Biological Questions Research Articles

Some tips and tricks for a Correlative Light Electron Microscopy workflow using stable expression of fluorescent proteins.

Correlative Light Electron Microscopy (CLEM) encompasses a wide range of experimental approaches with different degrees of complexity and technical challenges where the attributes of both light and electron microscopy are combined in a single experiment. Although the biological question always determines what technology is the most appropriate, we generally set out to apply the simplest workflow possible. For 2D cell cultures expressing fluorescently tagged molecules, we report on a simple and very powerful CLEM approach by using gridded finder imaging dishes. We first determine the gross localization of the fluorescence using light microscopy and subsequently we retrace the origin/localization of the fluorescence by projecting it onto the ultrastructural reference space obtained by transmission electron microscopy (TEM). Here we describe this workflow and highlight some basic principles of the sample preparation for such a simple CLEM experiment. We will specifically focus on the steps following the resin embedding for TEM and the introduction of the sample in the electron microscope.

A Hitchhiker's guide to high-dimensional tissue imaging with multiplexed ion beam imaging.

Advancements in multiplexed tissue imaging technologies are vital in shaping our understanding of tissue microenvironmental influences in disease contexts. These technologies now allow us to relate the phenotype of individual cells to their higher-order roles in tissue organization and function. Multiplexed Ion Beam Imaging (MIBI) is one of such technologies, which uses metal isotope-labeled antibodies and secondary ion mass spectrometry (SIMS) to image more than 40 protein markers simultaneously within a single tissue section. Here, we describe an optimized MIBI workflow for high-plex analysis of Formalin-Fixed Paraffin-Embedded (FFPE) tissues following antigen retrieval, metal isotope-conjugated antibody staining, imaging using the MIBI instrument, and subsequent data processing and analysis. While this workflow is focused on imaging human FFPE samples using the MIBI, this workflow can be easily extended to model systems, biological questions, and multiplexed imaging modalities.

Efficient Generation of CRISPR/Cas9-Mediated Knockout Human Primary Keratinocytes by Electroporation.

Due to their full differentiation capacity in vitro, the culture of human primary keratinocytes (HPKs) represents a physiological model for answering basic biological and dermatological research questions, including those related to skin diseases and the investigation of treatment options. When modified with the CRISPR/Cas9 gene editing approach and cultivated in organotypic 3D epidermal equivalents (EEs), these human cells have the potential to replace established mouse models. However, even when cultivated on feeder cells, HPKs have only a low proliferation capacity in 2D culture, limiting their application potential. This is particularly true for CRISPR/Cas9-modified HPKs, whose generation commonly requires selection of targeted cells, negatively affecting their lifespan. Here, we describe a robust protocol for the rapid, simple, and efficient generation of single- and multi-gene CRISPR/Cas9 knockout HPKs by electroporation of ribonucleoprotein (RNP) complexes, which comprise one or multiple guide RNAs (gRNAs) and Cas9 protein. Unlike DNA transfection or virus-based targeting strategies, electroporation of RNPs represents a targeting approach that minimizes immunological and toxic side effects. Using efficient gRNAs results in the generation of HPKs with a high yield of knockout cells, allowing for their immediate use in experiments without requiring the laborious process of selecting targeted cells or maintaining a feeder cell culture. Furthermore, the use of RNPs and their delivery via electroporation minimizes off-target and other unspecific effects, preventing unintended genomic alterations. Most importantly, CRISPR/Cas9 knockout HPKs generated with this protocol have the ability to form a fully differentiated epidermis in 3D, thus facilitating the understanding of specific protein functions in a highly physiological human skin model. Alternatively, this approach proves valuable for generating models of mono- or polygenic skin diseases via knockouts, providing insights into the underlying molecular mechanisms and facilitating the development of novel therapeutic approaches.

Whole-Genome Bisulfite Sequencing Protocol for the Analysis of Genome-Wide DNA Methylation and Hydroxymethylation Patterns at Single-Nucleotide Resolution.

The analysis of genome-wide epigenomic alterations including DNA methylation and hydroxymethylation has become a subject of intensive research for many biological and clinical questions. DNA methylation analysis bears the particular promise to supplement or replace biochemical and imaging-based tests for the next generation of personalized medicine. Whole-genome bisulfite sequencing (WGBS) using next-generation sequencing technologies is currently considered the gold standard for a comprehensive and quantitative analysis of DNA methylation throughout the genome. However, bisulfite conversion does not allow distinguishing between cytosine methylation and hydroxymethylation requiring an additional chemical or enzymatic step to identify hydroxymethylated cytosines. Here, we provide a detailed protocol based on a commercial kit for the preparation of sequencing libraries for the comprehensive whole-genome analysis of DNA methylation and/or hydroxymethylation. The protocol is based on the construction of sequencing libraries from limited amounts of input DNA by ligation of methylated adaptors to the fragmented DNA prior to bisulfite conversion. For analyses requiring a quantitative distinction between 5-methylcytosine and 5-hydroxymethylcytosines levels, an oxidation step is included in the same workflow to perform oxidative bisulfite sequencing (OxBs-Seq). In this case, two sequencing libraries will be generated and sequenced: a classic methylome following bisulfite conversion and analyzing modified cytosines (not distinguishing between methylated and hydroxymethylated cytosines) and a methylome analyzing only methylated cytosines, respectively. Hydroxymethylation levels are deduced from the differences between the two reactions. We also provide a step-by-step description of the data analysis using publicly available bioinformatic tools. The described protocol has been successfully applied to different human and plant samples and yields robust and reproducible results.

Preparation of Xenopus borealis and Xenopus tropicalis Egg Extracts for Comparative Cell Biology and Evolutionary Studies.

Cytoplasmic extracts prepared from eggs of the African clawed frog Xenopus laevis are extensively used to study various cellular events including the cell cycle, cytoskeleton dynamics, and cytoplasm organization, as well as the biology of membranous organelles and phase-separated non-membrane-bound structures. Recent development of extracts from eggs of other Xenopus allows interspecies comparisons that provide new insights into morphological and biological size variations and underlying mechanisms across evolution. Here, we describe methods to prepare cytoplasmic extracts from eggs of the allotetraploid Marsabit clawed frog, Xenopus borealis, and the diploid Western clawed frog, Xenopus tropicalis. We detail mixing and "hybrid" experiments that take advantage of the physiological but highly accessible nature of extracts to reveal the evolutionary relationships across species. These new developments create a robust and versatile toolbox to elucidate molecular, cell biological, and evolutionary questions in essential cellular processes.

Protein structures unravel the signatures and patterns of deep time evolution.

The formulation and testing of hypotheses using 'big biology data' often lie at the interface of computational biology and structural biology. The Protein Data Bank (PDB), which was established about 50years ago, catalogs three-dimensional (3D) shapes of organic macromolecules and showcases a structural view of biology. The comparative analysis of the structures of homologs, particularly of proteins, from different species has significantly improved the in-depth analyses of molecular and cell biological questions. In addition, computational tools that were developed to analyze the 'protein universe' are providing the means for efficient resolution of longstanding debates in cell and molecular evolution. In celebrating the golden jubilee of the PDB, much has been written about the transformative impact of PDB on a broad range of fields of scientific inquiry and how structural biology transformed the study of the fundamental processes of life. Yet, the transforming influence of PDB on one field of inquiry of fundamental interest-the reconstruction of the distant biological past-has gone almost unnoticed. Here, I discuss the recent advances to highlight how insights and tools of structural biology are bearing on the data required for the empirical resolution of vigorously debated and apparently contradicting hypotheses in evolutionary biology. Specifically, I show that evolutionary characters defined by protein structure are superior compared to conventional sequence characters for reliable, data-driven resolution of competing hypotheses about the origins of the major clades of life and evolutionary relationship among those clades. Since the better quality data unequivocally support two primary domains of life, it is imperative that the primary classification of life be revised accordingly.

Study of tree shrew biology and models: A booming and prosperous field for biomedical research.

The tree shrew ( Tupaia belangeri) has long been proposed as a suitable alternative to non-human primates (NHPs) in biomedical and laboratory research due to its close evolutionary relationship with primates. In recent years, significant advances have facilitated tree shrew studies, including the determination of the tree shrew genome, genetic manipulation using spermatogonial stem cells, viral vector-mediated gene delivery, and mapping of the tree shrew brain atlas. However, the limited availability of tree shrews globally remains a substantial challenge in the field. Additionally, determining the key questions best answered using tree shrews constitutes another difficulty. Tree shrew models have historically been used to study hepatitis B virus (HBV) and hepatitis C virus (HCV) infection, myopia, and psychosocial stress-induced depression, with more recent studies focusing on developing animal models for infectious and neurodegenerative diseases. Despite these efforts, the impact of tree shrew models has not yet matched that of rodent or NHP models in biomedical research. This review summarizes the prominent advancements in tree shrew research and reflects on the key biological questions addressed using this model. We emphasize that intensive dedication and robust international collaboration are essential for achieving breakthroughs in tree shrew studies. The use of tree shrews as a unique resource is expected to gain considerable attention with the application of advanced techniques and the development of viable animal models, meeting the increasing demands of life science and biomedical research.

Tracking of lineage mass via quantitative phase imaging and confinement in low refractive index microwells.

Measurements of cell lineages are central to a variety of fundamental biological questions, ranging from developmental to cancer biology. However, accurate lineage tracing requires nearly perfect cell tracking, which can be challenging due to cell motion during imaging. Here we demonstrate the integration of microfabrication, imaging, and image processing approaches to demonstrate a platform for cell lineage tracing. We use quantitative phase imaging (QPI), a label-free imaging approach that quantifies cell mass. This gives an additional parameter, cell mass, that can be used to improve tracking accuracy. We confine lineages within microwells fabricated to reduce cell adhesion to sidewalls made of a low refractive index polymer. This also allows the microwells themselves to serve as references for QPI, enabling measurement of cell mass even in confluent microwells. We demonstrate application of this approach to immortalized adherent and nonadherent cell lines as well as stimulated primary B cells cultured ex vivo. Overall, our approach enables lineage tracking, or measurement of lineage mass, in a platform that can be customized to varied cell types.

A Decision Tree to Guide Human and Mouse Mammary Organoid Model Selection.

Over the past 50 years, researchers from the mammary gland field have launched a collection of distinctive 3D cell culture systems to study multiple aspects of mammary gland physiology and disease. As our knowledge about the mammary gland evolves, more sophisticated 3D cell culture systems are required to answer more and more complex questions. Nowadays, morphologically complex mammary organoids can be generated in distinct 3D settings, along with reproduction of multiple aspects of the gland microenvironment. Yet, each 3D culture protocol comes with its advantages and limitations, where some culture systems are best suited to study stemness potential, whereas others are tailored towards the study of mammary gland morphogenesis. Therefore, prior to starting a 3D mammary culture experiment, it is important to consider and select the ideal culture model to address the biological question of interest. The number and technical requirements of novel 3D cell culture methods vastly increased over the past decades, making it currently challenging and time consuming to identify the best experimental testing. In this chapter, we provide a summary of the most promising murine and human 3D organoid models that are currently used in mammary gland biology research. For each model, we will provide a brief description of the protocol and an overview of the expected morphological outcome, the advantages of the model, and the potential pitfalls, to guide the reader to the best model of choice for specific applications.

High-Resolution Disease Phenotyping Reveals Distinct Resistance Mechanisms of Tomato Crop Wild Relatives against Sclerotinia sclerotiorum.

Besides the well-understood qualitative disease resistance, plants possess a more complex quantitative form of resistance: quantitative disease resistance (QDR). QDR is commonly defined as a partial but more durable form of resistance and, therefore, might display a valuable target for resistance breeding. The characterization of QDR phenotypes, especially of wild crop relatives, displays a bottleneck in deciphering QDR's genomic and regulatory background. Moreover, the relationship between QDR parameters, such as infection frequency, lag-phase duration, and lesion growth rate, remains elusive. High hurdles for applying modern phenotyping technology, such as the low availability of phenotyping facilities or complex data analysis, further dampen progress in understanding QDR. Here, we applied a low-cost (<1.000 €) phenotyping system to measure lesion growth dynamics of wild tomato species (e.g., Solanum pennellii or Solanum pimpinellifolium). We provide insight into QDR diversity of wild populations and derive specific QDR mechanisms and their cross-talk. We show how temporally continuous observations are required to dissect end-point severity into functional resistance mechanisms. The results of our study show how QDR can be maintained by facilitating different defense mechanisms during host-parasite interaction and that the capacity of the QDR toolbox highly depends on the host's genetic context. We anticipate that the present findings display a valuable resource for more targeted functional characterization of the processes involved in QDR. Moreover, we show how modest phenotyping technology can be leveraged to help answer highly relevant biological questions.

Proteomic Analysis of In Vitro Plant Tissues (Coffea canephora): A Case of Study.

Since the term proteomics was coined by Marc Wilkins in 1994, there has been an explosion in the number of articles reporting the use of the proteomics technique. As the layers of biological organization and their regulation increase, the complexity of living beings increases. Thus, we go from the genome to tissues, cells, cellular compartments, and phenotypes and the complexity of the tools used to study this complexity also increases. Unlike the genome study, in the case of the proteome, we have a more complex panorama. We have a spatial and temporal proteome. Proteomics helps to answer complex biological questions since proteins' function depends on their molecular structure, subcellular localization, and posttranslational modifications. In this protocol, we describe a methodology to extract proteins using different methods, separating proteins by electrophoresis in double-dimensional gels and analyzing the gels using specialized software that allows obtaining information on the number and abundance of the proteins from the gels.

Identification and engineering of potent cyclic peptides with selective or promiscuous binding through biochemical profiling and bioinformatic data analysis.

As our understanding of biological systems grows, so does the need to selectively target individual or multiple members of specific protein families in order to probe their function. Many targets of current biological and pharmaceutical interest are part of a large family of closely related proteins and achieving ligand selectivity often remains either an elusive or time-consuming endeavour. Cyclic peptides (CPs) occupy a key niche in ligand space, able to achieve high affinity and selectivity while retaining synthetic accessibility. De novo cyclic peptide ligands can be rapidly generated against a given target using mRNA display. In this study we harness mRNA display technology and the wealth of next generation sequencing (NGS) data generated to explore both experimental approaches and bioinformatic, statistical data analysis of peptide enrichment in cross-screen selections to rapidly generate high affinity CPs with differing intra-family protein selectivity profiles against fibroblast growth factor receptor (FGF-R) family proteins. Using these methods, CPs with distinct selectivity profiles can be generated which can serve as valuable tool compounds to decipher biological questions.

Neurodevelopmental disorders: 2024 update.

Neurodevelopmental disorders encompass a range of conditions such as intellectual disability, autism spectrum disorder, rare genetic disorders and developmental and epileptic encephalopathies, all manifesting during childhood. Over 1,500 genes involved in various signaling pathways, including numerous transcriptional regulators, spliceosome elements, chromatin-modifying complexes and de novo variants have been recognized for their substantial role in these disorders. Along with new machine learning tools applied to neuroimaging, these discoveries facilitate genetic diagnoses, providing critical insights into neuropathological mechanisms and aiding in prognosis, and precision medicine. Also, new findings underscore the importance of understanding genetic contributions beyond protein-coding genes and emphasize the role of RNA and non-coding DNA molecules but also new players, such as transposable elements, whose dysregulation generates gene function disruption, epigenetic alteration, and genomic instability. Finally, recent developments in analyzing neuroimaging now offer the possibility of characterizing neuronal cytoarchitecture in vivo, presenting a viable alternative to traditional post-mortem studies. With a recently launched digital atlas of human fetal brain development, these new approaches will allow answering complex biological questions about fetal origins of cognitive function in childhood. In this review, we present ten fascinating topics where major progress has been made in the last year.

Approaches for the Analysis and Interpretation of Whole-Genome Bisulfite Sequencing Data.

DNA methylation is a covalent modification of DNA that plays important roles in processes such as the regulation of gene expression, transcription factor binding, and suppression of transposable elements. The use of whole-genome bisulfite sequencing (WGBS) enables the genome-wide identification and quantification of DNA methylation patterns at single-base resolution and is the gold standard for the analysis of DNA methylation. However, the computational analysis of WGBS data can be particularly challenging, as many computationally intensive steps are required. Here, we outline step-by-step an approach for the analysis and interpretation of WGBS data. First, sequencing reads must be trimmed, quality-checked, and aligned to the genome. Second, DNA methylation levels are estimated at each cytosine position using the aligned sequence reads of the bisulfite-treated DNA. Third, regions of differential cytosine methylation between samples can be identified. Finally, these data need to be visualized and interpreted in the context of the biological question at hand.

Analysis of Creative Thinking Ability of Class X Students in Solving Biology Problems on Viruses

Background: This study aims to analyze descriptively students' creative thinking skills in solving biology questions regarding viruses at class X level at MA Mazro'atul Huda Wonorenggo Demak, based on the results of written test answers given by researchers to students. Methods: The type of research is quantitative research with data in the form of numbers that are processed using simple statistical formulas. The object of this study was the 20 students in class X as a population research. Data collection techniques used were written tests, interviews, observation and documentation. The statistical analysis is simple in the form of percentage data. Results: From the analysis conducted on the creative thinking abilities of class X MIPA 1 MA Mazro'atul Huda Wonorenggo Demak, it can be concluded that students' creative thinking abilities are in the high category with a percentage of 55%. The highest percentage is in the level of detail with a percentage of 70%, while the lowest percentage is in the level of fluency and novelty with the same percentage, namely 59%. Conclusion: Students who have high level abilities are able to fulfill all categories in the indicator, students who have medium levels are able to fulfill several indicator categories, while students who have low level abilities, have not been able to fulfill all categories in indicators. Keywords : Creative thinking ability; Biology; Virus

Tissue clearing and imaging approaches for in toto analysis of the reproductive system†.

New microscopy techniques in combination with tissue clearing protocols and emerging analytical approaches have presented researchers with the tools to understand dynamic biological processes in a three-dimensional context. This paves the road for the exploration of new research questions in reproductive biology, for which previous techniques have provided only approximate resolution. These new methodologies now allow for contextualized analysis of far-larger volumes than was previously possible. Tissue optical clearing and three-dimensional imaging techniques posit the bridging of molecular mechanisms, macroscopic morphogenic development, and maintenance of reproductive function into one cohesive and comprehensive understanding of the biology of the reproductive system. In this review, we present a survey of the various tissue clearing techniques and imaging systems, as they have been applied to the developing and adult reproductive system. We provide an overview of tools available for analysis of experimental data, giving particular attention to the emergence of artificial intelligence-assisted methods and their applicability to image analysis. We conclude with an evaluation of how novel image analysis approaches that have been applied to other organ systems could be incorporated into future experimental evaluation of reproductive biology.

Computational Modeling Insights into Extreme Heterogeneity in COVID-19 Nasal Swab Data.

Throughout the COVID-19 pandemic, an unprecedented level of clinical nasal swab data from around the globe has been collected and shared. Positive tests have consistently revealed viral titers spanning six orders of magnitude! An open question is whether such extreme population heterogeneity is unique to SARS-CoV-2 or possibly generic to viral respiratory infections. To probe this question, we turn to the computational modeling of nasal tract infections. Employing a physiologically faithful, spatially resolved, stochastic model of respiratory tract infection, we explore the statistical distribution of human nasal infections in the immediate 48 h of infection. The spread, or heterogeneity, of the distribution derives from variations in factors within the model that are unique to the infected host, infectious variant, and timing of the test. Hypothetical factors include: (1) reported physiological differences between infected individuals (nasal mucus thickness and clearance velocity); (2) differences in the kinetics of infection, replication, and shedding of viral RNA copies arising from the unique interactions between the host and viral variant; and (3) differences in the time between initial cell infection and the clinical test. Since positive clinical tests are often pre-symptomatic and independent of prior infection or vaccination status, in the model we assume immune evasion throughout the immediate 48 h of infection. Model simulations generate the mean statistical outcomes of total shed viral load and infected cells throughout 48 h for each "virtual individual", which we define as each fixed set of model parameters (1) and (2) above. The "virtual population" and the statistical distribution of outcomes over the population are defined by collecting clinically and experimentally guided ranges for the full set of model parameters (1) and (2). This establishes a model-generated "virtual population database" of nasal viral titers throughout the initial 48 h of infection of every individual, which we then compare with clinical swab test data. Support for model efficacy comes from the sampling of infection dynamics over the virtual population database, which reproduces the six-order-of-magnitude clinical population heterogeneity. However, the goal of this study is to answer a deeper biological and clinical question. What is the impact on the dynamics of early nasal infection due to each individual physiological feature or virus-cell kinetic mechanism? To answer this question, global data analysis methods are applied to the virtual population database that sample across the entire database and de-correlate (i.e., isolate) the dynamic infection outcome sensitivities of each model parameter. These methods predict the dominant, indeed exponential, driver of population heterogeneity in dynamic infection outcomes is the latency time of infected cells (from the moment of infection until onset of viral RNA shedding). The shedding rate of the viral RNA of infected cells in the shedding phase is a strong, but not exponential, driver of infection. Furthermore, the unknown timing of the nasal swab test relative to the onset of infection is an equally dominant contributor to extreme population heterogeneity in clinical test data since infectious viral loads grow from undetectable levels to more than six orders of magnitude within 48 h.

Fluorescent Probes Based on Charge and Proton Transfer for Probing Biomolecular Environment.

Fluorescent probes for sensing fundamental properties of biomolecular environment, such as polarity and hydration, help to study assembly of lipids into biomembranes, sensing interactions of biomolecules and imaging physiological state of the cells. Here, we summarize major efforts in the development of probes based on two photophysical mechanisms: (i) an excited-state intramolecular charge transfer (ICT), which is represented by fluorescent solvatochromic dyes that shift their emission band maximum as a function of environment polarity and hydration; (ii) excited-state intramolecular proton transfer (ESIPT), with particular focus on 5-membered cyclic systems, represented by 3-hydroxyflavones, because they exhibit dual emission sensitive to the environment. For both ICT and ESIPT dyes, the design of the probes and their biological applications are summarized. Thus, dyes bearing amphiphilic anchors target lipid membranes and report their lipid organization, while targeting ligands direct them to specific organelles for sensing their local environment. The labels, amino acid and nucleic acid analogues inserted into biomolecules enable monitoring their interactions with membranes, proteins and nucleic acids. While ICT probes are relatively simple and robust environment-sensitive probes, ESIPT probes feature high information content due their dual emission. They constitute a powerful toolbox for addressing multitude of biological questions.

In Vitro Models for Investigating Intestinal Host-Pathogen Interactions.

Infectious diseases are increasingly recognized as a major threat worldwide due to the rise of antimicrobial resistance and the emergence of novel pathogens. In vitro models that can adequately mimic in vivo gastrointestinal physiology are in high demand to elucidate mechanisms behind pathogen infectivity, and to aid the design of effective preventive and therapeutic interventions. There exists a trade-off between simple and high throughput models and those that are more complex and physiologically relevant. The complexity of the model used shall be guided by the biological question to be addressed. This review provides an overview of the structure and function of the intestine and the models that are developed to emulate this. Conventional models are discussed in addition to emerging models which employ engineering principles to equip them with necessary advanced monitoring capabilities for intestinal host-pathogen interrogation. Limitations of current models and future perspectives on the field are presented.

Multiple genomic solutions for local adaptation in two closely related species (sheep and goats) facing the same climatic constraints.

The question of how local adaptation takes place remains a fundamental question in evolutionary biology. The variation of allele frequencies in genes under selection over environmental gradients remains mainly theoretical and its empirical assessment would help understanding how adaptation happens over environmental clines. To bring new insights to this issue we set up a broad framework which aimed to compare the adaptive trajectories over environmental clines in two domesticated mammal species co-distributed in diversified landscapes. We sequenced the genomes of 160 sheep and 161 goats extensively managed along environmental gradients, including temperature, rainfall, seasonality and altitude, to identify genes and biological processes shaping local adaptation. Allele frequencies at putatively adaptive loci were rarely found to vary gradually along environmental gradients, but rather displayed a discontinuous shift at the extremities of environmental clines. Of the 430 candidate adaptive genes identified, only 6 were orthologous between sheep and goats and those responded differently to environmental pressures, suggesting different putative mechanisms involved in local adaptation in these two closely related species. Interestingly, the genomes of the 2 species were impacted differently by the environment, genes related to signatures of selection were most related to altitude, slope and rainfall seasonality for sheep, and summer temperature and spring rainfall for goats. The diversity of candidate adaptive pathways may result from a high number of biological functions involved in the adaptations to multiple eco-climatic gradients, and a differential role of climatic drivers on the two species, despite their co-distribution along the same environmental gradients. This study describes empirical examples of clinal variation in putatively adaptive alleles with different patterns in allele frequency distributions over continuous environmental gradients, thus showing the diversity of genetic responses in adaptive landscapes and opening new horizons for understanding genomics of adaptation in mammalian species and beyond.