The Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema was released in 2022 and approved by ISO as a standard for sharing clinical and genomic information about an individual, including phenotypic descriptions, numerical measurements, genetic information, diagnoses, and treatments. A phenopacket can be used as an input file for software that supports phenotype-driven genomic diagnostics and for algorithms that facilitate patient classification and stratification for identifying new diseases and treatments. There has been a great need for a collection of phenopackets to test software pipelines and algorithms. Here, we present Phenopacket Store. Phenopacket Store v.0.1.19 includes 6,668 phenopackets representing 475 Mendelian and chromosomal diseases associated with 423 genes and 3,834 unique pathogenic alleles curated from 959 different publications. This represents the first large-scale collection of case-level, standardized phenotypic information derived from case reports in the literature with detailed descriptions of the clinical data and will be useful for many purposes, including the development and testing of software for prioritizing genes and diseases in diagnostic genomics, machine learning analysis of clinical phenotype data, patient stratification, and genotype-phenotype correlations. This corpus also provides best-practice examples for curating literature-derived data using the GA4GH Phenopacket Schema.
- MeSH
- Algorithms MeSH
- Databases, Genetic MeSH
- Phenotype * MeSH
- Genomics * methods MeSH
- Humans MeSH
- Software * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Lactic acid bacteria (LABs) have emerged as a significant area of study within the field of probiotics due to their diverse health benefits and wide application. This review examines the various methods used to evaluate the antioxidant activity of LABs, including in vitro chemical evaluation methods, cell model evaluation methods, and in vivo evaluation methods. Comprehensive overview of the various assessment techniques employed to elucidate the multifaceted roles of LABs in enhancing the body's natural defenses against oxidative damage. Moreover, this review emphasizes several pivotal aspects of the antioxidant effects of LABs, including the activation of the antioxidant signal pathway, the induction of antioxidative enzymes, the formation of a ROS-binding system, the production of metabolites, the enhancement of intestinal barrier integrity, the activation of the oxidative damage repair system, and the assurance of mitochondrial function. These represent the key antioxidant effects of LABs. The synthesis of this information advances our understanding of the dynamic and diverse antioxidant effects of LABs, providing a foundation for further research into their therapeutic applications in combating oxidative stress-related disorders. Future research should employ multi-omics technologies, genetic engineering, studies on synergistic effects, and large-scale clinical trials to further elucidate the molecular mechanisms underlying the antioxidant effects of LABs. This will promote their application in functional foods, pharmaceuticals, and cosmetics, providing a scientific basis for the development of more efficient antioxidant products.
- MeSH
- Antioxidants * metabolism pharmacology MeSH
- Lactobacillales * metabolism chemistry MeSH
- Humans MeSH
- Oxidative Stress MeSH
- Probiotics * MeSH
- Reactive Oxygen Species metabolism MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
Integral membrane proteins carry out essential functions in the cell, and their activities are often modulated by specific protein-lipid interactions in the membrane. Here, we elucidate the intricate role of cardiolipin (CDL), a regulatory lipid, as a stabilizer of membrane proteins and their complexes. Using the in silico-designed model protein TMHC4_R (ROCKET) as a scaffold, we employ a combination of molecular dynamics simulations and native mass spectrometry to explore the protein features that facilitate preferential lipid interactions and mediate stabilization. We find that the spatial arrangement of positively charged residues as well as local conformational flexibility are factors that distinguish stabilizing from non-stabilizing CDL interactions. However, we also find that even in this controlled, artificial system, a clear-cut distinction between binding and stabilization is difficult to attain, revealing that overlapping lipid contacts can partially compensate for the effects of binding site mutations. Extending our insights to naturally occurring proteins, we identify a stabilizing CDL site within the E. coli rhomboid intramembrane protease GlpG and uncover its regulatory influence on enzyme substrate preference. In this work, we establish a framework for engineering functional lipid interactions, paving the way for the design of proteins with membrane-specific properties or functions.
- MeSH
- DNA-Binding Proteins MeSH
- Endopeptidases metabolism chemistry genetics MeSH
- Escherichia coli metabolism genetics MeSH
- Cardiolipins * metabolism chemistry MeSH
- Membrane Proteins * metabolism chemistry genetics MeSH
- Protein Engineering * MeSH
- Escherichia coli Proteins * metabolism chemistry genetics MeSH
- Molecular Dynamics Simulation MeSH
- Protein Binding MeSH
- Publication type
- Journal Article MeSH
The biotransformation of nanoparticles plays a crucial role in determining their biological fate and responses. Although a few engineering strategies (e.g., surface functionalization and shape control) have been employed to regulate the fate of nanoparticles, the genetic control of nanoparticle biotransformation remains an unexplored avenue. Herein, we utilized a CRISPR-based genome-scale knockout approach to identify genes involved in the biotransformation of rare earth oxide (REO) nanoparticles. We found that the biotransformation of REOs in lysosomes could be genetically controlled via SMPD1. Specifically, suppression of SMPD1 inhibited the transformation of La2O3 into sea urchin-shaped structures, thereby protecting against lysosomal damage, proinflammatory cytokine release, pyroptosis and RE-induced pneumoconiosis. Overall, our study provides insight into how to control the biological fate of nanomaterials.
- MeSH
- Biotransformation genetics MeSH
- CRISPR-Cas Systems MeSH
- Sea Urchins metabolism MeSH
- Metal Nanoparticles * chemistry MeSH
- Metals, Rare Earth * metabolism chemistry MeSH
- Humans MeSH
- Lysosomes metabolism MeSH
- Mice MeSH
- Nanoparticles * metabolism chemistry MeSH
- Pyroptosis MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Mice MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
Specialized or secondary metabolites are small molecules of biological origin, often showing potent biological activities with applications in agriculture, engineering and medicine. Usually, the biosynthesis of these natural products is governed by sets of co-regulated and physically clustered genes known as biosynthetic gene clusters (BGCs). To share information about BGCs in a standardized and machine-readable way, the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard and repository was initiated in 2015. Since its conception, MIBiG has been regularly updated to expand data coverage and remain up to date with innovations in natural product research. Here, we describe MIBiG version 4.0, an extensive update to the data repository and the underlying data standard. In a massive community annotation effort, 267 contributors performed 8304 edits, creating 557 new entries and modifying 590 existing entries, resulting in a new total of 3059 curated entries in MIBiG. Particular attention was paid to ensuring high data quality, with automated data validation using a newly developed custom submission portal prototype, paired with a novel peer-reviewing model. MIBiG 4.0 also takes steps towards a rolling release model and a broader involvement of the scientific community. MIBiG 4.0 is accessible online at https://mibig.secondarymetabolites.org/.
Allelic variability in the adaptive immune receptor loci, which harbor the gene segments that encode B cell and T cell receptors (BCR/TCR), is of critical importance for immune responses to pathogens and vaccines. Adaptive immune receptor repertoire sequencing (AIRR-seq) has become widespread in immunology research making it the most readily available source of information about allelic diversity in immunoglobulin (IG) and T cell receptor (TR) loci. Here, we present a novel algorithm for extrasensitive and specific variable (V) and joining (J) gene allele inference, allowing the reconstruction of individual high-quality gene segment libraries. The approach can be applied for inferring allelic variants from peripheral blood lymphocyte BCR and TCR repertoire sequencing data, including hypermutated isotype-switched BCR sequences, thus allowing high-throughput novel allele discovery from a wide variety of existing data sets. The developed algorithm is a part of the MiXCR software. We demonstrate the accuracy of this approach using AIRR-seq paired with long-read genomic sequencing data, comparing it to a widely used algorithm, TIgGER. We applied the algorithm to a large set of IG heavy chain (IGH) AIRR-seq data from 450 donors of ancestrally diverse population groups, and to the largest reported full-length TCR alpha and beta chain (TRA and TRB) AIRR-seq data set, representing 134 individuals. This allowed us to assess the genetic diversity within the IGH, TRA, and TRB loci in different populations and to establish a database of alleles of V and J genes inferred from AIRR-seq data and their population frequencies with free public access through VDJ.online database.
- MeSH
- Alleles * MeSH
- Algorithms * MeSH
- Genetic Variation MeSH
- Humans MeSH
- Receptors, Antigen, B-Cell genetics immunology MeSH
- Receptors, Antigen, T-Cell genetics immunology MeSH
- Sequence Analysis, DNA methods MeSH
- Software * MeSH
- High-Throughput Nucleotide Sequencing methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Patient-derived organoids (PDOs) and xenografts (PDXs) are powerful tools for personalized medicine in pancreatic cancer (PC) research. This study explores the complementary strengths of PDOs and PDXs in terms of practicality, genetic fidelity, cost, and labor considerations. Among other models like 2D cell cultures, spheroids, cancer-on-chip systems, cell line-derived xenografts (CDX), and genetically engineered mouse models (GEMMs), PDOs and PDXs uniquely balance genetic fidelity and personalized medicine potential, offering distinct advantages over the simplicity of 2D cultures and the advanced, but often resource-intensive, GEMMs and cancer-on-chip systems. PDOs excel in high-throughput drug screening due to their ease of use, lower cost, and shorter experimental timelines. However, they lack a complete tumor microenvironment. Conversely, PDXs offer a more complex microenvironment that closely reflects patient tumors, potentially leading to more clinically relevant results. Despite limitations in size, number of specimens, and engraftment success, PDXs demonstrate significant concordance with patient responses to treatment, highlighting their value in personalized medicine. Both models exhibit significant genetic fidelity, making them suitable for drug sensitivity testing. The choice between PDOs and PDXs depends on the research focus, resource availability, and desired level of microenvironment complexity. PDOs are advantageous for high-throughput screening of a diverse array of potential therapeutic agents due to their relative ease of culture and scalability. PDXs, on the other hand, offer a more physiologically relevant model, allowing for a comprehensive evaluation of drug efficacy and mechanisms of action.
- MeSH
- Precision Medicine * methods MeSH
- Humans MeSH
- Mice MeSH
- Tumor Microenvironment drug effects MeSH
- Pancreatic Neoplasms * drug therapy pathology genetics MeSH
- Organoids * drug effects pathology MeSH
- Antineoplastic Agents pharmacology therapeutic use MeSH
- Drug Screening Assays, Antitumor methods MeSH
- Xenograft Model Antitumor Assays * methods MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Mice MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
Neurofibromatosis type 2 (NF-2) is a dominantly inherited genetic disorder that results from variants in the tumor suppressor gene, neurofibromin 2 (NF2). Here, we report the generation of a conditional zebrafish model of neurofibromatosis established by inducible genetic knockout of nf2a/b, the zebrafish homologs of human NF2. Analysis of nf2a and nf2b expression revealed ubiquitous expression of nf2b in the early embryo, with overlapping expression in the neural crest and its derivatives and in the cranial mesenchyme. In contrast, nf2a displayed lower expression levels. Induction of nf2a/b knockout at early stages increased the proliferation of larval Schwann cells and meningeal fibroblasts. Subsequently, in adult zebrafish, nf2a/b knockout triggered the development of a spectrum of tumors, including vestibular Schwannomas, spinal Schwannomas, meningiomas and retinal hamartomas, mirroring the tumor manifestations observed in patients with NF-2. Collectively, these findings highlight the generation of a novel zebrafish model that mimics the complexities of the human NF-2 disorder. Consequently, this model holds significant potential for facilitating therapeutic screening and elucidating key driver genes implicated in NF-2 onset.
- MeSH
- Zebrafish * genetics embryology MeSH
- Animals, Genetically Modified MeSH
- Gene Knockout Techniques * MeSH
- Larva metabolism MeSH
- Humans MeSH
- Disease Models, Animal * MeSH
- Neurofibromatosis 2 genetics pathology metabolism MeSH
- Neurofibromatoses genetics pathology metabolism MeSH
- Neurofibromin 2 * genetics metabolism deficiency MeSH
- Cell Proliferation MeSH
- Zebrafish Proteins * genetics metabolism deficiency MeSH
- Schwann Cells metabolism pathology MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
... Dědičnost 16 -- Geny 20 -- Proteiny 26 -- Epigenetika 28 -- Lidský genom 30 no -- KAPITOLA 2 -- Genetika ... ... -- KAPITOLA 4 -- Geny a evoluce 79 -- Historie evoluce - 80 -- Vývoj evoluční teorie 82 -- Úloha genetiky ... ... - Onemocnění s komplexní dědičností 142 -- Genetická predispozice k nádorovým onemocněním 144 -- Genetika ...
Poprvé v češtině ; 9
1. vydání 176 stran : ilustrace ; 27 cm
Publikace se zaměřuje na evoluci, lidskou genetiku, na DNA a její použití. Určeno široké veřejnosti.; Kniha velmi přitažlivou formou představuje genetiku.Prezentuje základní principy dědičnosti, vztah genů a prostředí, vliv dědičnosti na nemoci a chování, také popisuje praktické využití poznatků genetiky v medicíně a farmacii nebo v archeologii a kriminalistice včetně identifikace osob. Snaží se odpovědět na otázku, co nám přinesou nové možnosti genetiky a výzkumu DNA a nastiňuje možnosti i hranice genetiky do budoucna.
- MeSH
- Biological Evolution MeSH
- DNA MeSH
- Epigenomics MeSH
- Genetic Engineering MeSH
- Genetic Code * MeSH
- Human Genetics MeSH
- Publication type
- Monograph MeSH
- Popular Work MeSH
- Conspectus
- Obecná genetika. Obecná cytogenetika. Evoluce
- NML Fields
- genetika, lékařská genetika
The major organelles of the endomembrane system were in place by the time of the last eukaryotic common ancestor (LECA) (~1.5 billion years ago). Their acquisitions were defining milestones during eukaryogenesis. Comparative cell biology and evolutionary analyses show multiple instances of homology in the protein machinery controlling distinct interorganelle trafficking routes. Resolving these homologous relationships allows us to explore processes underlying the emergence of additional, distinct cellular compartments, infer ancestral states predating LECA, and explore the process of eukaryogenesis itself. Here, we undertake a molecular evolutionary analysis (including providing a transcriptome of the jakobid flagellate Reclinomonas americana), exploring the origins of the machinery responsible for the biogenesis of lysosome-related organelles (LROs), the Biogenesis of LRO Complexes (BLOCs 1,2, and 3). This pathway has been studied only in animals and is not considered a feature of the basic eukaryotic cell plan. We show that this machinery is present across the eukaryotic tree of life and was likely in place prior to LECA, making it an underappreciated facet of eukaryotic cellular organisation. Moreover, we resolve multiple points of ancient homology between all three BLOCs and other post-endosomal retrograde trafficking machinery (BORC, CCZ1 and MON1 proteins, and an unexpected relationship with the "homotypic fusion and vacuole protein sorting" (HOPS) and "Class C core vacuole/endosomal tethering" (CORVET) complexes), offering a mechanistic and evolutionary unification of these trafficking pathways. Overall, this study provides a comprehensive account of the rise of the LROs biogenesis machinery from before the LECA to current eukaryotic diversity, integrating it into the larger mechanistic framework describing endomembrane evolution.
