Phenotypic Diversity Research Articles

A supergene affects androgen concentrations during early development in a bird with alternative reproductive morphs

Species with alternative reproductive tactics typically show pronounced phenotypic variation between and within sexes. In some species, this variation culminates in discrete reproductive morphs that are genetically determined, facilitating studies on how genetic variation translates into phenotypic variation. In ruffs (Calidris pugnax), an autosomal inversion polymorphism underlies three reproductive morphs (Independents, Satellites and Faeders), which differ in circulating steroid concentrations in adults. Yet, it remains unknown whether morph differences in steroid concentrations already arise before adulthood. We examined variation in circulating testosterone, androstenedione and progesterone concentrations between morphs and sexes in ruff chicks and juveniles and compared the differences to those in adults. Since measured hormone concentrations only provide momentary states and show high within- and between-individual variation, we took repeated measurements to compare means, variances and skewness between groups. We found clear differences between morphs but not the sexes in early life. Between morphs, androgen concentrations in young ruffs differed in variance and skewness, but not in their means. For testosterone, Independents had a higher variance than Satellites/Faeders, whereas for androstenedione, we observed the opposite pattern. For progesterone, we did not detect clear differences between groups. Skewness values mirrored differences in morph variances. Compared to adults, premature ruffs had lower androgen concentrations. In both life stages, we detected morph-specific associations between androgen concentrations: androstenedione concentrations increased with testosterone concentrations more in Satellites/Faeders than in Independents. These observed morph differences during early life are consistent with a supergene-mediated regulation of androgen variation that underlies the diversification of adult behavioural phenotypes.

ScRAPdb: an integrated pan-omics database for the Saccharomyces cerevisiae reference assembly panel.

As a unicellular eukaryote, the budding yeast Saccharomyces cerevisiae strikes a unique balance between biological complexity and experimental tractability, serving as a long-standing classic model for both basic and applied studies. Recently, S. cerevisiae further emerged as a leading system for studying natural diversity of genome evolution and its associated functional implication at population scales. Having high-quality comparative and functional genomics data are critical for such efforts. Here, we exhaustively expanded the telomere-to-telomere (T2T) S. cerevisiae reference assembly panel (ScRAP) that we previously constructed for 142 strains to cover high-quality genome assemblies and annotations of 264 S. cerevisiae strains from diverse geographical and ecological niches and also 33 outgroup strains from all the other Saccharomyces species complex. We created a dedicated online database, ScRAPdb (https://www.evomicslab.org/db/ScRAPdb/), to host this expanded pangenome collection. Furthermore, ScRAPdb also integrates an array of population-scale pan-omics atlases (pantranscriptome, panproteome and panphenome) and extensive data exploration toolkits for intuitive genomics analyses. All curated data and downstream analysis results can be easily downloaded from ScRAPdb. We expect ScRAPdb to become a highly valuable platform for the yeast community and beyond, leading to a pan-omics understanding of the global genetic and phenotypic diversity.

Unravelling cardiomyopathies: a comprehensive analysis of phenotypic diversity, endomyocardial biopsy patterns, and the impact of Gremlin-1 on clinical prognosis

Abstract Background Cardiomyopathies are the main cause of progressive heart failure (HF) and despite outstanding advances of diagnostics and therapies, mortality remains high.1,2 The current phenotype-based classification of non-ischemic cardiomyopathies (NICM) is based on a clinical workflow including endomyocardial biopsy (EMB).3-5 Inflammation and fibrosis are essentially involved in progression of HF and lead to development of adverse cardiovascular (CV) events.6,7 The diagnostic algorithm facilitates risk stratification of HF patients but nonetheless risk factors often remain inapparent prior to disease incidence. Objective In this study we investigate EMB patters in patients with NICM and elucidate alterations associated with phenotypic diversity and progression of HF. Methods We prospectively enrolled patients with HF due to NICM in a large-scale all-comers cohort (n=703). All patients underwent guideline-based phenotypic classification including EMB, and RNA data were acquired alongside histological analyses within the myocardium. We then performed a ten-year follow-up to screen for disease progression. Results A guideline-based classification of patients with NICM resulted in a phenotyping of aetiological risk groups (Figure 1A). We found that characteristic expression of fibroinflammatory mediators within the myocardium occurred in patients with symptomatic NICM (Figure 1B). We found that elevated expression of Gremlin-1 (Grem), a potent downstream profibrotic mediator of TGFß pathway, was associated with pro-fibrotic cardiac remodelling (Figure 1C). Further, Gremlin-1 was associated with a significant decrease of left ventricular functional capacity and inversely correlated with late gadolinium enhancement (LGE) (Figure 1D&E). Moreover, the expression of Gremlin-1 was enriched with pro-fibrotic and inflammatory RNA signalling pathways hinting at underlying pathophysiological cascades (Figure 2A&B). Most strikingly, the expression of Gremlin-1 was independently associated with an increased CV risk during the ten-year follow-up (Figure 2C). Thus, patients with Gremlin-1+ EMB were at elevated risk to suffer from all-cause mortality and number of patients eligible for ICD implantation was critically enhanced in patients with Gremlin-1+ EMB (Figure 2D-F). In addition, the estimation of an elevated CV risk by machine learning including Gremlin-1 improved the ten-year risk stratification among all patients with NICM (Figure 2G). Thus, Gremlin-1 was associated with cardiac remodelling and disease activity in HF patients (Figure 2H). Conclusion Our results unveiled that Gremlin-1 is associated with inflammation and cardiac remodelling in patients with symptomatic cardiomyopathy and patients with Gremlin-1+ EMB are at elevated risk to develop adverse CV events. Thus, the histological evaluation of Gremlin-1 may help to identify pathophysiological cascades and improve early risk discrimination and management of HF patients.Figure 1Figure 2

Unveiling the clinical profiles of heart failure across diverse stages and phenotypes: insights from the national echocardiographic society registry

Abstract Background The modern comprehension of heart failure (HF), based on a staging paradigm, demands systematic screening to promptly identify individuals at risk, those in the pre-HF stage, and symptomatic HF patients across various phenotypes (HFpEF, HFmrEF, and HFrEF). The discernment of clinical profiles within these categories holds significant potential for improving screening and ensuring timely therapeutic interventions. Material and Methods Our national echocardiographic society executed a multicenter HF screening program. General practitioners in 13 primary care centers utilized the original mobile app to determine referrals for transthoracic echocardiography and N-terminal pro-B-type natriuretic peptide (NT-proBNP) testing in patients without a prior HF diagnosis. The 2021 ESC guidelines' algorithms were employed for HF diagnosis (HFpEF, HFmrEF, HFrEF). This study identifies two pre-heart failure (pre-HF) stages: "heart stress" (elevated NT-proBNP in asymptomatic individuals with risk factors, regardless of structural heart disease or cardiac dysfunction) and individuals "at risk for HF" (normal NTproBNP and at least one HF risk factor). Ultimately, all patients were categorized into six groups: (I) no HF, no risk; (II) at risk for HF; (III) heart stress; (IV) HFpEF; (V) HFmrEF; and (VI) HFrEF. Subsequently, the eleven clinical variables were compared among groups (II) to (VI) using chi-square test. Results Among 930 screened outpatients (mean age 66±11 years, 61% female), diagnosis of HF was established in 34.2% (Figure, pie). Heart stress was found in 22.3% patients, and 38.1% were at risk for HF, while 5.5 % had neither HF nor risk factors. Group comparison revealed that older individuals were more frequent in the HFpEF group, females predominated in the heart-stress and HFpEF groups, and males in the HFrEF group (Figure, table). Obesity was the most frequent among those at risk and HFmrEF. Atrial fibrillation and pathological ECG increased gradually from those at risk to HFrEF. Previous MI was the most common in heart stress and HFmrEF groups, while arterial hypertension >10 years prevailed in HFpEF and HFmrEF patients. Diabetes mellitus > 5 years was present in 24-28% across groups. CKD or eGFR≤60 ml/min/1.73m² increased gradually towards HFmrEF. The family history of CMP or SCD was positive in 17-24%, with no significant differences observed across groups. Additionally, a small number of patients had a history of previous cardiotoxic cancer treatment, and no significant differences were found between groups. Conclusions The mobile phone application used in primary care successfully identified a significant number of pre-heart failure patients requiring further evaluation. Different HF stages and phenotypes exhibit distinct clinical profiles, aiding in the screening process and contributing to a deeper understanding of the heart's pathophysiological adaptation to diverse risk factors during HF development.

Segatella clades adopt distinct roles within a single individual’s gut

Segatella is a prevalent genus within individuals’ gut microbiomes worldwide, especially in non-Western populations. Although metagenomic assembly and genome isolation have shed light on its genetic diversity, the lack of available isolates from this genus has resulted in a limited understanding of how members’ genetic diversity translates into phenotypic diversity. Within the confines of a single gut microbiome, we have isolated 63 strains from diverse lineages of Segatella. We performed comparative analyses that exposed differences in cellular morphologies, preferences in polysaccharide utilization, yield of short-chain fatty acids, and antibiotic resistance across isolates. We further show that exposure to Segatella isolates either evokes strong or muted transcriptional responses in human intestinal epithelial cells. Our study exposes large phenotypic differences within related Segatella isolates, extending this to host-microbe interactions.

Diversity of heart failure phenotypes in transthyretin amyloid cardiomyopathy. More than just heart failure with preserved ejection fraction

Introduction Current guidelines recommend suspecting transthyretin amyloid cardiomyopathy (ATTR-CM) in patients over 65 years of age with unexplained left ventricular (LV) hypertrophy in a non-dilated LV, heart failure (HF) and preserved ejection fraction (HFpEF), hypertrophic cardiomyopathy or severe aortic stenosis. However, there is evidence indicating a high prevalence of ATTR-CM in other HF phenotypes. As such, this study aimed to characterize the diversity of HF phenotypes of ATTR-CM by examining the LV ejection fraction and LV dilatation using echocardiography. Methods This multicentre, retrospective observational study included patients diagnosed with ATTR-CM between 2015–2023. The diagnosis was based on a positive cardiac biopsy or positive bone scintigraphy without monoclonal gammopathy. Echocardiographic measurements were categorized according to LV ejection fraction (LVEF) into HFpEF (LVEF ≥50%), HF with mildly reduced EF (HFmrEF, LVEF 40–49%), and HF with reduced EF (HFrEF, LVEF <40%). LV cavity size was categorized by LV end-diastolic diameter (LVEDD) and volume index (LVEDVi) as normal, moderately increased and severe dilatation. Results The study included 135 patients with ATTR-CM (mean age, 78 years; 89% male; 89% wild-type ATTR-CM). Most patients were screened for ATTR-CM because of unexplained HF and increased LV wall thickness (57%). Echocardiography showed LVEF <50% in 60% of the patients, with a significant portion presenting with HFrEF. Patients with LVEF <50% had higher NYHA class and elevated N-terminal pro-B-type natriuretic peptide levels than HFpEF patients. LV dilatation was observed in 43% of the patients, with 10% presenting with both LVEF <50% and severe LV dilatation. Conclusion This study revealed significant variability in HF phenotypes among patients with ATTR-CM, from HFpEF without LV dilatation to HFrEF with severe LV dilatation. Relying solely on HFpEF for screening may lead to under-diagnosis. These findings suggest the need for more comprehensive diagnostic criteria beyond echocardiographic measures to improve ATTR-CM detection and management.

A retrospective study on biotinidase deficiency: analysis of the Eastern Anatolia region patient cohort

ABTRACT This study retrospectively reviews individuals diagnosed with biotinidase deficiency in Eastern Anatolia to analyze the genetic variants and their relationship with biotinidase activity levels. The research focuses on determining the percentage impact of different variants on enzyme activity. The study included 357 patients who presented to Erzurum City Hospital with symptoms of biotinidase deficiency between 2018 and 2023 and were referred to the medical genetics department. Biotinidase enzyme levels were determined using spectrophotometric and colorimetric techniques, while Sanger sequencing analyzed the four exons and intron boundaries of the BTD gene. In the analysis of 357 patients (181 boys, 176 girls), the most frequent variant was c.1270G > C | p.Asp424His. Biotinidase enzyme activity was above 30% in 97.3% of patients with a homozygous p.D424His mutation. The mutations that caused the most significant decrease in enzyme activity were c.410G > A p.Arg137His, c.38_delinsTCC p.Cys13phefs*36, and c.1535C > T p.Thr512Met. Hearing loss (4 patients) and optic atrophy (1 patient) were mainly observed in patients with the c.38_delinsTCC mutation (homozygous or heterozygous). Most patients were asymptomatic, and mild symptoms were effectively prevented with biotin treatment. This study provides a detailed analysis of genetic diversity and clinical presentation in biotinidase deficiency cases in Eastern Anatolia, demonstrating the efficacy of biotin treatment. It highlights the significant role of genetic variants in phenotypic diversity and the need for personalized treatment, calling for further genetic research to enhance understanding of variant diversity and its impact on enzyme activity.

A Comprehensive Protocol for Microbead-Induced Ocular Hypertension in Mice.

Glaucoma is a common optic neuropathy characterized by degeneration of retinal ganglion cells (RGCs). Elevated intraocular pressure (IOP), that is, ocular hypertension, is the primary modifiable risk factor for glaucoma and the primary characteristic of most preclinical glaucoma models. Extensive genotype and phenotype diversity at relatively low cost and high accessibility makes laboratory mice an excellent preclinical model for glaucoma. The microbead occlusion model was introduced in 2010 as an inducible model of ocular hypertension in mice and is now one of the most extensively utilized models of rodent glaucoma. Subsequent modifications of the microbead model increased the magnitude and duration of IOP elevation, primarily through modification of injection materials. Despite its popularity, accessibility of the model is hindered by procedural consistency between users. Here we outline an updated and comprehensive protocol for execution of the microbead model that is focused on improving surgical and outcome measure consistency and on enabling single experimenter execution.

Distant Metastases of Breast Cancer Resemble Primary Tumors in Cancer Cell Composition but Differ in Immune Cell Phenotypes.

Breast cancer is the most commonly diagnosed cancer in women, with distant metastasis being the main cause of breast cancer-related deaths. Elucidating the changes in the tumor and immune ecosystems that are associated with metastatic disease is essential to improve understanding and ultimately treatment of metastasis. Here, we developed an in-depth, spatially resolved single-cell atlas of the phenotypic diversity of tumor and immune cells in primary human breast tumors and matched distant metastases, using imaging mass cytometry to analyze a total of 75 unique antibody targets. While the same tumor cell phenotypes were typically present in primary tumors and metastatic sites, suggesting a strong founder effect of the primary tumor, their proportions varied between matched samples. Notably, the metastatic site did not influence tumor phenotype composition, except for the brain. Metastatic sites exhibited a lower number of immune cells overall, but had a higher proportion of myeloid cells as well as exhausted and cytotoxic T cells. Myeloid cells showed distinct tissue-specific compositional signatures and increased presence of potentially matrix remodeling phenotypes in metastatic sites. This analysis of tumor and immune cell phenotypic composition of metastatic breast cancer highlights the heterogeneity of the disease within patients and across distant metastatic sites, indicating myeloid cells as the predominant immune modulators that could potentially be targeted at these sites.

Next-Generation Cancer Phenomics: A Transformative Approach to Unraveling Lung Cancer Complexity and Advancing Precision Medicine.

Lung cancer remains one of the leading causes of cancer-related deaths globally, with its complexity driven by intricate and intertwined genetic, epigenetic, and environmental factors. Despite advances in genomics, transcriptomics, and proteomics, understanding the phenotypic diversity of lung cancer has lagged behind. Next-generation phenomics, which integrates high-throughput phenotypic data with multiomics approaches and digital technologies such as artificial intelligence (AI), offers a transformative strategy for unraveling the complexity of lung cancer. This approach leverages advanced imaging, single-cell technologies, and AI to capture dynamic phenotypic variations at cellular, tissue, and whole organism levels and in ways resolved in temporal and spatial contexts. By mapping the high-throughput and spatially and temporally resolved phenotypic profiles onto molecular alterations, next-generation phenomics provides deeper insights into the tumor microenvironment, cancer heterogeneity, and drug efficacy, safety, and resistance mechanisms. Furthermore, integrating phenotypic data with genomic and proteomic networks allows for the identification of novel biomarkers and therapeutic targets in ways informed by biological structure and function, fostering precision medicine in lung cancer treatment. This expert review examines and places into context the current advances in next-generation phenomics and its potential to redefine lung cancer diagnosis, prognosis, and therapy. It highlights the emerging role of AI and machine learning in analyzing complex phenotypic datasets, enabling personalized therapeutic interventions. Ultimately, next-generation phenomics holds the promise of bridging the gap between molecular alterations and clinical and population health outcomes, providing a holistic understanding of lung cancer biology that could revolutionize its management and improve patient survival rates.

Distinct mechanisms drive divergent phenotypes in hypertrophic and dilated cardiomyopathy associated TPM1 variants.

Hypertrophic and dilated cardiomyopathies (HCM and DCM, respectively) are inherited disorders that may be caused by mutations to the same sarcomeric protein but have completely different clinical phenotypes. The precise mechanisms by which point mutations within the same gene bring about phenotypic diversity remain unclear. Our objective has been to develop a mechanistic explanation of diverging phenotypes in two TPM1 mutations, E62Q (HCM) and E54K (DCM). Drawing on data from the literature and experiments with stem cell-derived cardiomyocytes expressing the TPM1 mutations of interest, we constructed computational simulations that provide plausible explanations of the distinct muscle contractility caused by each variant. In E62Q, increased calcium sensitivity and hypercontractility was explained most accurately by a reduction in effective molecular stiffness of tropomyosin and alterations in its interactions with the actin thin filament that favor the 'closed' regulatory state. By contrast, the E54K mutation appeared to act via long-range allosteric interactions to increase the association rate of the C-terminal troponin I mobile domain to tropomyosin/actin. These mutation-linked molecular events produced diverging alterations in gene expression that can be observed in human engineered heart tissues. Modulators of myosin activity confirmed our proposed mechanisms by rescuing normal contractile behavior in accordance with predictions.

Phenotypic diversity of type III secretion system activity in enteropathogenic Escherichia coli clinical isolates.

Introduction. Enteropathogenic Escherichia coli (EPEC) strains pose a significant threat as a leading cause of severe childhood diarrhoea in developing nations. EPEC pathogenicity relies on the type III secretion system (T3SS) encoded by the locus of enterocyte effacement (LEE), facilitating the secretion and translocation of bacterial effector proteins.Gap Statement. While the regulatory roles of PerC (plasmid-encoded regulator) and GrlA (global regulator of LEE-activator) in ler expression and LEE gene activation are well-documented in the EPEC prototype strain E2348/69, understanding the variability in LEE gene expression control mechanisms among clinical EPEC isolates remains an area requiring further investigation.Aim. This study aims to explore the diversity in LEE gene expression control mechanisms among clinical EPEC isolates through a comparative analysis of secretion profiles under defined growth conditions favouring either PerC- or GrlA-mediated activation of LEE expression.Methodology. We compared T3SS-dependent secretion patterns and promoter expression in both typical EPEC (tEPEC) and atypical EPEC (aEPEC) clinical isolates under growth conditions favouring either PerC- or GrlA-mediated activation of LEE expression. Additionally, we conducted promoter reporter activity assays, quantitative real-time PCR and Western blot experiments to assess gene expression activity.Results. Significant differences in T3SS-dependent secretion were observed among tEPEC and aEPEC strains, independent of LEE sequence variations or T3SS gene functionality. Notably, a clinical tEPEC isolate exhibited increased secretion levels under repressive growth conditions and in the absence of both PerC and GrlA, implicating an alternative mechanism in the activation of Ler (LEE-encoded regulator) expression.Conclusion. Our findings indicate that uncharacterized LEE regulatory mechanisms contribute to phenotypic diversity among clinical EPEC isolates, though their impact on clinical outcomes remains unknown. This challenges the conventional understanding based on reference strains and highlights the need to investigate beyond established models to comprehensively elucidate EPEC pathogenesis.

Dog10K: an integrated Dog10K database summarizing canine multi-omics.

The diversity observed in canine breed phenotypes, together with their risk for heritabily disorders of relevance to dogs and humans, makes the species an ideal subject for studies aimed at understanding the genetic basis of complex traits and human biomedical models. Dog10K is an ongoing international collaboration that aims to uncover the genetic basis of phenotypic diversity, disease, behavior, and domestication history of dogs. To best present and make the extensive data accessible and user friendly, we have established the Dog10K (http://dog10k.kiz.ac.cn/) database, a comprehensive-omics resource summarizing multiple types of data. This database integrates single nucleotide variants (SNVs) from 1987 canine genomes, de-novo mutations (DNMs) from 43 dog breeds with>40×sequence, RNA-seq data of 105057 single nuclei from hippocampus, 74067 single cells from leukocytesand 30 blood samples from published canid studies. We provide clear visualization, statistics, browse, searching, and downloading functions for all data. We have integrated three analysis tools, Selscan, LiftOver and AgeConversion, to aid researchers in custom exploration of the comprehensive-omics data. The Dog10K database will serve as a foundational platform for analyzing, presenting and utilizing canine multi-omics data.

Genotype from Phenotype: Using CRISPR Screens to Dissect Lymphoma Biology.

Genome-wide screens are a powerful technique to dissect the complex network of genes regulating diverse cellular phenotypes. The recent adaptation of the CRISPR-Cas9 system for genome engineering has revolutionized functional genomic screening. Here, we present protocols used to introduce Cas9 into human lymphoma cell lines, produce high-titer lentivirus of a genome-wide sgRNA library, transduce and culture cells during the screen, select cells with a specified phenotype, isolate genomic DNA, and prepare a custom library for next-generation sequencing. These protocols were tailored for loss-of-function CRISPR screens in human B-cell lymphoma cell lines but are highly amenable for other experimental purposes.

Genetic Variation, Polyploidy, Hybridization Influencing the Aroma Profiles of Rosaceae Family.

The fragrance and aroma of Rosaceae plants are complex traits influenced by a multitude of factors, with genetic variation standing out as a key determinant which is largely impacted by polyploidy. Polyploidy serves as a crucial evolutionary mechanism in plants, significantly boosting genetic diversity and fostering speciation. This review focuses on the Rosaceae family, emphasizing how polyploidy influences the production of volatile organic compounds (VOCs), which are essential for the aromatic characteristics of economically important fruits like strawberries, apples, and cherries. The review delves into the biochemical pathways responsible for VOC biosynthesis, particularly highlighting the roles of terpenoids, esters alcohols, aldehydes, ketones, phenolics, hydrocarbons, alongside the genetic mechanisms that regulate these pathways. Key enzymes, such as terpene synthases and alcohol acyltransferases, are central to this process. This review further explores how polyploidy and hybridization can lead to the development of novel metabolic pathways, contributing to greater phenotypic diversity and complexity in fruit aromas. It underscores the importance of gene dosage effects, isoenzyme diversity, and regulatory elements in determining VOC profiles. These findings provide valuable insights for breeding strategies aimed at improving fruit quality and aligning with consumer preferences. Present review not only elucidates the complex interplay between genomic evolution and fruit aroma but also offers a framework for future investigations in plant biology and agricultural innovation.

A Descriptive Study on the Phenotypic Variability of Pseudomonas aeruginosa Identified by MALDI-TOF

This descriptive study investigates the phenotypic variability of 50 Pseudomonas aeruginosa colonies isolated from wastewater, identified using MALDI-TOF mass spectrometry. The contamination of wastewater by opportunistic pathogens like P. aeruginosa poses significant public health risks due to their potential to cause severe infections and contribute to the spread of antimicrobial resistance. Pseudomonas aeruginosa is particularly concerning because of its remarkable adaptability, resilience, and intrinsic and acquired antibiotic resistance mechanisms, including the production of beta-lactamases, efflux pumps, and target site mutations. Our study highlights the phenotypic diversity and antibiotic resistance profiles of P. aeruginosa strains isolated from urban and hospital environments. Using MALDI-TOF MS, we rapidly and accurately characterized these strains, providing species-level identification within minutes. This technology surpasses traditional biochemical methods in speed and accuracy, revolutionizing microbial diagnostics by offering a high-throughput, cost-effective, and reliable tool. By analyzing the phenotypic traits and resistance mechanisms of these strains, we aim to provide critical insights into their ecology and inform strategies to mitigate the risks associated with their presence in the environment. The antibiotic resistance profiles revealed varied susceptibility among the strains, with notable resistance to drugs such as erythromycin, cefoxitin, and tetracycline. The study's findings underscore the importance of integrating advanced diagnostic technologies like MALDI-TOF MS into routine environmental monitoring and public health strategies to address the challenges posed by P. aeruginosa in wastewater. Ultimately, this research contributes to understanding the dynamics of contamination and resistance in urban environments. By detailing the methodology used for the identification and characterization of the strains, as well as the results obtained, this publication aims to provide a valuable database for researchers and practitioners engaged in combating nosocomial infections and environmental pollution by P. aeruginosa. This study highlights the need for effective management measures to control the dissemination of this pathogen in aquatic systems, promoting public health and environmental safety.

A Brief Review on Caenorhabditis elegans Role in Modelling Neurodegenerative Disease.

A small, translucent nematode known as Caenorhabditis elegans, or C. elegans, is frequently utilized as a model organism in biomedical studies. These worms, which are around 1 mm long and feed on bacteria, are usually found in soil. For accessible and effective research on genetics, developmental biology, neuroscience, cell biology, and aging, C. elegans provide an ideal model. Its simplicity, which includes a translucent body and a nervous system with only 302 neurons, makes it possible to see cellular and developmental processes in great detail. Because of its special benefits, the worm Caenorhabditis elegans allows for a thorough characterization of the cellular and molecular processes causing age-related neurodegenerative diseases. This is a general review of the life cycle, experimental methodologies, and the use of C. elegans to model brain diseases, including those related to molecular and genetic factors that cause neurodegenerative diseases. Additionally, we go over how C. elegans is a perfect model organism for studying neurons in instances of prevalent age-related neurodegenerative illnesses due to a combination of its biological traits and new analytical techniques. The literature review process was carried out step-by-step using online search databases such as Web of Science, PubMED, Embase, Google Scholar, Medline, and Google Patents. In the first searches, keywords like C.elegans, disease modelling, and neuroprotective activity were employed. Because of C. elegans's physiological transparency, it is possible to track the development of neurodegeneration in aging organisms by using co-expressed fluorescent proteins. Importantly, a fully characterized connectome provides a unique ability to precisely connect cellular death with behavioural instability or phenotypic diversity in vivo, thus permitting a deep knowledge of the detrimental effect of neurodegeneration on wellbeing. In addition, pharmacological therapies and both forward and reverse gene screening speed up the discovery of modifiers that change neurodegeneration. These chemical-genetic investigations work together to determine important threshold states that either increase or decrease cellular stress in order to unravel related pathways.

High phenotypic diversity correlated with genomic variation across the European Batrachochytrium salamandrivorans epizootic.

Recognizing the influence of pathogen diversity on infection dynamics is crucial for mitigating emerging infectious diseases. Characterising such diversity is often complex, for instance when multiple pathogen variants exist that interact differently with the environment and host. Here, we explore genotypic and phenotypic variation of Batrachochytrium salamandrivorans (Bsal), an emerging fungal pathogen that is driving declines among an increasing number of European amphibian species. For thirteen isolates, spanning most of the known temporal and geographical Bsal range in Europe, we mapped phenotypic diversity through numerous measurements that describe varying reproductive rates in vitro across a range of temperatures. Bsal isolates are revealed to have different thermal optima and tolerances, with phenotypic variation correlating with genomic diversity. Using a mechanistic niche model of the fire salamander (Salamandra salamandra) as an example, we illustrate how host steady-state body temperature and Bsal thermal range variation may influence pathogen growth through space and time across Europe. Our combined findings show how the identity of emergent pathogen variants may strongly influence when and which host populations are most at risk.

Comprehensive evaluation and guidance of structural variation detection tools in chicken whole genome sequence data

BackgroundStructural variations (SVs) are widespread across genome and have a great impact on evolution, disease, and phenotypic diversity. Despite the development of numerous bioinformatic tools, commonly referred to as SV callers, tailored for detecting SVs using whole genome sequence (WGS) data and employing diverse algorithms, their performance necessitates rigorous evaluation with real data and validated SVs. Moreover, a considerable proportion of these tools have been primarily designed and optimized using human genome data. Consequently, their applicability and performance in Avian species, characterized by smaller genomes and distinct genomic architectures, remain inadequately assessed.ResultsWe performed a comprehensive assessment of the performance of ten widely used SV callers using population-level real genomic data with the validated five common types of SVs. The performance of SV callers varies with the types and sizes of SVs. As compared with other tools, GRIDSS, Lumpy, Wham, and Manta present better detection accuracy. Pindel can detect more small SVs than others. CNVnator and CNVkit can detect more medium and large copy number variations. Given the poor consistency among different SV callers, the combination calling strategy is not recommended. All tools show poor ability in the detection of insertions (especially with size > 150 bp). At least 50× read depth is required to detect more than 80% of the SVs for most tools.ConclusionsThis study highlights the importance and necessity of using real sequencing data, rather than simulated data only, with validated SVs for SV caller evaluation. Some practical guidance and suggestions are provided for SV detection in future researches.

Chemical Diversity of Aspergillus alliaceus Phenotypes: Discovery of Brominated Bianthrones with Activity against Triple-Negative Breast Cancer Cell Lines.

Marine-derived fungi have emerged as a source for novel metabolites with a broad range of bioactivities. However, accessing the full potential of fungi under standard laboratory conditions remains challenging. LC-MS-based metabolomics in combination with varied culture conditions is a fast and powerful tool to detect new metabolites. Here, three developmental forms of the marine-derived fungus Aspergillus alliaceus were analyzed and 14 fungal metabolites, including new brominated polyketides (11-14) were isolated. Structure elucidation relied mainly on 1D and 2D NMR techniques and was supported by low- and high-resolution mass spectrometry and DFT-based computations. We sequenced the A. alliaceus genome, identified the bianthrone-producing biosynthetic gene cluster, and conducted expression analysis on genes involved in sexual development and biosynthesis. The NCI-60 cell line panel revealed selective in vitro activity against triple-negative breast cancer (TNBC) for the halogenated allianthrones and their full antiproliferative and cytotoxic effects were evaluated in five TNBC cell lines.