asian ancestries in the secondary event population. Conclusions and Relevance: A protein risk score was significantly associated with ASCVD events in primary and secondary event populations. When added to clinical risk factors, the protein risk score and polygenic risk score both provided statistically significant but modest improvement in discrimination.

Histopathology and levels of proteins in plasma associate with survival after colorectal cancer diagnosis.

BACKGROUND: The TNM system is used to assess prognosis after colorectal cancer (CRC) diagnosis. Other prognostic factors reported include histopathological assessments of the tumour, tumour mutations and proteins in the blood. As some of these factors are strongly correlated, it is important to evaluate the independent effects they may have on survival. METHODS: Tumour samples from 2162 CRC patients were visually assessed for amount of tumour stroma, severity of lymphocytic infiltrate at the tumour margins and the presence of lymphoid follicles. Somatic mutations in the tumour were assessed for 2134 individuals. Pre-surgical levels of 4963 plasma proteins were measured in 128 individuals. The associations between these features and prognosis were inspected by a Cox Proportional Hazards Model (CPH). RESULTS: Levels of stroma, lymphocytic infiltration and presence of lymphoid follicles all associate with prognosis, along with high tumour mutation burden, high microsatellite instability and TP53 and BRAF mutations. The somatic mutations are correlated with the histopathology and none of the somatic mutations associate with survival in a multivariate analysis. Amount of stroma and lymphocytic infiltration associate with local invasion of tumours. Elevated levels of two plasma proteins, CA-125 and PPP1R1A, associate with a worse prognosis. CONCLUSIONS: Tumour stroma and lymphocytic infiltration variables are strongly associated with prognosis of CRC and capture the prognostic effects of tumour mutation status. CA-125 and PPP1R1A may be useful prognostic biomarkers in CRC.

Integrative meta-omics in Galaxy and beyond.

BACKGROUND: 'Omics methods have empowered scientists to tackle the complexity of microbial communities on a scale not attainable before. Individually, omics analyses can provide great insight; while combined as "meta-omics", they enhance the understanding of which organisms occupy specific metabolic niches, how they interact, and how they utilize environmental nutrients. Here we present three integrative meta-omics workflows, developed in Galaxy, for enhanced analysis and integration of metagenomics, metatranscriptomics, and metaproteomics, combined with our newly developed web-application, ViMO (Visualizer for Meta-Omics) to analyse metabolisms in complex microbial communities. RESULTS: In this study, we applied the workflows on a highly efficient cellulose-degrading minimal consortium enriched from a biogas reactor to analyse the key roles of uncultured microorganisms in complex biomass degradation processes. Metagenomic analysis recovered metagenome-assembled genomes (MAGs) for several constituent populations including Hungateiclostridium thermocellum, Thermoclostridium stercorarium and multiple heterogenic strains affiliated to Coprothermobacter proteolyticus. The metagenomics workflow was developed as two modules, one standard, and one optimized for improving the MAG quality in complex samples by implementing a combination of single- and co-assembly, and dereplication after binning. The exploration of the active pathways within the recovered MAGs can be visualized in ViMO, which also provides an overview of the MAG taxonomy and quality (contamination and completeness), and information about carbohydrate-active enzymes (CAZymes), as well as KEGG annotations and pathways, with counts and abundances at both mRNA and protein level. To achieve this, the metatranscriptomic reads and metaproteomic mass-spectrometry spectra are mapped onto predicted genes from the metagenome to analyse the functional potential of MAGs, as well as the actual expressed proteins and functions of the microbiome, all visualized in ViMO. CONCLUSION: Our three workflows for integrative meta-omics in combination with ViMO presents a progression in the analysis of 'omics data, particularly within Galaxy, but also beyond. The optimized metagenomics workflow allows for detailed reconstruction of microbial community consisting of MAGs with high quality, and thus improves analyses of the metabolism of the microbiome, using the metatranscriptomics and metaproteomics workflows.

Sequence variants affecting voice pitch in humans.

The genetic basis of the human vocal system is largely unknown, as are the sequence variants that give rise to individual differences in voice and speech. Here, we couple data on diversity in the sequence of the genome with voice and vowel acoustics in speech recordings from 12,901 Icelanders. We show how voice pitch and vowel acoustics vary across the life span and correlate with anthropometric, physiological, and cognitive traits. We found that voice pitch and vowel acoustics have a heritable component and discovered correlated common variants in ABCC9 that associate with voice pitch. The ABCC9 variants also associate with adrenal gene expression and cardiovascular traits. By showing that voice and vowel acoustics are influenced by genetics, we have taken important steps toward understanding the genetics and evolution of the human vocal system.

Metabolic influence of core ciliates within the rumen microbiome.

Protozoa comprise a major fraction of the microbial biomass in the rumen microbiome, of which the entodiniomorphs (order: Entodiniomorphida) and holotrichs (order: Vestibuliferida) are consistently observed to be dominant across a diverse genetic and geographical range of ruminant hosts. Despite the apparent core role that protozoal species exert, their major biological and metabolic contributions to rumen function remain largely undescribed in vivo. Here, we have leveraged (meta)genome-centric metaproteomes from rumen fluid samples originating from both cattle and goats fed diets with varying inclusion levels of lipids and starch, to detail the specific metabolic niches that protozoa occupy in the context of their microbial co-habitants. Initial proteome estimations via total protein counts and label-free quantification highlight that entodiniomorph species Entodinium and Epidinium as well as the holotrichs Dasytricha and Isotricha comprise an extensive fraction of the total rumen metaproteome. Proteomic detection of protozoal metabolism such as hydrogenases (Dasytricha, Isotricha, Epidinium, Enoploplastron), carbohydrate-active enzymes (Epidinium, Diplodinium, Enoploplastron, Polyplastron), microbial predation (Entodinium) and volatile fatty acid production (Entodinium and Epidinium) was observed at increased levels in high methane-emitting animals. Despite certain protozoal species having well-established reputations for digesting starch, they were unexpectedly less detectable in low methane emitting-animals fed high starch diets, which were instead dominated by propionate/succinate-producing bacterial populations suspected of being resistant to predation irrespective of host. Finally, we reaffirmed our abovementioned observations in geographically independent datasets, thus illuminating the substantial metabolic influence that under-explored eukaryotic populations have in the rumen, with greater implications for both digestion and methane metabolism.

Analyzing Activities of Lytic Polysaccharide Monooxygenases by Liquid Chromatography and Mass Spectrometry.

Lytic polysaccharide monooxygenases perform oxidative cleavage of glycosidic bonds in various polysaccharides. The majority of LMPOs studied so far possess activity on either cellulose or chitin and analysis of these activities is therefore the main focus of this review. Notably, however, the number of LPMOs that are active on other polysaccharides is increasing. The products generated by LPMOs from cellulose are either oxidized in the downstream end (at C1) or upstream end (at C4), or at both ends. These modifications only result in small structural changes, which makes both chromatographic separation and product identification by mass spectrometry challenging. The changes in physicochemical properties that are associated with oxidation need to be considered when choosing analytical approaches. C1 oxidation leads to a sugar that is no longer reducing but instead has an acidic functionality, whereas C4 oxidation leads to products that are inherently labile at high and low pH and that exist in a keto-gemdiol equilibrium that is strongly shifted towards the gemdiol in aqueous solutions. Partial degradation of C4-oxidized products leads to the formation of native products, which could explain why some authors claim to have observed glycoside hydrolase activity for LPMOs. Notably, apparent glycoside hydrolase activity may also be due to small amounts of contaminating glycoside hydrolases since these normally have much higher catalytic rates than LPMOs. The low catalytic turnover rates of LPMOs necessitate the use of sensitive product detection methods, which limits the analytical possibilities considerably. Modern liquid chromatography and mass spectrometry have become essential tools for evaluating LPMO activity and this chapter provides an overview of available methods together with a few novel tools. The methods described constitute a suite of techniques for analyzing oxidized carbohydrate products, which can be applied to LPMOs as well as other carbohydrate-active redox enzymes.

Effect of yeast species and processing on intestinal microbiota of Atlantic salmon (Salmo salar) fed soybean meal-based diets in seawater.

BACKGROUND: Yeasts are gaining attention as alternative ingredients in aquafeeds. However, the impact of yeast inclusion on modulation of intestinal microbiota of fish fed plant-based ingredients is limited. Thus, the present study investigates the effects of yeast and processing on composition, diversity and predicted metabolic capacity of gut microbiota of Atlantic salmon smolt fed soybean meal (SBM)-based diet. Two yeasts, Cyberlindnera jadinii (CJ) and Wickerhamomyces anomalus (WA), were produced in-house and processed by direct heat-inactivation with spray-drying (ICJ and IWA) or autolyzed at 50 °C for 16 h, followed by spray-drying (ACJ and AWA). In a 42-day feeding experiment, fish were fed one of six diets: a fishmeal (FM)-based diet, a challenging diet with 30% SBM and four other diets containing 30% SBM and 10% of each of the four yeast products (i.e., ICJ, ACJ, IWA and AWA). Microbial profiling of digesta samples was conducted using 16S rRNA gene sequencing, and the predicted metabolic capacities of gut microbiota were determined using genome-scale metabolic models. RESULTS: The microbial composition and predicted metabolic capacity of gut microbiota differed between fish fed FM diet and those fed SBM diet. The digesta of fish fed SBM diet was dominated by members of lactic acid bacteria, which was similar to microbial composition in the digesta of fish fed the inactivated yeasts (ICJ and IWA diets). Inclusion of autolyzed yeasts (ACJ and AWA diets) reduced the richness and diversity of gut microbiota in fish. The gut microbiota of fish fed ACJ diet was dominated by the genus Pediococcus and showed a predicted increase in mucin O-glycan degradation compared with the other diets. The gut microbiota of fish fed AWA diet was highly dominated by the family Bacillaceae. CONCLUSIONS: The present study showed that dietary inclusion of FM and SBM differentially modulate the composition and predicted metabolic capacity of gut microbiota of fish. The inclusion of inactivated yeasts did not alter the modulation caused by SBM-based diet. Fish fed ACJ diet increased relative abundance of Pediococcus, and mucin O-glycan degradation pathway compared with the other diets.

Thirty novel sequence variants impacting human intracranial volume.

Intracranial volume, measured through magnetic resonance imaging and/or estimated from head circumference, is heritable and correlates with cognitive traits and several neurological disorders. We performed a genome-wide association study meta-analysis of intracranial volume (n = 79 174) and found 64 associating sequence variants explaining 5.0% of its variance. We used coding variation, transcript and protein levels, to uncover 12 genes likely mediating the effect of these variants, including GLI3 and CDK6 that affect cranial synostosis and microcephaly, respectively. Intracranial volume correlates genetically with volumes of cortical and sub-cortical regions, cognition, learning, neonatal and neurological traits. Parkinson's disease cases have greater and attention deficit hyperactivity disorder cases smaller intracranial volume than controls. Our Mendelian randomization studies indicate that intracranial volume associated variants either increase the risk of Parkinson's disease and decrease the risk of attention deficit hyperactivity disorder and neuroticism or correlate closely with a confounder.

Importance of NT-proBNP and conventional risk factors for prediction of death in older adults with and without diabetes mellitus- A report from the Atherosclerosis Risk in Communities (ARIC) study.

In this community-based cohort of 5861 individuals followed for median 7.2 years, the discriminatory ability of NT-proBNP alone in predicting mortality was similar to that of multiple conventional markers of risk in people without diabetes. In people with diabetes, NT-proBNP alone discriminated risk of mortality better than conventional risk factors.

SILAC-based quantitative proteomics and microscopy analysis of cancer cells treated with the N-glycolyl GM3-specific anti-tumor antibody 14F7.

Cancer immunotherapy represents a promising approach to specifically target and treat cancer. The most common mechanisms by which monoclonal antibodies kill cells include antibody-dependent cell-mediated cytotoxicity, complement-dependent cytotoxicity and apoptosis, but also other mechanisms have been described. 14F7 is an antibody raised against the tumor-associated antigen NeuGc GM3, which was previously reported to kill cancer cells without inducing apoptotic pathways. The antibody was reported to induce giant membrane lesions in tumor cells, with apparent changes in the cytoskeleton. Here, we investigated the effect of humanized 14F7 on HeLa cells using stable isotope labeling with amino acids in cell culture (SILAC) in combination with LC-MS and live cell imaging. 14F7 did not kill the HeLa cells, however, it caused altered protein expression (MS data are available via ProteomeXchange with identifier PXD024320). Several cytoskeletal and nucleic-acid binding proteins were found to be strongly down-regulated in response to antibody treatment, suggesting how 14F7 may induce membrane lesions in cells that contain higher amounts of NeuGc GM3. The altered expression profile identified in this study thus contributes to an improved understanding of the unusual killing mechanism of 14F7.

Multiomics study of nonalcoholic fatty liver disease.

Nonalcoholic fatty liver (NAFL) and its sequelae are growing health problems. We performed a genome-wide association study of NAFL, cirrhosis and hepatocellular carcinoma, and integrated the findings with expression and proteomic data. For NAFL, we utilized 9,491 clinical cases and proton density fat fraction extracted from 36,116 liver magnetic resonance images. We identified 18 sequence variants associated with NAFL and 4 with cirrhosis, and found rare, protective, predicted loss-of-function variants in MTARC1 and GPAM, underscoring them as potential drug targets. We leveraged messenger RNA expression, splicing and predicted coding effects to identify 16 putative causal genes, of which many are implicated in lipid metabolism. We analyzed levels of 4,907 plasma proteins in 35,559 Icelanders and 1,459 proteins in 47,151 UK Biobank participants, identifying multiple proteins involved in disease pathogenesis. We show that proteomics can discriminate between NAFL and cirrhosis. The present study provides insights into the development of noninvasive evaluation of NAFL and new therapeutic options.

The sequences of 150,119 genomes in the UK Biobank.

Detailed knowledge of how diversity in the sequence of the human genome affects phenotypic diversity depends on a comprehensive and reliable characterization of both sequences and phenotypic variation. Over the past decade, insights into this relationship have been obtained from whole-exome sequencing or whole-genome sequencing of large cohorts with rich phenotypic data1,2. Here we describe the analysis of whole-genome sequencing of 150,119 individuals from the UK Biobank3. This constitutes a set of high-quality variants, including 585,040,410 single-nucleotide polymorphisms, representing 7.0% of all possible human single-nucleotide polymorphisms, and 58,707,036 indels. This large set of variants allows us to characterize selection based on sequence variation within a population through a depletion rank score of windows along the genome. Depletion rank analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UK Biobank: a large British Irish cohort, a smaller African cohort and a South Asian cohort. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large-scale whole-genome sequencing studies. Using this formidable new resource, we provide several examples of trait associations for rare variants with large effects not found previously through studies based on whole-exome sequencing and/or imputation.

Neuroimaging Findings in Neurodevelopmental Copy Number Variants: Identifying Molecular Pathways to Convergent Phenotypes.

Genomic copy number variants (CNVs) are associated with a high risk of neurodevelopmental disorders. A growing body of genetic studies suggests that these high-risk genetic variants converge in common molecular pathways and that common pathways also exist across clinically distinct disorders, such as schizophrenia and autism spectrum disorder. A key question is how common molecular mechanisms converge into similar clinical outcomes. We review emerging evidence for convergent cognitive and brain phenotypes across distinct CNVs. Multiple CNVs were shown to have similar effects on core sensory, cognitive, and motor traits. Emerging data from multisite neuroimaging studies have provided valuable information on how these CNVs affect brain structure and function. However, most of these studies examined one CNV at a time, making it difficult to fully understand the proportion of shared brain effects. Recent studies have started to combine neuroimaging data from multiple CNV carriers and identified similar brain effects across CNVs. Some early findings also support convergence in CNV animal models. Systems biology, through integration of multilevel data, provides new insights into convergent molecular mechanisms across genetic risk variants (e.g., altered synaptic activity). However, the link between such key molecular mechanisms and convergent psychiatric phenotypes is still unknown. To better understand this link, we need new approaches that integrate human molecular data with neuroimaging, cognitive, and animal model data, while taking into account critical developmental time points. Identifying risk mechanisms across genetic loci can elucidate the pathophysiology of neurodevelopmental disorders and identify new therapeutic targets for cross-disorder applications.