Sci Rep. 2024 Dec 28;14(1):30885. doi: 10.1038/s41598-024-81866-1.

ABSTRACT

Personalized medicine aims to tailor medical treatments to individual patients, and predicting drug responses from molecular profiles using machine learning is crucial for this goal. However, the high dimensionality of the molecular profiles compared to the limited number of samples presents significant challenges. Knowledge-based feature selection methods are particularly suitable for drug response prediction, as they leverage biological insights to reduce dimensionality and improve model interpretability. This study presents the first comparative evaluation of nine different knowledge-based and data-driven feature reduction methods on cell line and tumor data. Our analysis employs six distinct machine learning models, with a total of more than 6,000 runs to ensure a robust evaluation. Our findings indicate that transcription factor activities outperform other methods in predicting drug responses, effectively distinguishing between sensitive and resistant tumors for seven of the 20 drugs evaluated.

PMID:39730699 | DOI:10.1038/s41598-024-81866-1

Nat Commun. 2024 Dec 27;15(1):10726. doi: 10.1038/s41467-024-55388-3.

ABSTRACT

Immune checkpoint blockade (ICB) has become a standard anti-cancer treatment, offering durable clinical benefits. However, the limited response rate of ICB necessitates biomarkers to predict and modulate the efficacy of the therapy. The gut microbiome's influence on ICB efficacy is of particular interest due to its modifiability through various interventions. However, gut microbiome biomarkers for ICB response have been inconsistent across different studies. Here, we identify TANB77, an uncultured and distinct bacterial clade, as the most consistent responder-enriched taxon through meta-analysis of ten independent ICB recipient cohorts. Traditional taxonomy fails to distinguish TANB77 from unrelated taxa, leading to its oversight. Mice with higher gut TANB77 abundance, either naturally or through transplantation, show improved response to anti-PD-1 therapy. Additionally, mice injected with TANB77-derived pilin-like protein exhibit improved anti-PD-1 therapy response, providing in vivo evidence for the beneficial role of the pilin-like protein. These findings suggest that pilins from the TANB77 order may enhance responses to ICB therapy across diverse cohorts of cancer patients.

PMID:39730328 | DOI:10.1038/s41467-024-55388-3

Transl Psychiatry. 2024 Dec 27;14(1):506. doi: 10.1038/s41398-024-03216-z.

ABSTRACT

The high comorbidity of major depressive disorder (MDD) with other diseases has been well-documented. However, the pairwise causal connections for MDD comorbid networks are poorly characterized. We performed Phenome-wide Mendelian randomization (MR) analyses to explore bidirectional causal associations between MDD (N = 807,553) and 877 common diseases from FinnGen datasets (N = 377,277). The inverse variance weighting method was the primary technique, and other methods (weighted median and MR-Egger) were used for sensitivity analyses. Our MR analyses showed that the genetic liability to MDD is causally associated with the risks of 324 disease phenotypes (average b: 0.339), including 46 psychiatric and behavioral disorders (average b: 0.618), 18 neurological diseases (average b: 0.348), 44 respiratory diseases (average b: 0.345), 40 digestive diseases (average b: 0.281), 18 circulatory diseases (average b: 0.237), 37 genitourinary diseases (average b: 0.271), 66 musculoskeletal and connective diseases (average b: 0.326), 22 endocrine diseases (average b: 0.302), and others. In a reverse analysis, a total of 51 genetic components predisposing to various diseases were causally associated with MDD risk (average b: 0.086), including 5 infectious diseases (average b: 0.056), 11 neurological diseases (average b: 0.106), 14 oncological diseases (average b: 0.108), and 5 psychiatric and behavioral disorders (average b: 0.114). Bidirectional causal associations were identified between MDD and 15 diseases. For most MR analyses, little evidence of heterogeneity and pleiotropy was detected. Our findings confirmed the extensive and significant causal role of genetic predisposition to MDD in contributing to human disease phenotypes, which were more pronounced than those seen in the reverse analysis of the causal influences of other diseases on MDD.

PMID:39730323 | DOI:10.1038/s41398-024-03216-z

Cell Rep Methods. 2024 Dec 20:100937. doi: 10.1016/j.crmeth.2024.100937. Online ahead of print.

ABSTRACT

Spatially resolved transcriptomics (ST) has revolutionized the field of biology by providing a powerful tool for analyzing gene expression in situ. However, current ST methods, particularly barcode-based methods, have limitations in reconstructing high-resolution images from barcodes sparsely distributed in slides. Here, we present SuperST, an algorithm that enables the reconstruction of dense matrices (higher-resolution and non-zero-inflated matrices) from low-resolution ST libraries. SuperST is based on deep image prior, which reconstructs spatial gene expression patterns as image matrices. Compared with previous methods, SuperST generated output images that more closely resembled immunofluorescence images for given gene expression maps. Furthermore, we demonstrated how one can combine images created by SuperST with computer vision algorithms. In this context, we proposed a method for extracting features from the images, which can aid in spatial clustering of genes. By providing a dense matrix for each gene in situ, SuperST can successfully address the resolution and zero-inflation issue.

PMID:39729996 | DOI:10.1016/j.crmeth.2024.100937

Mol Cell. 2024 Dec 19:S1097-2765(24)00993-6. doi: 10.1016/j.molcel.2024.11.038. Online ahead of print.

ABSTRACT

Changing environmental conditions necessitate rapid adaptation of cytoplasmic and nuclear volumes. We use the slime mold Dictyostelium discoideum, known for its ability to tolerate extreme changes in osmolarity, to assess which role nuclear pore complexes (NPCs) play in achieving nuclear volume adaptation and relieving mechanical stress. We capitalize on the unique properties of D. discoideum to quantify fluid flow across NPCs. D. discoideum has an elaborate NPC structure in situ. Its dilation state affects NPC permeability for nucleocytosolic flow. Based on mathematical concepts adapted from hydrodynamics, we conceptualize this phenomenon as porous flow across NPCs, which is distinct from canonically characterized modes of nucleocytoplasmic transport because of its dependence on pressure. Viral NPC blockage decreased nucleocytosolic flow. Our results may be relevant for any biological conditions that entail rapid nuclear size adaptation, including metastasizing cancer cells, migrating cells, or differentiating tissues.

PMID:39729993 | DOI:10.1016/j.molcel.2024.11.038

Dev Cell. 2024 Dec 19:S1534-5807(24)00722-6. doi: 10.1016/j.devcel.2024.11.022. Online ahead of print.

ABSTRACT

Two distinct lineages, pluripotent epiblast (EPI) and primitive (extra-embryonic) endoderm (PrE), arise from common inner cell mass (ICM) progenitors in mammalian embryos. To study how these sister identities are forged, we leveraged mouse embryonic stem (ES) cells and extra-embryonic endoderm (XEN) stem cells-in vitro counterparts of the EPI and PrE. Bidirectional reprogramming between ES and XEN coupled with single-cell RNA and ATAC-seq analyses showed distinct rates, efficiencies, and trajectories of state conversions, identifying drivers and roadblocks of reciprocal conversions. While GATA4-mediated ES-to-iXEN conversion was rapid and nearly deterministic, OCT4-, KLF4-, and SOX2-induced XEN-to-induced pluripotent stem (iPS) reprogramming progressed with diminished efficiency and kinetics. A dominant PrE transcriptional program, safeguarded by GATA4, alongside elevated chromatin accessibility and reduced DNA methylation of the EPI underscored the differential plasticities of the two states. Mapping in vitro to embryo trajectories tracked reprogramming cells in either direction along EPI and PrE in vivo states, without transitioning through the ICM.

PMID:39729987 | DOI:10.1016/j.devcel.2024.11.022

Mol Oncol. 2024 Dec 27. doi: 10.1002/1878-0261.13762. Online ahead of print.

ABSTRACT

Hypoxia is known to induce reprogramming of glucose metabolism in cancer. However, the impact of hypoxia on global metabolism remains poorly understood. Here, using the systems approach, we evaluated the potential crosstalk between hypoxia and global metabolism using data from > 2000 breast tumors. Tumor samples were scored for hypoxia and 90 metabolic pathways, and these metrics were subjected to an analysis pipeline. Hypoxia showed a very strong association with metabolic aggression and an overall contextual relationship with metabolism. Out of three (M1, M2, and M3) metabolic types in breast cancer, M3 exhibited the strongest relationship with hypoxia; that is, high hypoxic tumors were also metabolically deregulated. Further, the overall correlation pattern between hypoxia and metabolic pathway scores was specific to each type, with M1 showing maximal sensitivity to hypoxia, followed by M2 and then M3. Experimental validation using metabolic inhibitors on cell lines with high or low hypoxia scores further confirmed the metabolic type-dependence of hypoxia. In addition, evaluation of the impact of hypoxia on cancer pathways other than metabolic ones revealed a potential role of hypoxia in immune evasive characteristic of M3 tumors. Overall, the results suggest a complex interplay between hypoxia and metabolism in the context of human breast tumors, with potential implications for both basic cancer biology and breast cancer therapy.

PMID:39729399 | DOI:10.1002/1878-0261.13762

Elife. 2024 Dec 27;13:RP97350. doi: 10.7554/eLife.97350.

ABSTRACT

As pathogens spread in a population of hosts, immunity is built up, and the pool of susceptible individuals are depleted. This generates selective pressure, to which many human RNA viruses, such as influenza virus or SARS-CoV-2, respond with rapid antigenic evolution and frequent emergence of immune evasive variants. However, the host's immune systems adapt, and older immune responses wane, such that escape variants only enjoy a growth advantage for a limited time. If variant growth dynamics and reshaping of host-immunity operate on comparable time scales, viral adaptation is determined by eco-evolutionary interactions that are not captured by models of rapid evolution in a fixed environment. Here, we use a Susceptible/Infected model to describe the interaction between an evolving viral population in a dynamic but immunologically diverse host population. We show that depending on strain cross-immunity, heterogeneity of the host population, and durability of immune responses, escape variants initially grow exponentially, but lose their growth advantage before reaching high frequencies. Their subsequent dynamics follows an anomalous random walk determined by future escape variants and results in variant trajectories that are unpredictable. This model can explain the apparent contradiction between the clearly adaptive nature of antigenic evolution and the quasi-neutral dynamics of high-frequency variants observed for influenza viruses.

PMID:39728926 | DOI:10.7554/eLife.97350

Toxins (Basel). 2024 Dec 2;16(12):519. doi: 10.3390/toxins16120519.

ABSTRACT

The intricate combination of organic and inorganic compounds found in snake venom includes proteins, peptides, lipids, carbohydrates, nucleotides, and metal ions. These components work together to immobilise and consume prey through processes such as paralysis and hypotension. Proteins, both enzymatic and non-enzymatic, form the primary components of the venom. Based on the effects they produce, venom can be classified as neurotoxic, hemotoxic, and cytotoxic. Studies have shown that, after envenomation, proteins in snake venom also contribute significantly to the induction of inflammatory responses which can either have systemic or localized consequences. This review delves into the mechanisms by which snake venom proteins trigger inflammatory responses, focusing on key families such as phospholipase A2, metalloproteinases, serine proteases, C-type lectins, cysteine-rich secretory proteins, and L-amino acid oxidase. In addition, the role of venom proteins in activating various inflammatory pathways, including the complement system, inflammasomes, and sterile inflammation are also summarized. The available therapeutic options are examined, with a focus on antivenom therapy and its side effects. In general, this review offers a comprehensive understanding of the inflammatory mechanisms that are triggered by snake venom proteins and the side effects of antivenom treatment. All these emphasize the need for effective strategies to mitigate these detrimental effects.

PMID:39728777 | DOI:10.3390/toxins16120519

Metabolites. 2024 Dec 19;14(12):714. doi: 10.3390/metabo14120714.

ABSTRACT

Background: As the burden of Alzheimer's disease (AD) escalates with an ageing population, the demand for early and accessible diagnostic methods becomes increasingly urgent. Saliva, with its non-invasive and cost-effective nature, presents a promising alternative to cerebrospinal fluid and plasma for biomarker discovery. Methods: In this study, we conducted a comprehensive multi-omics analysis of saliva samples (n = 20 mild cognitive impairment (MCI), n = 20 Alzheimer's disease and age- and n = 40 gender-matched cognitively normal individuals), from the South Australian Neurodegenerative Disease (SAND) cohort, integrating proteomics, metabolomics, and microbiome data with plasma measurements, including pTau181. Results: Among the most promising findings, the protein Stratifin emerged as a top candidate, showing a strong negative correlation with plasma pTau181 (r = -0.49, p < 0.001) and achieving an AUC of 0.95 in distinguishing AD and MCI combined from controls. In the metabolomics analysis, 3-chlorotyrosine and L-tyrosine exhibited high correlations with disease severity progression, with AUCs of 0.93 and 0.96, respectively. Pathway analysis revealed significant alterations in vitamin B12 metabolism, with Transcobalamin-1 levels decreasing in saliva as AD progressed despite an increase in serum vitamin B12 levels (p = 0.008). Microbiome analysis identified shifts in bacterial composition, with a microbiome cluster containing species such as Lautropia mirabilis showing a significant decrease in abundance in MCI and AD samples. The overall findings were reinforced by weighted correlation network analysis, which identified key hubs and enriched pathways associated with AD. Conclusions: Collectively, these data highlight the potential of saliva as a powerful medium for early AD diagnosis, offering a practical solution for large-scale screening and monitoring.

PMID:39728495 | DOI:10.3390/metabo14120714

Metabolites. 2024 Dec 2;14(12):670. doi: 10.3390/metabo14120670.

ABSTRACT

Background: Diabetic encephalopathy (DE) is a neurological complication of diabetes marked by cognitive decline and complex metabolic disturbances. Salidroside (SAL), a natural compound with antioxidant and neuroprotective properties, has shown promise in alleviating diabetic complications. Exploring the spatial metabolic reprogramming in DE and elucidating SAL's metabolic effects are critical for deepening our understanding of its pathogenesis and developing effective therapeutic strategies. Methods: Air-flow-assisted desorption electrospray ionization-mass spectrometry imaging (AFADESI-MSI) was employed to investigate spatial metabolic alterations in the brains of db/db mice, a spontaneous DE model. The mice were treated with SAL (30 and 150 mg/kg, orally) for 12 weeks. Differential metabolites were identified and characterized using high-resolution mass spectrometry and validated against public databases. Results: Our AFADESI-MSI analysis revealed significant changes in 26 metabolites in the brains of DE mice compared to the controls. These metabolic changes indicated disruptions in glucose, glutamate-glutamine, nucleotide, lipid, choline, aspartate, and L-carnitine metabolism. Notably, glucose 6-phosphate (G6P), glutamine, adenosine, L-carnitine, and choline exhibited similar trends in both db/db mice and STZ-induced rat models of DE, suggesting their potential as reliable biomarkers. Twelve weeks of SAL treatment demonstrated a positive regulatory effect on glucose metabolism, the glutamate-glutamine cycle, and lipid metabolism. Conclusions: This study identifies key metabolic alterations in DE and demonstrates the therapeutic potential of SAL in modulating these disturbances, offering valuable insights for targeted interventions in diabetic complications.

PMID:39728451 | DOI:10.3390/metabo14120670

Curr Issues Mol Biol. 2024 Nov 29;46(12):13583-13606. doi: 10.3390/cimb46120812.

ABSTRACT

Neurological disorders such as Autism Spectrum Disorder (ASD), Schizophrenia (SCH), Bipolar Disorder (BD), and Major Depressive Disorder (MDD) affect millions of people worldwide, yet their molecular mechanisms remain poorly understood. This study describes the application of the Comparative Analysis of Shapley values (CASh) to transcriptomic data from nine datasets associated with these complex disorders, demonstrating its effectiveness in identifying differentially expressed genes (DEGs). CASh, which combines Game Theory with Bootstrap resampling, offers a robust alternative to traditional statistical methods by assessing the contribution of each gene in the broader context of the complete dataset. Unlike conventional approaches, CASh is highly effective at detecting subtle but meaningful molecular patterns that are often missed. These findings highlight the potential of CASh to enhance the precision of transcriptomic analysis, providing a deeper understanding of the molecular mechanisms underlying these disorders and establishing a solid basis to improve diagnostic techniques and developing more targeted therapeutic interventions.

PMID:39727940 | DOI:10.3390/cimb46120812

Microbiol Resour Announc. 2024 Dec 27:e0100124. doi: 10.1128/mra.01001-24. Online ahead of print.

ABSTRACT

Here, we present amplicon sequences from sourdough starter cultures that have been treated with a chlorine concentration gradient mirroring public water distribution systems. Data derived present insights into the effect of important environmental factors that may influence the formation of microbial communities in food biomes.

PMID:39727394 | DOI:10.1128/mra.01001-24

Genetics. 2024 Dec 27:iyae208. doi: 10.1093/genetics/iyae208. Online ahead of print.

ABSTRACT

Expansion of nucleotide repeat sequences is associated with more than 40 human neuromuscular disorders. The different pathogenic mechanisms associated with the expression of nucleotide repeats are not well understood. We use a Caenorhabditis elegans model that expresses expanded CUG repeats only in cells of the body wall muscle and recapitulate muscle dysfunction and impaired organismal motility to identify the basis by which expression of RNA repeats is toxic to muscle function. Here, we performed 2 consecutive RNA interference screens and uncovered coenzyme Q metabolism and mitochondrial dysfunction as critical genetic modifiers of the motility phenotype. Furthermore, coenzyme Q supplementation reduced the toxic phenotypes, ameliorating the motility impairment and mitochondrial phenotypes. Together our data show how the expression of expanded RNA repeats can be toxic to mitochondrial homeostasis.

PMID:39727349 | DOI:10.1093/genetics/iyae208

CPT Pharmacometrics Syst Pharmacol. 2024 Dec 27. doi: 10.1002/psp4.13296. Online ahead of print.

ABSTRACT

Type 2 diabetes mellitus (T2DM), characterized by insulin resistance, is closely associated with Alzheimer's disease (AD). Cerebrovascular dysfunction is manifested in both T2DM and AD, and is often considered as a pathological link between the two diseases. Insulin signaling regulates critical functions of the blood-brain barrier (BBB), and endothelial insulin resistance could lead to BBB dysfunction, aggravating AD pathology. However, insulin signaling is intrinsically dynamic and involves interactions among numerous molecular mediators. Hence, a mechanistic systems biology model is needed to understand how insulin regulates BBB physiology and the consequences of its impairment in T2DM and AD. In this study, we investigated the pharmacodynamic effect of insulin on the expression of vascular cell adhesion molecule 1 (VCAM1), a marker of cerebrovascular inflammation. Intriguingly, normal insulin concentrations selectively activated the PI3K-AKT pathway, leading to decreased VCAM1 expression. However, exposure to supraphysiological insulin levels, which is present in insulin resistance, activated both PI3K-AKT and MEK-ERK pathways, and increased VCAM1 expression. We developed a mathematical model that adequately described the dynamics of various insulin signaling nodes and VCAM1 expression. Further, the model was integrated with in vitro proteomics and transcriptomics data from AD patients to simulate VCAM1 expression under pathological conditions. This approach allowed us to establish a quantitative systems pharmacology framework to investigate BBB dysfunction in AD and metabolic syndrome, thereby offering opportunities to identify specific disruptions in molecular networks that will enable us to identify novel therapeutic targets.

PMID:39727246 | DOI:10.1002/psp4.13296

Front Nutr. 2024 Dec 12;11:1479501. doi: 10.3389/fnut.2024.1479501. eCollection 2024.

ABSTRACT

INTRODUCTION: Disease-related malnutrition is common but often underdiagnosed in patients with chronic gastrointestinal diseases, such as liver cirrhosis, short bowel and intestinal insufficiency, and chronic pancreatitis. To improve malnutrition diagnosis in these patients, an evaluation of the current Global Leadership Initiative on Malnutrition (GLIM) diagnostic criteria, and possibly the implementation of additional criteria, is needed.

AIM: This study aimed to identify previously unknown and potentially specific features of malnutrition in patients with different chronic gastrointestinal diseases and to validate the relevance of the GLIM criteria for clinical practice using machine learning (ML).

METHODS: Between 10/2018 and 09/2021, n = 314 patients and controls were prospectively enrolled in a cross-sectional study. A total of n = 230 features (anthropometric data, body composition, handgrip strength, gait speed, laboratory values, dietary habits, physical activity, mental health) were recorded. After data preprocessing (cleaning, feature exploration, imputation of missing data), n = 135 features were included in the ML analyses. Supervised ML models were used to classify malnutrition, and key features were identified using SHapley Additive exPlanations (SHAP).

RESULTS: Supervised ML effectively classified malnourished versus non-malnourished patients and controls. Excluding the existing GLIM criteria and malnutrition risk reduced model performance (sensitivity -19%, specificity -8%, F1-score -10%), highlighting their significance. Besides some GLIM criteria (weight loss, reduced food intake, disease/inflammation), additional anthropometric (hip and upper arm circumference), body composition (phase angle, SMMI), and laboratory markers (albumin, pseudocholinesterase, prealbumin) were key features for malnutrition classification.

CONCLUSION: ML analysis confirmed the clinical applicability of the current GLIM criteria and identified additional features that may improve malnutrition diagnosis and understanding of the pathophysiology of malnutrition in chronic gastrointestinal diseases.

PMID:39726873 | PMC:PMC11670747 | DOI:10.3389/fnut.2024.1479501

J Exp Bot. 2024 Dec 27:erae514. doi: 10.1093/jxb/erae514. Online ahead of print.

ABSTRACT

In aerobic life forms, reactive oxygen species (ROS) are produced by the partial reduction of oxygen during energy-generating metabolic processes. In plants, ROS production increases during periods of both abiotic and biotic stress, severely overloading the antioxidant systems. Hydrogen peroxide (H2O2) plays a central role in cellular redox homeostasis and signaling by oxidising crucial cysteines to sulfenic acid, which is considered a biologically relevant post-translational modification (PTM). Until now, the impact of the nucleus on cellular redox homeostasis has been relatively unexplored. The regulation of histone-modifying enzymes by oxidative PTMs at redox-sensitive cysteine or tyrosine residues is particularly intriguing because it allows the integration of redox signaling mechanisms with chromatin control of transcriptional activity. One of the most extensively studied histone acetyltransferases is the conserved GENERAL CONTROL NONDEPRESSIBLE 5 (GCN5) complex. This study investigated the nuclear sulfenome in Arabidopsis thaliana by expressing a nuclear variant of the Yeast Activation Protein-1 (YAP1) probe and identified 225 potential redox-active proteins undergoing S-sulfenylation. Mass spectrometry analysis further confirmed the S-sulfenylation of GCN5 at cysteines 293, 368, and 400, and their functional significance and impact on the GCN5 protein-protein interaction network were assessed using cysteine-to-serine mutagenesis.

PMID:39726278 | DOI:10.1093/jxb/erae514

BMC Plant Biol. 2024 Dec 27;24(1):1258. doi: 10.1186/s12870-024-05897-6.

ABSTRACT

Pre-harvest sprouting (PHS) in groundnut leads to substantial yield losses and reduced seed quality, resulting in reduced market value of groundnuts. Breeding cultivars with 14-21 days of fresh seed dormancy (FSD) holds promise for precisely mitigating the yield and quality deterioration. In view of this, six multi-locus genome-wide association study (ML-GWAS) models alongside a single-locus GWAS (SL-GWAS) model were employed on a groundnut mini-core collection using multi season phenotyping and 58 K "Axiom_Arachis" array genotyping data. A total of 9 significant SNP-trait associations (STAs) for FSD were detected on A01, A04, A08, A09, B02, B04, B05, B07 and B09 chromosomes using six ML-GWAS models. Additionally, the SL-GWAS model identified 38 STAs across 14 chromosomes of groundnut. A single STA on chromosome B02 (qFSD-B02-1) was consistently identified in both ML-GWAS and SL-GWAS models. Furthermore, candidate gene mining identified nine high confidence genes viz., Cytochrome P450 705 A, Dormancy/auxin associated family protein, WRKY family transcription factor, Protein kinase superfamily protein, serine/threonine protein phosphatase, myb transcription factor, transcriptional regulator STERILE APETALA-like, ethylene-responsive transcription factor 7-like and F-box protein interaction domain protein as prime regulators involved in Abscisic acid/Gibberellic acid signaling pathways regulating dormancy/germination. In addition, three of the allele-specific markers developed from the identified STAs were validated across a diverse panel. These markers hold potential for increasing dormancy in groundnut through marker-assisted selection (MAS). Thus, this research offers insights into genetic and molecular mechanisms underlying groundnut seed dormancy in addition to providing markers and donors for breeding future varieties with 2-3 weeks of FSD.

PMID:39725911 | DOI:10.1186/s12870-024-05897-6

PDA J Pharm Sci Technol. 2024 Dec 26;78(6):753-754. doi: 10.5731/pdajpst.2024.99902.

ABSTRACT

In pharmaceutical manufacturing, benefit is conferred in detection of specified microorganism (i.e., Burkholderia cepacia complex (BCC), E. coli, Pseudomonas aeruginosa, Salmonella enterica) not readily identified by culture-dependent methods. It's logical to test for the presence of "specified microorganism" using metagenomic analysis before culturing a "specified organism", especially when the organism isn't easy to culture. We developed a metagenomic analysis during enrichment to identify specified organisms. The enriched bacterial community consisted predominantly of Bacillus spp. and Stenotrophomonas spp., each contributing about 97-99% to total taxon abundance in TSB and 1/10× TSB. The specified microorganisms that were observed were Clostridium spp., Burkholderia spp., and Staphylococcus spp. (0.04 - 0.07%) in TSB, otherwise Burkholderia spp., Pseudomonas spp., Salmonella spp., Staphylococcus spp. and Escherichia spp. (0.01 - 1.73%) in 1/10× TSB. PreQ0 biosynthesis (PWY-6703) and guanosine ribonucleotides de novo biosynthesis (PWY-7221) were the most abundant pathways in 1/10× TSB-24 h. BCC chiefly contributed to the toluene degradation (PWY-5180 and PWY-5182) pathways. Initial results demonstrate the potential of the metagenomic approach during enrichment in water-based environments. These results indicate that a metagenomic enrichment approach to evaluating water samples can be useful to monitor specified organisms over time, including oligotrophs such as BCC in 1/10× TSB.

PMID:39725489 | DOI:10.5731/pdajpst.2024.99902

BMJ Open. 2024 Dec 26;14(12):e091884. doi: 10.1136/bmjopen-2024-091884.

ABSTRACT

INTRODUCTION: Children represent a large and vulnerable patient group. However, the evidence base for most paediatric diagnostic and therapeutic procedures remains limited or is often inferred from adults. There is an urgency to improve paediatric healthcare provision based on real-world evidence generation. Digital transformation is a unique opportunity to shape a data-driven, agile, learning healthcare system and deliver more efficient and personalised care to children and their families. The goal of Paediatric Personalized Research Network Switzerland (SwissPedHealth) is to build a sustainable and scalable infrastructure to make routine clinical data from paediatric hospitals in Switzerland interoperable, standardised, quality-controlled, and ready for observational research, quality assurance, trials and health-policy creation. This study describes the design, aims and current achievements of SwissPedHealth.

METHODS AND ANALYSIS: SwissPedHealth was started in September 2022 as one of four national data streams co-funded by the Swiss Personalized Health Network (SPHN) and the Personalized Health and Related Technologies (PHRT). SwissPedHealth develops modular governance and regulatory strategies and harnesses SPHN automatisation procedures in collaboration with clinical data warehouses, the Data Coordination Center, Biomedical Information Technology Network, and other SPHN institutions and funded projects. The SwissPedHealth consortium is led by a multisite, multidisciplinary Steering Committee, incorporating patient and family representatives. The data stream contains work packages focusing on (1) governance and implementation of standardised data collection, (2) nested projects to test the feasibility of the data stream, (3) a lighthouse project that enriches the data stream by integrating multi-omics data, aiming to improve diagnoses of rare diseases and 4) engagement with families through patient and public involvement activities and bioethics interviews.

ETHICS AND DISSEMINATION: The health database regulation of SwissPedHealth was approved by the ethics committee (AO_2022-00018). Research findings will be disseminated through national and international conferences and publications in peer-reviewed journals, and in lay language via online media and podcasts.

PMID:39725440 | DOI:10.1136/bmjopen-2024-091884