Biological Phenotypes Research Articles

P1003 The shorter the interval between preconceptional disease activity and pregnancy, the greater the risk of disease activity during pregnancy: Evidence from a large Dutch cohort

Abstract Background Inflammatory bowel disease (IBD) often coincides with pregnancy. It is well known that disease activity during pregnancy is associated with a higher incidence of adverse pregnancy outcomes 1–3. Previous studies have identified disease activity at conception as an important risk factor for activity later on during pregnancy. We aimed to explore other potential risk factors for activity during pregnancy in women who were in remission at conception, and report on pregnancy outcomes in a tertiary cohort in the Netherlands. Methods For this multicenter, retrospective cohort study, all adult female IBD-patients who had been pregnant during treatment in any of the three participating Dutch university medical centers between 2017 and 2022 were included. Data on patient- and disease characteristics, lab values, medication usage and pregnancy outcomes was extracted from the electronic patient records. Univariate and multivariate binary linear regressions were performed to investigate the relationship between having activity during pregnancy – defined as a fecal calprotectin of ≥200µg/L or the prescription of corticosteroids – and plausible risk factors including biological use, phenotype, disease duration, previous surgery, smoking, BMI, gravidity, and use of IVF. Finally, we evaluate the relationship between activity during pregnancy and pre-conceptional flares, divided over three time intervals: twelve to six months, six to three months, and less than three months prior to conception. Results In total, 432 women were included (61.6% Crohn’s disease, 35.6% ulcerative colitis), who together had been pregnant 716 times. In this cohort, 16.3% of pregnancies was lost before the 16th week. The adverse outcomes for the remaining pregnancies included the following: 10.8% low birthweight, 12.2% premature, 11.7% small for gestational age. Out of the pregnancies carried beyond 16 weeks, a flare occurred in 27.6% of cases. Preconceptional flares were significantly associated with a flare during pregnancy if they occurred within three months prior to conception (OR 9.8, 95%CI 3.8-25.1, p<0.001), but not if they occurred six to three months prior (OR 3.7, 95%CI 1.0-14.1, p=0.058) or twelve to six months prior (OR 2.0, 95%CI 0.7-5.7, p=0.184). In multivariate analysis, increasing disease duration was associated with a lower risk of activity during pregnancy (OR 0.9, 95%CI 0.9-1.0, p=0.047). No further significant correlations were found (Table 1). Conclusion With a shorter interval between a flare and conception, the risk of relapse during pregnancy increases. Further analyses based on remission rather than activity could show the ideal period of time a woman should be free of activity before attempting to conceive.

Aggressive characteristics of tumor deposits in colorectal cancer highlight the need for staging refinement in patients with 0-3 metastatic lymph nodes.

Accurate staging is essential for the optimal management of patients with colorectal cancer (CRC). The role of tumor deposits (TDs) in CRC staging has been contentious due to a lack of comprehensive understanding of their clinical and biological traits. In this retrospective study, we analyzed large data from 5718 CRC patients diagnosed between 2011 and 2022, ensuring rigorous data collection and long-term follow-up. Patients with positive TDs displayed aggressive clinical features. The risk factors for TDs varied among patients with different backgrounds of lymph node (LN) involvement, and the numbers of TDs and metastatic LNs showed a significantly positive correlation. TDs significantly impacted CRC prognosis, resulting in unfavorable outcomes irrespective of LN status. To delve into the biological characteristics of TDs, we performed transcriptome sequencing, immunohistochemistry, and Kaplan-Meier analyses on tissue samples from the additional CRC cohort and The Cancer Genome Atlas datasets. TDs exhibited aggressive biological phenotypes that were distinct from primary tumors and metastatic LNs, characterized by elevated signatures of epithelial-mesenchymal transition, angiogenesis, and immune suppression. Cox proportional hazards analysis was then applied to reassess the appropriate role of TDs within the TNM staging system, revealing that the prognostic weightiness of TDs in CRC corresponded to N2a rather than N1 in patients with 0-3 LN metastases. Overall, our comprehensive analysis showed that TDs, with their aggressive clinical and biological characteristics, could optimize the staging of CRC, highlighting the need to refine their role within the TNM staging system.

Phenotypic Profiling of Selected Cellulolytic Strains to Develop a Crop Residue-Decomposing Bacterial Consortium.

Slow decomposition rates of cereal crop residues can lead to agronomic challenges, such as nutrient immobilization, delayed soil warming, and increased pest pressures. In this regard, microbial inoculation with efficient strains offers a viable and eco-friendly solution to accelerating the decomposition process of crop residues. However, this solution often focuses mostly on selecting microorganisms based on the appropriate enzymic capabilities and neglects the metabolic versatility required to utilize both structural and non-structural components of residues. Therefore, this study aimed to address these limitations by assessing the metabolic profiles of five previously identified cellulolytic bacterial strains, including Bacillus pumilus 1G17, Micromonospora chalcea 1G49, Bacillus mobilis 5G17, Streptomyces canus 1TG5, and Streptomyces achromogenes 3TG21 using Biolog Phenotype Microarray analysis. Moreover, this study evaluated the impact of wheat straw inoculation with single strains and a bacterial consortium on soil organic carbon and nitrogen content in a pot experiment. Results revealed that, beyond the core subset of 12 carbon sources, the strains exhibited diverse metabolic capacities in utilizing 106 carbon sources. All strains demonstrated effective straw biomass degradation compared to the negative control, with significant differences detected only in oil seed rape straw biodegradation estimations. Furthermore, wheat straw inoculated with a bacterial consortium showed a significant increase in soil organic carbon content after 180 days in the pot experiment. Overall, these findings underscore the critical role of metabolic profiling in gaining a deeper understanding of microbial capabilities and addressing the complexities of residue composition and environmental variability.

First-in-class ultralong-target-residence-time p38α inhibitors as a mitosis-targeted therapy for colorectal cancer.

Colorectal cancer (CRC) constitutes the second leading cause of cancer-related death worldwide and advanced CRCs are resistant to targeted therapies, chemotherapies and immunotherapies. p38α (Mapk14) has been suggested as a therapeutic target in CRC; however, available p38α inhibitors only allow for insufficient target inhibition. Here we describe a unique class of p38α inhibitors with ultralong target residence times (designated ULTR-p38i) that robustly inhibit p38α downstream signaling and induce distinct biological phenotypes. ULTR-p38i monotherapy triggers an uncontrolled mitotic entry by activating Cdc25 and simultaneously blocking Wee1. Consequently, CRC cells undergo mitotic catastrophe, resulting in apoptosis or senescence. ULTR-p38i exhibit high selectivity, good pharmaco-kinetic properties and no measurable toxicity with strong therapeutic effects in patient-derived CRC organoids and syngeneic CRC mouse models. Conceptually, our study suggests ultralong-target-residence-time kinase inhibitors as an alternative to covalent inhibitors, which, because of the lack of cysteine residues, cannot be generated for many kinase cancer targets.

EIF4A3-Mediated circ_0008126 Inhibits the Progression and Metastasis of Gastric Cancer by Modulating the APC/β-Catenin Pathway.

Mounting evidence exhibits circRNAs as critical regulators in the progression of many tumors. The regulatory function and potential mechanism by which circ_0008126 in gastric cancer (GC) is unknown. To validate and analyze the expression levels and clinical values of circ_0008126 in GC patients, the biological phenotypes of circ_0008126 in GC were investigated in vitro and in vivo. The roles and effects of circ_0008126 on miR-502-5p, EIF4A3, and APC in GC cells were explored using rescue experiment, RNA stability assay, RNA pull-down, dual-luciferase reporter, RNA immunoprecipitation (RIP), RNA FISH, immunofluorescence (IF), and TOP/Flash and FOP/Flash assays. Circ_0008126 expression levels were prominently down-regulated in GC tissues and cells. Importantly, low expression of circ_0008126 was relevant to the more lymphatic metastasis, advanced TNM stage, and poor survival period in patients with GC. Functionally, circ_0008126 inhibited GC cell proliferative activity, metastatic ability, and epithelial-mesenchymal transition (EMT) in vitro and vivo. Mechanistically, we verified that EIF4A3 can mediate the formation of circ_0008126, and circ_0008126 could competitively bind miR-502-5p and alleviate its role and effect on APC, thus inactivating the β-catenin pathway in GC. Additionally, circ_0008126 was determined to increase the stability of APC mRNA by interacting with cytoplasmic EIF4A3 protein and then enhancing the APC expression. These data demonstrate that EIF4A3-mediated circ_0008126 could regulate the APC expression and inactivate the β-catenin pathway partly by binding to miR-502-5p and EIF4A3, thus inhibiting the tumorigenesis and development of GC.

G2PDeep-v2: a web-based deep-learning framework for phenotype prediction and biomarker discovery for all organisms using multi-omics data.

The G2PDeep-v2 server is a web-based platform powered by deep learning, for phenotype prediction and markers discovery from multi-omics data in any organisms including humans, plants, animals, and viruses. The server provides multiple services for researchers to create deep-learning models through an interactive interface and train these models using an automated hyperparameter tuning algorithm on high-performance computing resources. Users can visualize the results of phenotype and markers predictions and perform Gene Set Enrichment Analysis for the significant markers to provide insights into the molecular mechanisms underlying complex diseases, conditions and other biological phenotypes being studied. The G2PDeep-v2 server is publicly available at https://g2pdeep.org/ and can be utilized for all organisms.

Deep learning–based assessment of missense variants in the COG4 gene presented with bilateral congenital cataract

ObjectiveWe compared the protein structure and pathogenicity of clinically relevant variants of the COG4 gene with AlphaFold2 (AF2), Alpha Missense (AM), and ThermoMPNN for the first time.Methods and analysisThe sequences...

The potential endocrine-disrupting of fluorinated pesticides and molecular mechanism of EDPs in cell models.

Environmental endocrine disruptors constitute a category of exogenous compounds that interfere with the endocrine system's functions in organisms or cells. As a class of particularly representative endocrine-disrupting chemicals, the accumulation of per- and polyfluoroalkyl substances potentially leads to adverse health effects, including hormonal disruptions, developmental issues, and cancer. However, the classification of these disruptors is intricate, and the data on their potential health risks is scattered. The research into fluorinated pesticides is somewhat superficial, with the majority of review articles in this field focusing on the structural characteristics, biodegradation processes, and environmental risks associated with these pesticides. In this study, we compared and investigated the research development processes of seven types of fluorine-containing pesticides and five types of fluorinated endocrine disruptors. The varying toxic effects of these endocrine disruptors are highly dependent on exposure conditions. Their actions are complex, affecting behavioral substances throughout the organism, and monitoring some complex biological phenotypes, sex- or age-specific effects, and behavioral learning poses significant challenges. The findings will serve as a reference for future studies on the toxicity of pesticides to humans and other organisms.

Computational and digital analyses in the INSPIRE mouse cohort to define sex-specific functional determinants of biological aging.

Biological age, which reflects the physiological state of an individual, offers a better predictive value than chronological age for age-related diseases and mortality. Nonetheless, determining accurate functional features of biological age remains challenging due to the multifactorial nature of aging. Here, we established a unique mouse cohort comprising 1576 male and female outbred SWISS mice subjected or not to high-fat, high-sucrose diet to investigate multiorgan/system biological aging throughout adulthood. Comprehensive functional and biological phenotyping at ages of 6, 12, 18, and 24 months revealed notable sex-specific disparities in longitudinal locomotion patterns and multifunctional aging parameters. Topological data analysis enabled the identification of functionally similar mouse clusters irrespective of chronological age. Moreover, our study pinpointed critical functional markers of biological aging such as muscle function, anxiety characteristics, urinary patterns, reticulocyte maturation, cardiac remodeling and function, and metabolic alterations, underscoring muscle function as an early indicator of biological age in male mice.

Development and Applications of Organoids in Gynecological Diseases.

Organoids are rapidly self-organizing 3D in vitro cultures derived from pluripotent stem cells (PSCs) or adult stem cells (ASCs) that possess disease-like characteristics with high success rates. Due to their ability to retain tissue structure, biological phenotypes, and genetic information, they have been utilized as a novel in vitro model for disease research. In recent years, scientists have established self-organizing 3D organoids for human endometrium, fallopian tubes, ovaries, and cervix by culturing stem cells with cytokines in 3D scaffolds. The integration of organoids with animal models, organ-on-a-chip systems, and 3D printing technologies offers a novel preclinical model for exploring disease mechanisms and developing treatments. This review elaborate on the recent research progress of stem cells-formed organoids in the field of gynecology from the aspects of constructing gynecological disease organoids, drug screening and new drug development, simulation modeling, allogeneic transplantation, regenerative medicine and personalized treatment."

Beyond Hormone Receptors: liquid biopsy tools to unveil new clinical meanings and empower therapeutic decision-making in Luminal-like metastatic breast cancer.

Immunohistochemical (IHC) tissue profiling is a standard practice in the management of metastatic breast cancer (mBC), that enables the identification of distinct biological phenotypes based on hormone receptors' expression. Luminal-like tumors primarily benefit from a first line treatment strategy combining endocrine therapy and cyclin-dependent kinase 4/6 inhibitors. However, IHC analyses necessitate invasive procedures and may encounter technical and interpretational challenges. In the current era of precision medicine, liquid biopsy holds potential to provide clinicians with additional insights into disease biology, including mechanisms underlying endocrine resistance and disease progression. Several liquid-based biomarkers are entering clinical practice and hold prognostic and predictive values in Luminal-like mBC, while many others are currently being investigated. The present work aims to summarize the current evidence regarding the clinical meanings of hormone receptors and their downstream molecular pathways, alongside their implications for therapeutic decision-making in Luminal-like mBC.

Human limits in machine learning: prediction of potato yield and disease using soil microbiome data

BackgroundThe preservation of soil health is a critical challenge in the 21st century due to its significant impact on agriculture, human health, and biodiversity. We provide one of the first comprehensive investigations into the predictive potential of machine learning models for understanding the connections between soil and biological phenotypes. We investigate an integrative framework performing accurate machine learning-based prediction of plant performance from biological, chemical, and physical properties of the soil via two models: random forest and Bayesian neural network.ResultsPrediction improves when we add environmental features, such as soil properties and microbial density, along with microbiome data. Different preprocessing strategies show that human decisions significantly impact predictive performance. We show that the naive total sum scaling normalization that is commonly used in microbiome research is one of the optimal strategies to maximize predictive power. Also, we find that accurately defined labels are more important than normalization, taxonomic level, or model characteristics. ML performance is limited when humans can’t classify samples accurately. Lastly, we provide domain scientists via a full model selection decision tree to identify the human choices that optimize model prediction power.ConclusionsOur study highlights the importance of incorporating diverse environmental features and careful data preprocessing in enhancing the predictive power of machine learning models for soil and biological phenotype connections. This approach can significantly contribute to advancing agricultural practices and soil health management.

Older patients affected by COVID-19: investigating the existence of biological phenotypes

IntroductionCOVID-19 provides an opportunity to examine biological phenotypes (observable morphological, functional and biological characteristics) in individuals who experience the same acute condition, potentially revealing differences in response to acute external stressors. The aim our study was to investigate biological phenotypes in older patients hospitalized for COVID-19, exploiting a panel of aging biomarkers.MethodsData were gathered from the FRACOVID Project, an observational multicenter study, aimed to evaluate the impact of frailty on health-related outcomes in patients 60 + with COVID-19 in Northern Italy. A hierarchical cluster analysis was run using log-transformed and scaled values of TNF-a, IL-1 beta, IL-6, PAI-1, GDF-15, NT-proBNP, and Cystatin C evaluated at admission.ResultsEighty-one participants (mean age 75.3 years; 60.5% male) were evaluated. Frailty was identified in 42% of the sample and 27.2% were unable to ambulate outdoors. The mean hospital stay was 24.7 days, with an in-hospital mortality rate of 18.5%. Three biological phenotypes were found: (1) ‘inflammatory’, with high inflammatory biomarkers; (2) ‘organ dysfunction’, characterized by elevated cystatin C and NT-proBNP, and lower inflammatory markers; and (3) ‘unspecific’, with lower NT-proBNP and GDF-15 levels, and intermediate concentrations of other biomarkers. The ’organ dysfunction’ phenotype showed the highest mean age and prevalence of frailty, disability, and chronic diseases. The ‘inflammatory‘ phenotype showed the highest burden of respiratory and systemic signs and symptoms of infection.ConclusionBiological phenotypes might be used to identify different clinical and functional phenotypes in individuals affected by COVID-19.

Overlapping and Distinct Physical and Biological Phenotypes in Pure Frailty and Obese Frailty.

Pure frailty and obese frailty are common types of frailty syndrome. However, the overlapping and distinct characteristics between pure frailty and obese frailty remain unclear. This study aims to reveal the overlapping/distinct physical and biological phenotypes of pure frailty and obese frailty, providing theoretical support for their prevention, diagnosis, and treatment. Mice were fed either a normal or high-fat diet and assessed at 20 months of age. They were assigned to one of the four groups: control, obesity, pure frailty, and obese frailty. Grip strength, walking speed, physical activity, endurance, and body weight were measured to determine pure frailty and obese frailty. Physical and biological phenotypes were assessed. Distinct physical phenotypes were observed between pure frailty and obese frailty in terms of body weight, lean mass, fat mass, fat mass in tissue, grip strength, endurance, and physical activity, while walking speed overlapped. In biological phenotypes, levels of Smad2/3, FoxO3a, P62, LAMP-2, and cathepsin L expression were distinct, while AKT, p-AKT, mTOR, p-mTOR, p-Smad2/3, p-FoxO3a, Beclin-1, ATG7, and LC3 overlapped. Distinct physical phenotypes observed in obese frailty are primarily attributable to the effect of obesity, with further impairment of muscle function resulting from the combined effects of frailty syndromes and obesity. Pure frailty and obese frailty share overlapping biological phenotypes, particularly in the regulation of muscle protein synthesis. Moreover, the interaction between obesity and frailty syndromes gives rise to both overlapping and distinct biological phenotypes, especially in the regulation of specific degradation signaling proteins.

Reconstruction and analyses of genome-scale halomonas metabolic network yield a highly efficient PHA production

In pursuit of reliable and efficient industrial microbes, this study integrates cutting-edge systems biology tools with Halomonas bluephagenesis TD01, a robust halophilic bacterium. We generated the complete and annotated circular genome sequence for this model organism, constructed and meticulously curated a genome-scale metabolic network, achieving striking 86.32% agreement with Biolog Phenotype Microarray data and visualize the network via an interactive Electron/Thrift server architecture. We then analyzed the genome-scale network using vertex sampling analysis (VSA) and found that productions of biomass, polyhydroxyalkanoates (PHA), citrate, acetate, and pyruvate are mutually competing. Recognizing the dynamic nature of H. bluephagenesis TD01, we further developed and implemented the hyper-cube-shrink-analysis (HCSA) framework to predict effects of nutrient availabilities and metabolic reactions in the model on biomass and PHA accumulation. We then, based on the analysis results, proposed and validate multi-step feeding strategies tailored to different fermentation stages. This integrated approach yielded remarkable results, with fermentation culminating in a cell dry weight of 100.4 g/L and 70% PHA content, surpassing previous benchmarks. Our findings exemplify the powerful potential of system-level tools in the design and optimization of industrial microorganisms, paving the way for more efficient and sustainable bio-based processes.

УВЕЛИЧЕНИЕ ТОЛЩИНЫ ДЕСНЫ В ОБЛАСТИ ПЛАНИРУЕМЫХ ИМПЛАНТАТОВ ПУТЕМ ИЗМЕНЕНИЯ БИОТИПА ДЕСНЫ

The initial deficiency or complete absence of attached keratinized gum in the area of the above-mentioned implants are features of the use of dental implantation. The most common way to increase gum thickness is through the use of connective tissue grafts. A gingival autograft from the palatal surface of the upper jaw is transferred to a specially prepared recipient site of the alveolar process, which needs to increase the thickness of the attached gum. Since the increase in gingival thickness is the result of plastic surgery, the original biological phenotype of the gingiva does not change. This article describes a technique for increasing the thickness of the gums by changing the initial biological phenotype of the gums through the use of an allogeneic graft as a connective tissue graft: a fascial limiter for directed tissue regeneration “Alloplant”. Materials and methods. Clinical studies were performed on volunteers with a thin gum phenotype in the area of the planned dental implant: dental implantation was performed using soft tissue autografts from the mucous membrane of the patient's upper palate; Dental implantation was performed using the Alloplant fascial limiter for directed tissue regeneration. The thickness of the gums was determined by morphological examination of tissues. Results. The thickness of the gum tissue of operated patients using the Alloplant fascial limiter for directed tissue regeneration in the implant projection was more than 1.5 mm with an increase in gum thickness to 2.3 mm. The gum phenotype changed to thick, which was confirmed by the results of morphological studies. Conclusion. Allograft fascial limiter for directed tissue regeneration “Alloplant”, when used as a connective tissue graft, in accordance with the method described in this article, forms the phenotype of “thick” gums (thickness more than 1.5 mm) in the projection of dental implant platforms (thickness more than 1.5 mm), which allows predictable perform restoration on implants.

PhenoMetaboDiff: R Package for Analysis and Visualization of Phenotype Microarray Data.

PhenoMetaboDiff is a novel R package for computational analysis and visualization of data generated by Biolog Phenotype Mammalian Microarrays (PM-Ms). These arrays measure the energy production of mammalian cells in different metabolic environments, assess the metabolic activity of cells exposed to various drugs or energy sources, and compare the metabolic profiles of cells from individuals affected by specific disorders versus healthy controls. PhenoMetaboDiff has several modules that facilitate statistical analysis by sample comparisons using non-parametric Mann-Whitney U-test, the integration of the OPM package (an R package for analysing OmniLog® phenotype microarray data) for robust file conversion, and calculation of slope and area under the curve (AUC). In addition, the built-in visualization allows specific wells to be visualized in selected pathways for a particular time slice. Compared to the standard OPM package, the features developed in PhenoMetaboDiff assess metabolic profiles by employing statistical tests and visualize the dynamic nature of the energy production in several conditions. Examples of how this package can be used are demonstrated for several rare disease conditions. The incorporation of a graphical user interface expands the utility of this program to both expert and novice users of R. PhenoMetaboDiff makes the deployment of the cutting-edge Biolog system available to any researcher.

Studying of serum bile acids metabolomics as potential biomarkers for differentiation between hepatocellular carcinoma and cholangiocarcinoma

BackgroundMetabolomics is an emerging field that quantifies numerous metabolites systematically aiming to determine the metabolites corresponding to each biological phenotype and then provide an analysis of the mechanisms involved. Bile acids (as an organic metabolites) are synthesized in the liver from cholesterol and could be used as indicator of hepatobiliary impairment. However, the role of these bile acids in the pathogenesis of cholangiocarcinoma (CCA) and hepatocellular carcinoma (HCC) is still unclear. Therefore, the current study aimed to use serum bile acid profiles potential diagnostic biomarkers for early detection of cholangiocarcinoma and differentiating it from hepatocellular carcinoma.Subjects and methodsUltra-performance liquid chromatography-tandem mass spectrometry (UPLC/MS/ MS) analytical method was used for the measurement of bile acids in the serum of patients with hepatocellular carcinoma (n = 35), cholangiocarcinoma (n = 35), and control group (n = 35) to determine role as markers for differentiation between hepatocellular carcinoma and cholangiocarcinoma.ResultsThis study revealed that there was a significant increase in all 14 bile acids in both HCC and CCA compared to control. Also, there was significant increase in LCA, TCA, GDCA, and GCA in cholangiocarcinoma (CCA) compared to HCC with AUC 0.775, 0.825, 0.797, and 0.831 respectively with highest sensitivity and specificity for GCA (82% and 74%, respectively) for differentiation between the two types of cancers.ConclusionDetermination of the serum bile acids pattern using UPLC/MS/MS may help to differentiate between hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA) especially GCA which may be a good biomarker for differentiation between two types of liver cancers.

Hypermigration of macrophages through the concerted action of GRA effectors on NF-κB/p38 signaling and host chromatin accessibility potentiates Toxoplasma dissemination.

Intracellular pathogens can hijack the cellular functions of infected host cells to their advantage, for example, for intracellular survival and dissemination. However, how microbes orchestrate the hijacking of complex cellular processes, such as host cell migration, remains poorly understood. As such, the common parasite Toxoplasma gondii actively invades the immune cells of humans and other vertebrates and modifies their migratory properties. Here, we show that the concerted action of a number of secreted effector proteins from the parasite, principally GRA15 and GRA24, acts on host cell signaling pathways to activate chemotaxis. Furthermore, the protein effector GRA28 selectively acted on chromatin accessibility in the host cell nucleus to selectively boost host gene expression. The joint activities of GRA effectors culminated in pro-migratory signaling within the infected phagocyte. We provide a molecular framework delineating how T. gondii can orchestrate a complex biological phenotype, such as the migratory activation of phagocytes to boost dissemination.

Species barrier as molecular basis for adaptation of synthetic prions with N-terminally truncated PrP.

Mammalian prions are neurotropic pathogens formed from PrPSc assemblies, a misfolded variant of the host-encoded prion protein PrPC. Multiple PrPSc conformations or strains self-propagate in host populations or mouse models of prion diseases, exhibiting distinct biological and biochemical phenotypes. Constrained interactions between PrPSc and PrPC conformations confer species specificity and regulate cross-species transmission. The pathogenicity of fibrillar assemblies derived from bacterially expressed recombinant PrP (rPrP) has been instrumental in demonstrating the protein-only nature of prions. Yet, their ability to encode different strains and transmit between species remains poorly studied, hampering their use in exploring structure-to-strain relationships. Fibrillar assemblies from rPrP with hamster, mouse, human, and bovine primary structures were generated and tested for transmission and adaptation in tg7 transgenic mice expressing hamster PrPC. All assemblies, except the bovine ones, were fully pathogenic on the primary passage, causing clinical disease, PrPSc brain deposition, and spongiform degeneration. They exhibited divergent adaptation processes and strain properties upon subsequent passage. Assemblies of hamster origin propagated without apparent need for adaptation, those of mouse origin adapted abruptly, and those of human origin required serial passages for optimal fitness. Molecular analyses revealed the presence of endogenously truncated PrPSc species in the resulting synthetic strains that lack the 90-140 amino acid region considered crucial for infectivity. In conclusion, rPrP assemblies provide a facile means of generating novel prion strains with adaptative/evolutive properties mimicking genuine prions. The PrP amino acid backbone is sufficient to encode different strains with specific adaptative properties, offering insights into prion transmission and strain diversity.