Biology Methods and Protocols最新文献

A new pre-clinical method for capturing breath samples from intubated mice is presented. This method significantly reduces background levels, allowing more accurate measurements of VOCs originating from the breath ("on-breath") as opposed to background contamination. The method was developed by integrating industry-standard volatile-capturing sorbent tubes with respiratory mechanics measurement equipment (flexiVent^®), resulting in a mouse breath sample that can be transported and analyzed by TD-GC-MS and other central lab technologies. Using the methodology, the discrimination between on-breath VOCs from background compounds provides a cleaner dataset, which can accelerate the validation of VOCs identified from mouse models and their translation to clinical trials. Three metrics were developed to identify on-breath VOCs, with 22 identified using Type 1 (50% of the breath samples exceeding three standard deviations above the mean signal of the system blanks), 34 with Type 2 (P-value ≤ .05 between paired breath and blank samples), and 61 with Type 3 (ROC-AUC value ≥ 0.8 to differentiate between breath and blank samples). The number of compounds seen at elevated levels on mouse breath was quantified and compared to the levels seen on human breath samples to compare methodologies.

Instance segmentation is the task of assigning unique identifiers to individual objects in images. Solving this task requires breaking the inherent symmetry that semantically similar objects must result in distinct outputs. Deep learning algorithms bypass this break-of-symmetry by training specialized predictors or by utilizing intermediate label representations. However, many of these approaches break down when faced with overlapping labels that are ubiquitous in biomedical imaging, for instance for segmenting cell layers. Here, we discuss the reason for this failure and offer a novel approach for instance segmentation based on diffusion models that breaks this symmetry spontaneously. Our method outputs pixel-level instance segmentations matching the performance of models such as cellpose on the cellpose fluorescent cell dataset, while also permitting overlapping labels.

Molecular profiling is a crucial aspect of cancer therapy selection, underscoring the necessity for representative sampling of both tumor and normal tissues. While much attention has been given to representative tumor sampling, there has been a notable lack of exploration into the issue of poor RNA quality in normal breast tissue processing. Normal breast tissue from the same patient is often used as a negative control for most "-omics" experiments. RNA extracted from normal breast tissues frequently contains nucleic acids from surrounding adipocytes, endothelial cells, and immune cells, leading to a low representation of ductal elements and skewed results. Therefore, ensuring a complete representation of breast glandular tissue is imperative. The study aimed to investigate the variations in RNA enrichment between a random sampling technique and a targeted sampling approach when visually selecting normal breast tissue sections as negative controls for "-omics" experiments. Fifteen female breast cancer subjects who underwent Modified Radical Mastectomy were selected for the study. Normal Breast tissue was visually examined, and samples were collected from random fat pockets (random sampling) and fibromuscular grey-white streak areas (targeted sampling). RNA was isolated, followed by spectrophotometric analysis, agarose gel electrophoresis and Agilent Tape station analysis. Histopathological assessments and a gene expression study for housekeeping genes were performed on both subsets. Tissues collected through targeted sampling exhibited significantly higher RNA quality than those obtained via random sampling. Histopathological analysis revealed cellular areas abundant in terminal ductular units within the targeted samples, and a final validation qPCR showed that the targeted samples were the most representative of normal breast glandular tissue. The comparative analysis of the two sampling methods clearly indicates that the targeted approach, with its superior accuracy and reliability, is the more practical choice for obtaining representative normal breast glandular tissue for "-omics" experiments.

This protocol introduces a streamlined and efficient method for isolating human fibroblast from skin primary cell culture with a specific focus on its application to keloid, hypertrophic scar, and normal skin biopsies. Additionally, the absence of suitable animal models for keloid and hypertrophic scar has led preclinical research to rely on in vitro studies using primary cell cultures. This approach addresses the challenges of existing protocols in terms of time, cost, equipment, and technical expertise required. The method involves derivation, culture, and characterization analysis including cell proliferation, migration, and fibroblastic marker (Vimentin, CD90, CD73, and CD105) expression. Our study yielded high amounts of fibroblast from tested skin explants while maintaining their in vivo-like characteristics and behaviour. Immunostaining assay confirmed that the cultivated fibroblast was positively expressed Vimentin. Flowcytometry results showed high expression of CD90 and CD73 while relatively showing lower expression of CD105. Fibroblast derived from keloid tissue showed the highest rate of proliferation and migration ability compared to the other samples. These findings suggest an efficient and reproducible technique to cultivate high qualified fibroblast from human skin in normal or pathological condition, particularly for keloid and hypertrophic scar. The application of this protocol provides a foundation for further studies to investigate the progression and potential intervention of aberrant fibrotic dermatological disorder, in vitro.

We present a rapid high-throughput DNA extraction method for use with EDTA-anticoagulated blood using silicon dioxide (SiO₂) powder in a guanidine-HCl solution, hereinafter referred to as "Glassmilk." The method utilizes a 96-well deep-well plate, enabling DNA extraction from 96 samples in under 3 h. The method integrates cell lysis, washing, elution, and DNA storage within the same well, eliminating the need for DNA transfer. The Glassmilk extraction method is cost-effective and fast, and it avoids expensive or toxic reagents by using only basic lab equipment. The method yielded approximately 40 μg of high-quality DNA from 200 μl of blood. The DNA yield of the Glassmilk method was about 50% higher, and the purity of the DNA was comparable to those obtained using two commercial column-based extraction kits that were used for comparison. The cost per sample was around $1, with the most expensive item being the filter pipette tips, which account for about $0.80 per sample. As we show, the extracted DNA is suitable for downstream applications such as polymerase chain reaction (PCR), PCR-restriction fragment length polymorphism analysis, and qPCR. The method can be adapted for various sample types, including biopsies, fecal samples, cultured cells, and bacteria (see "subprotocols" section), and can also be applied in individual Eppendorf tubes. Our protocol may be useful for basic molecular research in laboratories having limited funds.

Protein maldigestion and malabsorption lead to malnutrition and are a feature of exocrine pancreatic insufficiency (EPI). Although it is the current standard, measurement of nitrogen in stool to assess protease activity is indirect. Up to 80% of hydrolysed proteins appear in blood in the form of peptides, so we developed a method to measure peptide-derived amino acids in plasma as a relevant measure of proteolysis, verified its accuracy, precision, and linearity, and validated it in a porcine model. We modified a ninhydrin method. Large proteins were eliminated from plasma with 10 kDa-cut-off centrifugal filters. Free and total amino acids were measured in permeate before and after its hydrolysis. Peptide-derived amino acids were quantified by subtracting free amino acids from total amino acids. We verified the method in vitro and by comparing results in healthy and EPI pigs. The accuracy of the analysis was close to 100%, with excellent precision (mean relative standard deviation for low, medium, and high amino acid levels = 0.88%) and with stringent linearity (r²  = 0.986, %RE = 5.23). The high-throughput ninhydrin method detected levels of peptide-derived amino acids in vivo with maximal changes seen approximately 2 hours postprandially in young pigs. The AUC and Cmax were significantly higher in healthy compared to EPI pigs (P = .0026 and P = .0037, respectively). The high-throughput ninhydrin method is a sensitive, reliable, and practical method for the estimation of dietary peptide-derived amino acids. This assay endpoint could serve as a direct biomarker of protein digestion and absorption.

Adaptive, rather than innate, immunity relies mainly on antigen-antibody recognition. This recognition is driven by the binding of specific antibody paratopes to distinct epitopes found on antigens. This interaction is pivotal for immune responses that have been re-purposed for diagnostic and therapeutic purposes. This article focuses on Western blotting, an in vitro technique performed for protein immunodetection. Traditionally, this technique requires separate incubations of both primary and secondary antibodies, for which these antibodies recognize different antigen epitopes (conventional method). We propose a modified protocol combining both antibodies, involving a single incubation step that reduces time and conserves reagents (non-conventional/improved method). This improved protocol will enhance efficiency without compromising detection accuracy. It will support multiplexing, enabling the simultaneous detection of multiple proteins. Despite the positive results found by applying available antibodies, further optimization is required for a more thorough evaluation, to ensure that all antibodies consistently yield successful results in every detection attempt for broader use. Our findings indicate that the tested antibody cocktails remained stable over time, which suggests potential for commercialization of this modified Western blot protocol with a wide scope towards multiplex diagnostic application.

Fluorescence microscopy images of biological samples contain valuable information but require rigorous analysis for accurate and reliable determination of changes in protein localization, fluorescence intensity, and morphology of the studied objects. Traditionally, cells for microscopy are immobilized using chemicals, which can introduce stress. Analysis often focuses only on colocalization and involves manual segmentation and measurement, which are time-consuming and can introduce bias. Our new workflow addresses these issues by gently immobilizing cells using a small agarose block on a microscope coverslip. This approach is suitable for cell-walled cells (yeast, fungi, plants, bacteria), facilitates their live imaging under conditions close to their natural environment and enables the addition of chemicals during time-lapse experiments. The primary focus of the protocol is on the presented analysis workflow, which is applicable to virtually any cell type-we describe cell segmentation using the Cellpose software followed by automated analysis of a multitude of parameters using custom-written Fiji (ImageJ) macros. The results can be easily processed using the provided R markdown scripts or available graphing software. Our method facilitates unbiased batch analysis of large datasets, improving the efficiency and accuracy of fluorescence microscopy research. The reported sample preparation protocol and Fiji macros were used in our recent publications: Microbiol Spectr (2022), DOI: 10.1128/spectrum.01961-22; Microbiol Spectr (2022), DOI: 10.1128/spectrum.02489-22; J Cell Sci (2023), DOI: 10.1242/jcs.260554.

Traumatic brain injury (TBI) can be caused by a sudden blow or jolt to the head, causing irreversible brain damage leading to cellular and functional loss. Mammals cannot repair such damage, which may increase the risk of progressive neurodegeneration. Unlike mammals, lower vertebrates such as zebrafish have the astounding capability to regenerate their brains. A model system would be of great value to study zebrafish brain regeneration. Here, we describe a physical method to induce traumatic injury in the zebrafish brain and outline a pipeline to utilize this model system to explore various aspects of brain regeneration. This will significantly advance the fields of regenerative biology and neuroscience. The method includes inducing TBI and validating this through histological assays, immunohistochemistry, and gene expression analysis. By using this model system, researchers will be able to gain valuable insights into the cellular and molecular mechanisms underlying brain regeneration. Understanding these mechanisms could lead to the identification of potential strategies to address neurodegenerative conditions in higher vertebrates.

Severe acute respiratory syndrome coronavirus infection presents complications known as long COVID, a multisystemic organ disease which allows multidimensional analysis. This study aims to uncover clusters of long COVID cases and establish their correlation with the clinical classification developed at the Clinical Research Unit of Brugmann University Hospital, Brussels. Such an endeavour is instrumental in customizing patient management strategies tailored to the unique needs of each distinct group. A two-stage multidimensional exploratory analysis was performed on a retrospective cohort of 205 long COVID patients, involving a factorial analysis of mixed data, and then hierarchical clustering post component analysis. The study's sample comprised 76% women, with an average age of 44.5 years. Three clinical forms were identified: long, persistent, and post-viral syndrome. Multidimensional analysis using demographic, clinical, and biological variables identified three clusters of patients. Biological data did not provide sufficient differentiation between clusters. This emphasizes the importance of identifying or classifying long COVID patients according to their predominant clinical syndrome. Long COVID phenotypes, as well as clinical forms, appear to be associated with distinct pathophysiological mechanisms or genetic predispositions. This underscores the need for further research.