Publications

Objective:To investigate the spermidine pathway capability to predict patients at risk for tumor recurrence following colorectal cancer (CRC) surgery.Background:Recurrence rates after CRC surgery remain at about 20% despite an optimal technique and adjuvant therapy when necessary. Identification of risk biomarkers of recurrence is an unmet need. The spermidine pathway is indispensable for cell proliferation and differentiation, and is suggested to accelerate tumor spread.Methods:This was a prospective cohort study of patients undergoing CRC surgery from 2015 to 2018. Plasma samples were collected before surgery and on postoperative day 4, and the spermidine pathway was assessed through mass spectrometry. Oncological outcomes were registered.Results:A total of 146 patients were included and 24 (16.4%) developed tumor recurrence. Higher levels of preoperative spermidine pathway components (spermidine, spermine, spermidine synthase enzyme, and spermine/arginine balance) were positively associated with recurrence. Surgery promoted a decrease in these pathway elements. The greater the decline was, the lower the risk of recurrence. Preoperative spermidine over the cut-off of 0.198 mu M displayed a 4.69-fold higher risk of recurrence. The spermine synthase enzyme behaved in the opposite direction.Conclusions:The spermidine pathway is associated with tumor recurrence following CRC surgery and, after confirmation in larger cohorts, could be translated as a risk biomarker of recurrence into clinical practice.

JTD Keywords: Adjuvant chemotherapy, Colon-cancer, Colorectal cancer, Energ, Metabolomics, Polyamine levels, Postoperative intraabdominal infection, Spermidine pathway, Stage, Tumor recurrenc

Multiplexed assays of variant effect (MAVEs) have emerged as a powerful approach for interrogating thousands of genetic variants in a single experiment. The flexibility and widespread adoption of these techniques across diverse disciplines have led to a heterogeneous mix of data formats and descriptions, which complicates the downstream use of the resulting datasets. To address these issues and promote reproducibility and reuse of MAVE data, we define a set of minimum information standards for MAVE data and metadata and outline a controlled vocabulary aligned with established biomedical ontologies for describing these experimental designs.

JTD Keywords: Deep mutational scanning, Dms, Genetic variants, Genomics, Mave, Multiplexed assays of variant effect, Standards

Background: Early detection of postoperative complications after colorectal cancer (CRC) surgery is associated with improved outcomes. The aim was to investigate early metabolomics signatures capable to detect patients at risk for severe postoperative complications after CRC surgery. Materials and methods: Prospective cohort study of patients undergoing CRC surgery from 2015 to 2018. Plasma samples were collected before and after surgery, and analyzed by mass spectrometry obtaining 188 metabolites and 21 ratios. Postoperative complications were registered with Clavien-Dindo Classification and Comprehensive Complication Index. Results: One hundred forty-six patients were included. Surgery substantially modified metabolome and metabolic changes after surgery were quantitatively associated with the severity of postoperative complications. The strongest positive relationship with both Clavien-Dindo and Comprehensive Complication Index (beta=4.09 and 63.05, P<0.001) corresponded to kynurenine/tryptophan, against an inverse relationship with lysophosphatidylcholines (LPCs) and phosphatidylcholines (PCs). Patients with LPC18:2/PCa36:2 below the cut-off 0.084 mu M/mu M resulted in a sevenfold higher risk of major complications (OR=7.38, 95% CI: 2.82-21.25, P<0.001), while kynurenine/tryptophan above 0.067 mu M/mu M a ninefold (OR=9.35, 95% CI: 3.03-32.66, P<0.001). Hexadecanoylcarnitine below 0.093 mu M displayed a 12-fold higher risk of anastomotic leakage-related complications (OR=11.99, 95% CI: 2.62-80.79, P=0.004). Conclusion: Surgery-induced phospholipids and amino acid dysregulation is associated with the severity of postoperative complications after CRC surgery, including anastomotic leakage-related outcomes. The authors provide quantitative insight on metabolic markers, measuring vulnerability to postoperative morbidity that might help guide early decision-making and improve surgical outcomes.

JTD Keywords: Acids, Anastomotic leakage, Bypass, Clinical-practice guidelines, Colon, Colorectal cancer, Metabolomics, Postoperative complications, Predict, Sepsis, Trauma, Tryptophan degradation

Sequencing has revealed hundreds of millions of human genetic variants, and continued efforts will only add to this variant avalanche. Insufficient information exists to interpret the effects of most variants, limiting opportunities for precision medicine and comprehension of genome function. A solution lies in experimental assessment of the functional effect of variants, which can reveal their biological and clinical impact. However, variant effect assays have generally been undertaken reactively for individual variants only after and, in most cases long after, their first observation. Now, multiplexed assays of variant effect can characterise massive numbers of variants simultaneously, yielding variant effect maps that reveal the function of every possible single nucleotide change in a gene or regulatory element. Generating maps for every protein encoding gene and regulatory element in the human genome would create an 'Atlas' of variant effect maps and transform our understanding of genetics and usher in a new era of nucleotide-resolution functional knowledge of the genome. An Atlas would reveal the fundamental biology of the human genome, inform human evolution, empower the development and use of therapeutics and maximize the utility of genomics for diagnosing and treating disease. The Atlas of Variant Effects Alliance is an international collaborative group comprising hundreds of researchers, technologists and clinicians dedicated to realising an Atlas of Variant Effects to help deliver on the promise of genomics.

JTD Keywords: functional genomics, genome interpretation, global alliance, multiplexed assay of variant effect, saturation mutagenesis, Functional genomics, Genome interpretation, Global alliance, Multiplexed assay of variant effect, Saturation mutagenesis, Variant effect

Introduction: There is evidence that sample treatment of blood-based biosamples may affect integral signals in nuclear magnetic resonance-based metabolomics. The presence of macromolecules in plasma/serum samples makes investigating low-molecular-weight metabolites challenging. It is particularly relevant in the targeted approach, in which absolute concentrations of selected metabolites are often quantified based on the area of integral signals. Since there are a few treatments of plasma/serum samples for quantitative analysis without a universally accepted method, this topic remains of interest for future research. Methods: In this work, targeted metabolomic profiling of 43 metabolites was performed on pooled plasma to compare four methodologies consisting of Carr-Purcell-Meiboom-Gill (CPMG) editing, ultrafiltration, protein precipitation with methanol, and glycerophospholipid solid-phase extraction (g-SPE) for phospholipid removal; prior to NMR metabolomics analysis. The effect of the sample treatments on the metabolite concentrations was evaluated using a permutation test of multiclass and pairwise Fisher scores. Results: Results showed that methanol precipitation and ultrafiltration had a higher number of metabolites with coefficient of variation (CV) values above 20%. G-SPE and CPMG editing demonstrated better precision for most of the metabolites analyzed. However, differential quantification performance between procedures were metabolite-dependent. For example, pairwise comparisons showed that methanol precipitation and CPMG editing were suitable for quantifying citrate, while g-SPE showed better results for 2-hydroxybutyrate and tryptophan. Discussion: There are alterations in the absolute concentration of various metabolites that are dependent on the procedure. Considering these alterations is essential before proceeding with the quantification of treatment-sensitive metabolites in biological samples for improving biomarker discovery and biological interpretations. The study demonstrated that g-SPE and CPMG editing are effective methods for removing proteins and phospholipids from plasma samples for quantitative NMR analysis of metabolites. However, careful consideration should be given to the specific metabolites of interest and their susceptibility to the sample treatment procedures. These findings contribute to the development of optimized sample preparation protocols for metabolomics studies using NMR spectroscopy.Copyright © 2023 Madrid-Gambin, Oller, Marco, Pozo, Andres-Lacueva and Llorach.

JTD Keywords: binding, h-1-nmr spectroscopy, human serum, lactate, metabolites, nuclear magnetic resonance, plasma, protein, quantification, quantitative analysis, sample treatment, Metabolomics, Nuclear magnetic resonance, Nuclear-magnetic-resonance, Plasma, Quantification, Quantitative analysis, Sample treatment

(Phospho)proteomics of old-aged subjects without cognitive or behavioral symptoms, and without AD-neuropathological changes and lacking any other neurodegenerative alteration will increase understanding about the physiological state of human brain aging without associate neurological deficits and neuropathological lesions.(Phospho)proteomics using conventional label-free- and SWATH-MS (Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry) has been assessed in the frontal cortex (FC) of individuals without NFTs, senile plaques (SPs) and age-related co-morbidities classified by age (years) in four groups; group 1 (young, 30-44); group 2 (middle-aged: MA, 45-52); group 3 (early-elderly, 64-70); and group 4 (late-elderly, 75-85).Protein levels and deregulated protein phosphorylation linked to similar biological terms/functions, but involving different individual proteins, are found in FC with age. The modified expression occurs in cytoskeleton proteins, membranes, synapses, vesicles, myelin, membrane transport and ion channels, DNA and RNA metabolism, ubiquitin-proteasome-system (UPS), kinases and phosphatases, fatty acid metabolism, and mitochondria. Dysregulated phosphoproteins are associated with the cytoskeleton, including microfilaments, actin-binding proteins, intermediate filaments of neurons and glial cells, and microtubules; membrane proteins, synapses, and dense core vesicles; kinases and phosphatases; proteins linked to DNA and RNA; members of the UPS; GTPase regulation; inflammation; and lipid metabolism. Noteworthy, protein levels of large clusters of hierarchically-related protein expression levels are stable until 70. However, protein levels of components of cell membranes, vesicles and synapses, RNA modulation, and cellular structures (including tau and tubulin filaments) are markedly altered from the age of 75. Similarly, marked modifications occur in the larger phosphoprotein clusters involving cytoskeleton and neuronal structures, membrane stabilization, and kinase regulation in the late elderly.Present findings may increase understanding of human brain proteostasis modifications in the elderly in the subpopulation of individuals not having AD neuropathological change and any other neurodegenerative change in any telencephalon region.

JTD Keywords: (phospho)proteomics, cortex, cytoskeleton, hippocampus, kinases, membranes, mitochondria, mitochondrial-function, pathological process, phosphoproteome analysis, phosphorylation, proteome, quantitative proteomics, synapsis, tau-protein, therapeutic target, (phospho)proteomics, Brain aging, Cytoskeleton, Kinases, Membranes, Mitochondria, Neurodegenerative diseases, Proteome, Synapsis

JTD Keywords: deep generative models, eatris european infrastructure for translational medicine, integrative omics, machine learning, multi-omics, personalized medicine, Deep generative models, Eatris european infrastructure for translational medicine, Integrative omics, Machine learning, Multi-omics, Personalized medicine, Protein protein interaction (ppi) network

Transcriptomics and phosphoproteomics were carried out in the cerebral cortex of B6.Cg-Mapttm1(EGFP)Klt (tau knockout: tau-KO) and wild-type (WT) 12 month-old mice to learn about the effects of tau ablation. Compared with WT mice, tau-KO mice displayed reduced anxiety-like behavior and lower fear expression induced by aversive conditioning, whereas recognition memory remained unaltered. Cortical transcriptomic analysis revealed 69 downregulated and 105 upregulated genes in tau-KO mice, corresponding to synaptic structures, neuron cytoskeleton and transport, and extracellular matrix components. RT-qPCR validated increased mRNA levels of col6a4, gabrq, gad1, grm5, grip2, map2, rab8a, tubb3, wnt16, and an absence of map1a in tau-KO mice compared with WT mice. A few proteins were assessed with Western blotting to compare mRNA expression with corresponding protein levels. Map1a mRNA and protein levels decreased. However, β-tubulin III and GAD1 protein levels were reduced in tau-KO mice. Cortical phosphoproteomics revealed 121 hypophosphorylated and 98 hyperphosphorylated proteins in tau-KO mice. Deregulated phosphoproteins were categorized into cytoskeletal (n = 45) and membrane proteins, including proteins of the synapses and vesicles, myelin proteins, and proteins linked to membrane transport and ion channels (n = 84), proteins related to DNA and RNA metabolism (n = 36), proteins connected to the ubiquitin-proteasome system (UPS) (n = 7), proteins with kinase or phosphatase activity (n = 21), and 22 other proteins related to variegated pathways such as metabolic pathways, growth factors, or mitochondrial function or structure. The present observations reveal a complex altered brain transcriptome and phosphoproteome in tau-KO mice with only mild behavioral alterations.

JTD Keywords: computational platform, conformational-changes, cytoskeleton, disease, expression, isoforms, mechanisms, mice, phosphoproteomics, phosphorylation, synapse, tau-ko, tauopathies, transcriptomics, Tau-ko, Tau-protein, Transcriptomics

The etiology of dental caries remains poorly understood. With the advent of next-generation sequencing, a number of studies have focused on the microbial ecology of the disease. However, taxonomic associations with caries have not been consistent. Researchers have also pursued function-centric studies of the caries microbial communities aiming to identify consistently conserved functional pathways. A major question is whether changes in microbiome are a cause or a consequence of the disease. Thus, there is a critical need to define conserved functional signatures at the onset of dental caries.Since it is unethical to induce carious lesions clinically, we developed an innovative longitudinal ex-vivo model integrated with the advanced non-invasive multiphoton second harmonic generation bioimaging to spot the very early signs of dental caries, combined with 16S rRNA short amplicon sequencing and liquid chromatography-mass spectrometry-based targeted metabolomics.For the first time, we induced longitudinally monitored caries lesions validated with the scanning electron microscope. Consequently, we spotted the caries onset and, associated with it, distinguished five differentiating metabolites - Lactate, Pyruvate, Dihydroxyacetone phosphate, Glyceraldehyde 3-phosphate (upregulated) and Fumarate (downregulated). Those metabolites co-occurred with certain bacterial taxa; Streptococcus, Veillonella, Actinomyces, Porphyromonas, Fusobacterium, and Granulicatella, regardless of the abundance of other taxa.These findings are crucial for understanding the etiology and dynamics of dental caries, and devising targeted interventions to prevent disease progression.© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

JTD Keywords: bacteria, biofilms, children, dental caries, generation, genomics, longitudinal model, metabolism, metabolomics, microscopy, non-invasive bioimaging, oral microbiome, plaque, restorations, signatures, Dental caries, Field-emission sem, Signatures

Identification of asymptomatic patients at higher risk for suffering cardiac events remains controversial and challenging in Brugada syndrome (BS). In this work, we proposed an ECG-based classifier to predict BS-related symptoms, by merging the most predictive electrophysiological features derived from the ventricular depolarization and repolarization periods, along with autonomic-related markers. The initial feature space included local and dynamic ECG markers, assessed during a physical exercise test performed in 110 BS patients (25 symptomatic). Morphological, temporal and spatial properties quantifying the ECG dynamic response to exercise and recovery were considered. Our model was obtained by proposing a two-stage feature selection process that combined a resampled-based regularization approach with a wrapper model assessment for balancing, simplicity and performance. For the classification step, an ensemble was constructed by several logistic regression base classifiers, whose outputs were fused using a performance-based weighted average. The most relevant predictors corresponded to the repolarization interval, followed by two autonomic markers and two other makers of depolarization dynamics. Our classifier allowed for the identification of novel symptom-related markers from autonomic and dynamic ECG responses during exercise testing, suggesting the need for multifactorial risk stratification approaches in order to predict future cardiac events in asymptomatic BS patients.

JTD Keywords: brugada syndrome, depolarization disorders, ensemble classifier, heart-rate recovery, Acute myocardial-ischemia, Autonomics, Brugada syndrome, Brugadum syndrome, Cardiac death, Depolarization, Depolarization disorder, Depolarization disorders, Dynamic ecg, Electrocardiography, Electrophysiology, Ensemble classifier, Ensemble-classifier, Events, Exercise, Forecasting, Heart, Heart-rate, Heart-rate recovery, Prognosis, Qrs, Quantification, Recovery, Repolarization, Sudden cardiac death

Introduction and aimsDietary polyphenols have long been associated with health benefits, including the prevention of obesity and related chronic diseases. Overfeeding was shown to rapidly induce weight gain and fat mass, associated with mild insulin resistance in humans, and thus represents a suitable model of the metabolic complications resulting from obesity. We studied the effects of a polyphenol-rich grape extract supplementation on the plasma metabolome during an overfeeding intervention in adults, in two randomized parallel controlled clinical trials.MethodsBlood plasma samples from 40 normal weight to overweight male adults, submitted to a 31-day overfeeding (additional 50% of energy requirement by a high calorie-high fructose diet), given either 2 g/day grape polyphenol extract or a placebo at 0, 15, 21, and 31 days were analyzed (Lyon study). Samples from a similarly designed trial on females (20 subjects) were collected in parallel (Lausanne study). Nuclear magnetic resonance (NMR)-based metabolomics was conducted to characterize metabolome changes induced by overfeeding and associated effects from polyphenol supplementation. The clinical trials are registered under the numbers NCT02145780 and NCT02225457 atResultsChanges in plasma levels of many metabolic markers, including branched chain amino acids (BCAA), ketone bodies and glucose in both placebo as well as upon polyphenol intervention were identified in the Lyon study. Polyphenol supplementation counterbalanced levels of BCAA found to be induced by overfeeding. These results were further corroborated in the Lausanne female study.ConclusionAdministration of grape polyphenol-rich extract over 1 month period was associated with a protective metabolic effect against overfeeding in adults.

JTD Keywords: branched chain amino acids, grape polyphenols, human trials, metabolism, metabolomics, nmr, obesity, Branched chain amino acids, Grape polyphenols, Human trials, Metabolism, Metabolomics, Nmr, Obesity, Overfeeding

The neocortex of P301S mice, used as a model of fronto-temporal lobar degeneration linked to tau mutation (FTLD-tau), and wild-type mice, both aged 9 months, were analyzed with conventional label-free phosphoproteomics and SWATH-MS (sequential window acquisition of all theoretical fragment ion spectra mass spectrometry) to assess the (phospho)proteomes. The total number of identified dysregulated phosphoproteins was 328 corresponding to 524 phosphorylation sites. The majority of dysregulated phosphoproteins, most of them hyperphosphorylated, were proteins of the membranes, synapses, membrane trafficking, membrane vesicles linked to endo- and exocytosis, cytoplasmic vesicles, and cytoskeleton. Another group was composed of kinases. In contrast, proteins linked to DNA, RNA metabolism, RNA splicing, and protein synthesis were hypophosphorylated. Other pathways modulating energy metabolism, cell signaling, Golgi apparatus, carbohydrates, and lipids are also targets of dysregulated protein phosphorylation in P301S mice. The present results, together with accompanying immunohistochemical and Western-blotting studies, show widespread abnormal phosphorylation of proteins, in addition to protein tau, in P301S mice. These observations point to dysregulated protein phosphorylation as a relevant contributory pathogenic component of tauopathies.

JTD Keywords: (phospho)proteomics, cytoskeleton, kinases, membranes, tau, (phospho)proteomics, Cytoskeleton, Kinases, Membranes, Networks, Oxidative stress, Pathology, Phosphoproteome analysis, Tau, Tauopathy

The histone demethylase KDM1A is a multi- faceted regulator of vital developmental processes, including mesodermal and cardiac tube formation during gastrulation. However, it is unknown whether the fine-tuning of KDM1A splicing isoforms, already shown to regulate neuronal maturation, is crucial for the specification and maintenance of cell identity during cardiogenesis. Here, we discovered a temporal modulation of ubKDM1A and KDM1A+2a during human and mice fetal cardiac development and evaluated their impact on the regulation of cardiac differentiation. We revealed a severely impaired cardiac differentiation in KDM1A(-/-) hESCs that can be rescued by re-expressing ubKDM1A or catalytically impaired ubKDM1A-K661A, but not by KDM1A+2a or KDM1A+2a-K661A. Conversely, KDM1A+2a(-/-) hESCs give rise to functional cardiac cells, displaying increased beating amplitude and frequency and enhanced expression of critical cardiogenic markers. Our findings prove the existence of a divergent scaffolding role of KDM1A splice variants, independent of their enzymatic activity, during hESC differentiation into cardiac cells.

JTD Keywords: cell biology, molecular mechanism of gene regulation, omics, Bhlh transcription factor, Corest, Differentiation, Dna, Embryonic stem-cells, Heart, Lsd1, Phosphorylation, Proteins, Stem cells research, Swirm domain

There has been a renewed interest in the potential use of psychedelics for the treatment of psychiatric conditions. Nevertheless, little is known about the mechanism of action and molecular pathways influenced by ayahuasca use in humans. Therefore, for the first time, our study aims to investigate the human metabolomics signature after consumption of a psychedelic, ayahuasca, and its connection with both the psychedelic-induced subjective effects and the plasma concentrations of ayahuasca alkaloids. Plasma samples of 23 individuals were collected both before and after ayahuasca consumption. Samples were analysed through targeted metabolomics and further integrated with subjective ratings of the ayahuasca experience (i.e., using the 5-Dimension Altered States of Consciousness Rating Scale [ASC]), and plasma ayahuasca-alkaloids using integrated network analysis. Metabolic pathways enrichment analysis using diffusion algorithms for specific KEGG modules was performed on the metabolic output. Compared to baseline, the consumption of ayahuasca increased N-acyl-ethanolamine endocannabinoids, decreased 2-acyl-glycerol endocannabinoids, and altered several large-neutral amino acids (LNAAs). Integrated network results indicated that most of the LNAAs were inversely associated with 9 out of the 11 subscales of the ASC, except for tryptophan which was positively associated. Several endocannabinoids and hexosylceramides were directly associated with the ayahuasca alkaloids. Enrichment analysis confirmed dysregulation in several pathways involved in neurotransmission such as serotonin and dopamine synthesis. In conclusion, a crosstalk between the circulating LNAAs and the subjective effects is suggested, which is independent of the alkaloid concentrations and provides insights into the specific metabolic fingerprint and mechanism of action underlying ayahuasca experiences. © 2022 The Authors

JTD Keywords: anxiety, ayahuasca, dimethyltryptamine, integrative network analysis, metabolism, metabolomics, psychedelics, rats, subjective effects, system, tryptophan, Ayahuasca, Dimethyltryptamine, Integrative network analysis, Metabolomics, Psychedelics, Serotonin 5-ht2a, Subjective effects

Formalin-fixed paraffin embedding (FFPE) is the most widespread long-term tissue preservation approach. Here, we report a procedure to perform genome-wide spatial analysis of mRNA in FFPE-fixed tissue sections, using well-established, commercially available methods for imaging and spatial barcoding using slides spotted with barcoded oligo(dT) probes to capture the 3' end of mRNA molecules in tissue sections. We applied this method for expression profiling and cell type mapping in coronal sections from the mouse brain to demonstrate the method's capability to delineate anatomical regions from a molecular perspective. We also profiled the spatial composition of transcriptomic signatures in two ovarian carcinosarcoma samples, exemplifying the method's potential to elucidate molecular mechanisms in heterogeneous clinical samples. Finally, we demonstrate the applicability of the assay to characterize human lung and kidney organoids and a human lung biopsy specimen infected with SARS-CoV-2. We anticipate that genome-wide spatial gene expression profiling in FFPE biospecimens will be used for retrospective analysis of biobank samples, which will facilitate longitudinal studies of biological processes and biomarker discovery.© 2021 The Authors.

JTD Keywords: colonic transit, gut, intestinal motility, ld score regression, metaanalysis, nervous-system, neurotrophic factor, population, severity, Covid-19, Ffpe, Genome-wide, Irritable-bowel-syndrome, Mouse brain, Organoids, Ovarian carcinosarcoma, Pfa, Sars-cov-2, Spatial transcriptomics, Visium

Tau hyperphosphorylation is the first step of neurofibrillary tangle (NFT) formation. In the present study, samples of the entorhinal cortex (EC) and frontal cortex area 8 (FC) of cases with NFT pathology classified as stages I–II, III–IV, and V–VI without comorbidities, and of middle-aged (MA) individuals with no NFT pathology, were analyzed by conventional label-free and SWATH-MS (sequential window acquisition of all theoretical fragment ion spectra mass spectrometry) to assess the (phospho)proteomes. The total number of identified dysregulated phosphoproteins was 214 in the EC, 65 of which were dysregulated at the first stages (I–II) of NFT pathology; 167 phosphoproteins were dysregulated in the FC, 81 of them at stages I–II of NFT pathology. A large percentage of dysregulated phosphoproteins were identified in the two regions and at different stages of NFT progression. The main group of dysregulated phosphoproteins was made up of components of the membranes, cytoskeleton, synapses, proteins linked to membrane transport and ion channels, and kinases. The present results show abnormal phosphorylation of proteins at the first stages of NFT pathology in the elderly (in individuals clinically considered representative of normal aging) and sporadic Alzheimer's disease (sAD). Dysregulated protein phosphorylation in the FC precedes the formation of NFTs and SPs. The most active period of dysregulated phosphorylation is at stages III–IV when a subpopulation of individuals might be clinically categorized as suffering from mild cognitive impairment which is a preceding determinant stage in the progression to dementia. Altered phosphorylation of selected proteins, carried out by activation of several kinases, may alter membrane and cytoskeletal functions, among them synaptic transmission and membrane/cytoskeleton signaling. Besides their implications in sAD, the present observations suggest a molecular substrate for “benign” cognitive deterioration in “normal” brain aging.

JTD Keywords: (phospho)proteomics, alzheimer's disease, amyloid-beta, association guidelines, brain aging, cytoskeleton, frontal-cortex, kinases, lipid rafts, membranes, national institute, neuropathologic assessment, pathological process, protein phosphorylation, synapse pathology, synapses, tau, tau pathology, (phospho)proteomics, Age-related tauopathy, Alzheimer's disease, Brain aging, Cytoskeleton, Kinases, Membranes, Protein phosphorylation, Synapses, Tau

To increase compliance with colorectal cancer screening programs and to reduce the recommended screening age, cheaper and easy non‐invasiveness alternatives to the fecal immunochemical test should be provided. Following the PRISMA procedure of studies that evaluated the metabolome and volatilome signatures of colorectal cancer in human urine samples, an exhaustive search in PubMed, Web of Science, and Scopus found 28 studies that met the required criteria. There were no restrictions on the query for the type of study, leading to not only colorectal cancer samples versus control comparison but also polyps versus control and prospective studies of surgical effects, CRC staging and comparisons of CRC with other cancers. With this systematic review, we identified up to 244 compounds in urine samples (3 shared compounds between the volatilome and metabolome), and 10 of them were relevant in more than three articles. In the meta-analysis, nine studies met the criteria for inclusion, and the results combining the case‐control and the pre‐/post‐surgery groups, eleven compounds were found to be relevant. Four upregulated metabolites were identified, 3‐hydroxybutyric acid, L‐dopa, L‐histidinol, and N1, N12‐ diacetylspermine and seven downregulated compounds were identified, pyruvic acid, hydroquinone, tartaric acid, and hippuric acid as metabolites and butyraldehyde, ether, and 1,1,6‐ trimethyl‐1,2‐dihydronaphthalene as volatiles.

JTD Keywords: biomarkers, breast, chromatography, colorectal cancer, diagnosis, markers, meta-analysis, metabolomics, metabonomics, n-1,n-12-diacetylspermine, nucleosides, systematic review, urine, validation, volatilomics, Colorectal cancer, Early-stage, Metabolomics, Meta‐analysis, Systematic review, Urine, Volatilomics

Plaques of the amyloid beta (A beta) peptide are a pathological hallmark of Alzheimer's disease (AD), the most common form of dementia. Mutations in A beta also cause familial forms of AD (fAD). Here, we use deep mutational scanning to quantify the effects of >14,000 mutations on the aggregation of A beta. The resulting genetic landscape reveals mechanistic insights into fibril nucleation, including the importance of charge and gatekeeper residues in the disordered region outside of the amyloid core in preventing nucleation. Strikingly, unlike computational predictors and previous measurements, the empirical nucleation scores accurately identify all known dominant fAD mutations in A beta, genetically validating that the mechanism of nucleation in a cell-based assay is likely to be very similar to the mechanism that causes the human disease. These results provide the first comprehensive atlas of how mutations alter the formation of any amyloid fibril and a resource for the interpretation of genetic variation in A beta.

JTD Keywords: aggregation, kinetics, oligomers, onset, rates, state, Aggregation, Alzheimer disease, Alzheimer's, Amyloid, Amyloid beta-peptides, Computational biology, Deep mutagenesis, Dna mutational analysis, Genetics, Genomics, High-throughput nucleotide sequencing, Kinetics, Mutation, Nucleation, Oligomers, Onset, Plasmids, Precursor protein, Rates, S. cerevisiae, Saccharomyces cerevisiae, State, Systems biology

Gene duplications are a feature of bacterial genomes. In the present work we analyze the extent of gene duplications in the genomes of three microorganisms that belong to the Firmicutes phylum and that are etiologic agents of several nosocomial infections: Staphylococcus aureus, Enterococcus faecium, and Enterococcus faecalis. In all three groups, there is an irregular distribution of duplications in the genomes of the strains analyzed. Whereas in some of the strains duplications are scarce, hundreds of duplications are present in others. In all three species, mobile DNA accounts for a large percentage of the duplicated genes: phage DNA in S. aureus, and plasmid DNA in the enterococci. Duplicates also include core genes. In all three species, a reduced group of genes is duplicated in all strains analyzed. Duplication of the deoC and rpmG genes is a hallmark of S. aureus genomes. Duplication of the gene encoding the PTS IIB subunit is detected in all enterococci genomes. In E. faecalis it is remarkable that the genomes of some strains encode duplicates of the prgB and prgU genes. They belong to the prgABCU cluster, which responds to the presence of the peptide pheromone cCF10 by expressing the surface adhesins PrgA, PrgB, and PrgC.

JTD Keywords: Bacterial genomics, Enterococcus faecalis, Enterococcus faecium, Gene duplication, Staphylococcus aureus

Rice is a staple food of more than half of the world’s population; more than 3.5 billion inhabitants depend on rice for obtaining 20% of their daily calorie intake. Nitrogen is the most important for crop growth and yield potential. Indeed, nitrogen is essential to stimulate tillering, leaf growth, photosynthesis, and protein synthesis. Significant achievements have recently been observed at the molecular level in nitrogen use efficiency and water use efficiency in plants. In this chapter we will discuss the following issue: (i) definition of both nitrogen use efficiency and water use efficiency, (ii) genes responsible for nitrogen use efficiency and water use efficiency, (iii) best ways for improving water and nutrient use efficiency in rice, and (iv) optimizing nitrogen options for improving water and nitrogen use efficiency of rice under different water regimes.

JTD Keywords: Rice, Water use efficiency, Nitrogen use efficiency, Breeding, Genomics approaches

Insoluble protein aggregates are the hallmarks of many neurodegenerative diseases. For example, aggregates of TDP-43 occur in nearly all cases of amyotrophic lateral sclerosis (ALS). However, whether aggregates cause cellular toxicity is still not clear, even in simpler cellular systems. We reasoned that deep mutagenesis might be a powerful approach to disentangle the relationship between aggregation and toxicity. We generated >50,000 mutations in the prion-like domain (PRD) of TDP-43 and quantified their toxicity in yeast cells. Surprisingly, mutations that increase hydrophobicity and aggregation strongly decrease toxicity. In contrast, toxic variants promote the formation of dynamic liquid-like condensates. Mutations have their strongest effects in a hotspot that genetic interactions reveal to be structured in vivo, illustrating how mutagenesis can probe the in vivo structures of unstructured proteins. Our results show that aggregation of TDP-43 is not harmful but protects cells, most likely by titrating the protein away from a toxic liquid-like phase.

JTD Keywords: Computational biology and bioinformatics, Genomics, Mechanisms of disease, Neurodegeneration, Systems biology

Advances in analytical instrumentation have provided the possibility of examining thousands of genes, peptides, or metabolites in parallel. However, the cost and time-consuming data acquisition process causes a generalized lack of samples. From a data analysis perspective, omics data are characterized by high dimensionality and small sample counts. In many scenarios, the analytical aim is to differentiate between two different conditions or classes combining an analytical method plus a tailored qualitative predictive model using available examples collected in a dataset. For this purpose, partial least squares-discriminant analysis (PLS-DA) is frequently employed in omics research. Recently, there has been growing concern about the uncritical use of this method, since it is prone to overfitting and may aggravate problems of false discoveries. In many applications involving a small number of subjects or samples, predictive model performance estimation is only based on cross-validation (CV) results with a strong preference for reporting results using leave one out (LOO). The combination of PLS-DA for high dimensionality data and small sample conditions, together with a weak validation methodology is a recipe for unreliable estimations of model performance. In this work, we present a systematic study about the impact of the dataset size, the dimensionality, and the CV technique used on PLS-DA overoptimism when performance estimation is done in cross-validation. Firstly, by using synthetic data generated from a same probability distribution and with assigned random binary labels, we have obtained a dataset where the true classification rate (CR) is 50%. As expected, our results confirm that internal validation provides overoptimistic estimations of the classification accuracy (i.e., overfitting). We have characterized the CR estimator in terms of bias and variance depending on the internal CV technique used and sample to dimensionality ratio. In small sample conditions, due to the large bias and variance of the estimator, the occurrence of extremely good CRs is common. We have found that overfitting peaks when the sample size in the training subset approaches the feature vector dimensionality minus one. In these conditions, the models are neither under- or overdetermined with a unique solution. This effect is particularly intense for LOO and peaks higher in small sample conditions. Overoptimism is decreased beyond this point where the abundance of noisy produces a regularization effect leading to less complex models. In terms of overfitting, our study ranks CV methods as follows: Bootstrap produces the most accurate estimator of the CR, followed by bootstrapped Latin partitions, random subsampling, K-Fold, and finally, the very popular LOO provides the worst results. Simulation results are further confirmed in real datasets from mass spectrometry and microarrays.

JTD Keywords: Metabolomics, Mass spectrometry, Microarrays, Chemometrics, Data analysis, Classification, Method validation

The quality and composition of bitter orange essential oils (EOs) strongly depend on the ripening stage of the citrus fruit. The concentration of volatile compounds and consequently its organoleptic perception varies. While this can be detected by trained humans, we propose an objective approach for assessing the bitter orange from the volatile composition of their EO. The method is based on the combined use of headspace gas chromatography–mass spectrometry (HS-GC-MS) and artificial neural networks (ANN) for predictive modeling. Data obtained from the analysis of HS-GC-MS were preprocessed to select relevant peaks in the total ion chromatogram as input features for ANN. Results showed that key volatile compounds have enough predictive power to accurately classify the EO, according to their ripening stage for different applications. A sensitivity analysis detected the key compounds to identify the ripening stage. This study provides a novel strategy for the quality control of bitter orange EO without subjective methods.

JTD Keywords: Bitter orange essential oil, Headspace gas chromatography–mass spectrometry, Artificial neural network, Foodomics, Chemometrics, Feature selection

Purpose : The nutritional intervention program “DiOGenes” focuses on how obesity can be prevented and treated from a dietary perspective. We generated differential plasma proteome profiles in the DiOGenes cohort to identify proteins associated with weight loss and maintenance and explore their relation to body mass index, fat mass, insulin resistance and sensitivity. Experimental Design : Relative protein quantification was obtained at baseline and after combined weight loss/maintenance phases using isobaric tagging and MS/MS. A Welch t-test determined proteins differentially present after intervention. Protein relationships with clinical variables were explored using univariate linear models, considering collection center, gender and age as confounding factors. Results : 473 subjects were measured at baseline and end of the intervention; 39 proteins were longitudinally differential. Proteins with largest changes were sex hormone-binding globulin, adiponectin, C-reactive protein, calprotectin, serum amyloid A, and proteoglycan 4 (PRG4), whose association with obesity and weight loss is known. We identified new putative biomarkers for weight loss/maintenance. Correlation between PRG4 and proline-rich acidic protein 1 (PRAP1) variation and Matsuda insulin sensitivity increment was showed. Conclusions and Clinical Relevance : MS-based proteomic analysis of a large cohort of non-diabetic overweight and obese individuals concomitantly identified known and novel proteins associated with weight loss and maintenance.

JTD Keywords: Biomarker, Diabetes, Large-scale study, Mass spectrometry, Obesity, Proteomics

The authors present an introductory work for the implementation of an international cooperative project aimed at designing, developing and validating a new generation of ergonomic robotic suits, wearable by the users and controlled by the human brain. The aim of the proposers is to allow the motion of people affected by paralysis or with reduced motor abilities. Therefore, the project will focus on the fusion between neuroergonomics and robotics, also by means of brain-machine interfaces. Breakthrough solutions will compose the advanced robotic suit, endowed with soft structures to increment safety and human comfort, and with an advanced real-time control that takes into account the interaction with the human body.

JTD Keywords: Neuroergonomics, Brain computer interfaces, Robotics, Robotic suits, Compliant actuators, Exoskeleton, EEG, Dynamic balance control