Biology Methods and Protocols最新文献

Natural killer (NK) cells have emerged as promising candidates for novel immunotherapy strategies against various malignancies. Their unique ability to recognize and eliminate tumour cells without prior sensitization, coupled with the secretion of pro-inflammatory cytokines such as interferon-gamma and tumour necrosis factor, position them as promising agents in cancer therapy. Adoptive NK cell transfer has shown particular promise in haematological malignancies, where NK cell infusions could achieve remission in a high proportion of patients. Moreover, the possibility to engineer NK cells to express chimeric antigen receptors can further enhance their efficacy, thereby broadening their applicability to include solid tumours. Ongoing research is crucial to optimize NK cell therapies and enhance their efficacy to expand their clinical applications. However, this research hinges on robust protocols and experimental methodology for the isolation, expansion, and genetic engineering of NK cells. In an attempt to set up a standardized protocol for NK cell isolation and expansion, we present a thoroughly tested and validated protocol that can produce highly pure, viable, and potent NK cells that can be used for research and development of NK cell therapies. The protocol is highly reproducible, closely aligned to comply with Good Manufacturing Practice regulations, and tested for scalability to produce NK cells at clinically relevant dosages to support the development of off-the-shelf NK products.

Subjective variability in human interpretation of diagnostic imaging presents significant clinical limitations, potentially resulting in diagnostic errors and increased healthcare costs. While artificial intelligence (AI) algorithms offer promising solutions to reduce interpreter subjectivity, they frequently demonstrate poor generalizability across different healthcare settings. To address these issues, we introduce Retrieval Augmented Medical Diagnosis System (RAMDS), which integrates an AI classification model with a similar image model. This approach retrieves historical cases and their diagnoses to provide context for the AI predictions. By weighing similar image diagnoses alongside AI predictions, RAMDS produces a final weighted prediction, aiding physicians in understanding the diagnosis process. Moreover, RAMDS does not require complete retraining when applied to new datasets; rather, it simply necessitates re-calibration of the weighing system. When RAMDS fine-tuned for negative predictive value was evaluated on breast ultrasounds for cancer classification, RAMDS improved sensitivity by 21% and negative predictive value by 9% compared to ResNet-34. Offering enhanced metrics, explainability, and adaptability, RAMDS represents a notable advancement in medical AI. RAMDS is a new approach in medical AI that has the potential for pan-pathological uses, though further research is needed to optimize its performance and integrate multimodal data.

Polysaccharide quantification plays a vital role in understanding ecological and nutritional processes in microbes, plants, and animals. Traditional methods typically hydrolyze these large molecules into monomers using chemical methods, but such approaches do not work for all polysaccharides. Enzymatic degradation is a promising alternative but typically requires the use of characterized recombinant enzymes or characterized microbial isolates that secrete enzymes. In this study, we introduce a versatile method that employs undefined enzyme cocktails secreted by individual microbes or complex environmental microbial communities for the hydrolysis of polysaccharides. We focus on colloidal chitin and laminarin as representative polysaccharides of ecological relevance. Our results demonstrate that colloidal chitin can be effectively digested with an enzyme cocktail derived from a chitin-degrading Psychromonas sp. isolate. Utilizing a 3,5-dinitrosalicylic acid reducing sugar assay or liquid chromatography-mass spectrometry for monomer and oligomer detection, we successfully determined chitin concentrations as low as 62 and 15 mg/l, respectively. This allows for effective monitoring of microbial chitin degradation. To extend the applicability of our method, we also leveraged complex, undefined microbial communities as sources of enzyme cocktails capable of degrading laminarin. With this approach, we achieved a detection limit of 30 mg/l laminarin through the reducing sugar assay. Our findings highlight the potential of utilizing enzyme cocktails from both individual microbes and, notably, from undefined microbial communities for polysaccharide quantification. This advancement addresses limitations associated with traditional chemical hydrolysis methods.

Glyoxalase I (Glo I) is an enzyme essential for detoxifying methylglyoxal, a toxic compound associated with advanced glycation end products. Given Glo I's multifaceted roles in various physiological and pathological processes, accurately measuring its activity is crucial for understanding its implications in metabolic disorders. The current assay utilizes 2,4-dinitrophenylhydrazine (2,4-DNPH) to measure Glo I activity. This reagent has previously been employed to evaluate a group of enzyme protocols. The procedure involves incubating Glo I enzyme samples in a controlled phosphate buffer at pH 6.6, optimizing conditions for enzymatic activity. Glutathione and methylglyoxal serve as substrates, with Glo I catalyzing the conversion of the hemithioacetal adduct into S-D-lactoylglutathione. Unreacted methylglyoxal is quantified by forming a colored hydrazone complex with 2,4-DNPH. The 2,4-DNPH method is rigorously validated for linearity, stability, resistance to interference, and sensitivity from several chemicals. It strongly correlates with the existing ultraviolet method, offering enhanced simplicity and cost-effectiveness. The protocol allows precise quantification of Glo I activity, with potential in research and diagnostics. Intra- and inter-day analyses confirm accuracy as percentage relative error, ensuring reliable measurement activity. The DNPH-Glo I method exhibited excellent sensitivity, with low limits of detection and quantification at 0.006 U/L and 0.018 U/L, respectively. This research provides valuable insights into the quantification of Glo I, highlighting significant implications for future studies in metabolic disorders and related health fields. This study contributes to a deeper understanding of its role in health and disease management by advancing the methods available for measuring Glo I activity.

Hymenolepis diminuta is a parasitic tapeworm that utilizes rats as hosts and offers advantages over human parasitic tapeworms and free-living flatworms as a model system to study the biology and pathology of helminth infections. H. diminuta is minimally infectious to humans, easy to maintain in the lab, demonstrates impressive growth, regeneration, and reproductive capabilities, and is amenable to loss-of-function manipulations. As an emerging model, tool development is critical to increasing the utility of this system. This study introduces a novel protocol for H. diminuta that combines fluorescent in situ hybridization (FISH) and 2'-Deoxy-2'-fluoro-5-ethynyluridine (F-ara-EdU) uptake and staining. Our protocol allows for the spatial detection of gene expression and simultaneous identification of proliferating cells. Dual labeling of F-ara-EdU and stem cell markers revealed a distinct expression pattern in different anatomical regions, especially in the head and neck. We demonstrate optimal labeling without permeabilization, streamlining the protocol. We also demonstrate generalizability using FISH for other tissue markers. The protocol was applied to perform bulk lineage tracing, revealing that stem cells can differentiate into neuronal and tegumental cells within 3 days. Our protocol provides an important tool in the arsenal for investigating gene expression and cell proliferation in H. diminuta, contributing valuable insights into the biology of parasitic tapeworms and potentially opening new avenues for the study of human parasitic tapeworms.

Patient-derived tumor organoids (PDOs) hold immense potential for personalized drug sensitivity testing, but accurate efficacy determination is crucial for clinical translation. This study investigated factors influencing the accuracy and reproducibility of drug sensitivity measurements in PDOs, focusing on half-maximal-inhibitory-concentration (IC50) calculation methods, drug concentration numbers, and plate types. PDOs were established from six primary cancer tissues, including two cervical resections, one lung biopsy, one lung pleural effusion, one breast biopsy, and one gastric resection. They were subjected to drug sensitivity assays with 21 single/combined treatments, encompassing chemotherapy and targeted therapy drugs, with concentrations standardized in fold. Utilizing 6- and 12-concentration setups, IC50 derived from GraphPad-Dose-response-Inhibition (DRI), LC-logit, and LC-probit methods were compared. Relative changes (RCs) in IC50 and area-under-the dose-response-curve (AUC) between setups and the impact of plate type on cell viability measurements were assessed. In the 12-concentration setup, no significant IC50 differences were observed among the calculation methods. Notably, GraphPad-DRI and LC-logit exhibited minimal RCs between the 6- and 12-concentration setups (0.035 and -0.033, respectively), indicating accurate IC50 quantification even with fewer drug concentrations. AUC correlated strongly with GraphPad-DRI-derived IC50 (R = 0.858) and demonstrated lower variance between technical replicates. Furthermore, opaque-bottom plates yielded higher precision in cell viability measurements compared to transparent-bottom plates. This study provides valuable insights into optimizing drug sensitivity testing in PDOs. By demonstrating the robustness of specific IC50 calculation methods and the feasibility of using fewer drug concentrations, this study contributed to the standardization and reliability of PDO-based drug sensitivity assays.

The discovery of antibodies through phage display is significantly influenced by antigen presentation during panning, particularly for membrane-anchored proteins, which pose challenges due to their complex structures. Traditional approaches, such as whole cells expressing the target protein, often result in low antigen density and high background signals. In this study, we describe an alternative method using stably transfected cell lines that express the target antigen on their surface, regulated by an intracellular enhanced green fluorescent protein (EGFP) signal. This system enables high-throughput flow cytometry-based screening of phage display libraries to isolate human antibodies that recognize the native conformation of membrane proteins. Using human epithelial cell adhesion molecule (EpCAM) and human neuroplastin 65 (NP65) as model antigens, we established an optimized screening workflow with polyclonal phage pools. Selected EpCAM-specific single-chain variable fragments (scFvs) from a naïve library were recombinantly expressed with an IgG4 scaffold and characterized for specific binding. This approach provides an effective platform for the identification of antibodies against membrane proteins in their native state.

Given the risk of zoonotic disease emergence, including new SARS-CoV-2 variants of COVID-19, rapid diagnostic tools are urgently needed to improve the control of the spread of infectious diseases. A one-pot triplex real-time RT-LAMP (reverse-transcription-loop-mediated isothermal amplification) assay, based on two regions of the genome SARS-CoV-2-specifically the Orf1ab and N genes-along with one internal control, the human RNase P gene, was developed. The multiplexing relies on the distinct melting peaks produced during an annealing step. This tool, named RUNCOV, was compared to the gold-standard reverse-transcription real-time quantitative PCR (RT-qPCR) assay. A simple sample preparation step was designed alongside the assay, making it ready for use on site, as a point-of-care diagnostic tool. RUNCOV is rapid (typically less than 40 minutes), highly sensitive and specific. When tested on clinical samples with known SARS-CoV-2 status, its limit of detection (LOD) ranges between 5 and 20 copies per reaction and its diagnostic sensitivity (97.44%) and specificity (100%) values are high compared to the RT-qPCR gold standard. These results were supported with an extensive in silico analysis of over 14 million genomes, demonstrating this tool was capable of detecting all known SARS-CoV-2 variants, including the most recent ones KP.3.1.1 and BA2.86.1. This molecular assay is portable, as demonstrated when it was used successfully in La Réunion in different contexts outside the laboratory.

[This corrects the article DOI: 10.1093/biomethods/bpae098.].

Protein homeostasis (proteostasis) is the balance of protein synthesis, protein maintenance, and degradation. Loss of proteostasis contributes to the aging process and characterizes neurodegenerative diseases. It is well established that the processes of protein maintenance and degradation are declining with aging; however, the contribution of a declining quality of protein synthesis to the loss of proteostasis is less well understood. In fact, protein synthesis at the ribosome is an error-prone process and challenges the cell with misfolded proteins. Here, we present the development of a highly sensitive and reproducible reporter assay for the detection of translational errors and the measurement of translational fidelity. Using Nano-luciferase, an enzyme 3 times smaller and 50 times more sensitive than the hitherto used Firefly-luciferase, we introduced stop-codon and amino-acid exchanges that inactivate the enzyme. Erroneous re-activation of luciferase activity indicates ribosomal inaccuracy and translational infidelity. This highly sensitive and reproducible method has broad applications for studying the molecular mechanisms underlying diseases associated with defective protein synthesis and can be used for drug screening to modulate translational fidelity.