Biology Methods and Protocols最新文献

{"title":"PUPMCR: an R package for image-based identification of color based on Rayner's (1970) terminology and known fungal pigments.","authors":"Niña Rose Zapanta, Rhenz Hannah Santos, Jericho Ivan Pineda, Jireh Sealtiel Pedrosa, Kristine Joyce Rabelas, Charina Samontan, Lourdes Alvarez, Chester Deocaris","doi":"10.1093/biomethods/bpaf004","DOIUrl":"10.1093/biomethods/bpaf004","url":null,"abstract":"<p><p>Fungi are eukaryotic organisms grouped based on different traits of their morphology. In 1970, R. W. Rayner published <i>A Mycological Colour Chart</i> to provide a standardized system for identifying color in fungi. While its terminologies have contributed a standard way of color matching for taxonomic diagnoses, this method using the personal color perception of the observer does not guarantee accuracy. Considering the diversity of fungi, visual color matching is expected to be challenging without a standard assisting instrument. In this study, the R package PUPMCR is developed to approximate the color name and associated pigments of fungal species based on the pixel coordinates of its uploaded image. This software utilizes CIELAB and RGB color spaces as well as Euclidean and Chi-square distance metric systems. The package is tested and validated using 300 fungal images as a dataset for conducting interrater reliability tests. Results showed the highest agreement for parameters utilizing the RGB color space (Cohen's kappa values: 0.655 ± 0.013 for RGB and Euclidean; 0.658 ± 0.004 for RGB and Chi-square), attributed to its computational efficiency, which facilitates more uniform binning and universally scaled distance metrics. The produced color-identifying tool is also available as a Shiny web application (https://pupmcr.shinyapps.io/PUPMCR/) to allow better accessibility for users on the World Wide Web. The development of PUPMCR not only benefits a variety of users from its free accessibility but also provides a more reliable color identification system in the field of mycology.</p>","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"10 1","pages":"bpaf004"},"PeriodicalIF":2.5,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11825390/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143433676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A cost-effective and scalable approach for DNA extraction from FFPE tissues.","authors":"Christoph Geisenberger, Edgar Chimal, Philipp Jurmeister, Frederick Klauschen","doi":"10.1093/biomethods/bpaf003","DOIUrl":"10.1093/biomethods/bpaf003","url":null,"abstract":"<p><p>Genomic profiling of cancer plays an increasingly vital role for diagnosis and therapy planning. In addition, research of novel diagnostic applications such as DNA methylation profiling requires large training and validation cohorts. Currently, most diagnostic cases processed in pathology departments are stored as formalin-fixed and paraffin embedded tissue blocks (FFPE). Consequently, there is a growing demand for high-throughput extraction of nucleic acids from FFPE tissue samples. While proprietary kits are available, they are expensive and offer little flexibility. Here, we present ht-HiTE, a high-throughput implementation of a recently published and highly efficient DNA extraction protocol. This approach enables manual and automated processing of 96-well plates with a liquid handler, offers two options for purification and utilizes off-the-shelf reagents. Finally, we show that NGS and DNA methylation microarray data obtained from DNA processed with ht-HiTE are of equivalent quality as compared to a manual, kit-based approach.</p>","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"10 1","pages":"bpaf003"},"PeriodicalIF":2.5,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11849955/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143493904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantification of variegated <i>Drosophila</i> ommatidia with high-resolution image analysis and machine learning.","authors":"Hunter J Hill, William Sullivan, Brandon S Cooper","doi":"10.1093/biomethods/bpaf002","DOIUrl":"10.1093/biomethods/bpaf002","url":null,"abstract":"<p><p>A longstanding challenge in biology is accurately analyzing images acquired using microscopy. Recently, machine learning (ML) approaches have facilitated detailed quantification of images that were refractile to traditional computation methods. Here, we detail a method for measuring pigments in the complex-mosaic adult <i>Drosophila</i> eye using high-resolution photographs and the pixel classifier <i>ilastik</i> [1]. We compare our results to analyses focused on pigment biochemistry and subjective interpretation, demonstrating general overlap, while highlighting the inverse relationship between accuracy and high-throughput capability of each approach. Notably, no coding experience is necessary for image analysis and pigment quantification. When considering time, resolution, and accuracy, our view is that ML-based image analysis is the preferred method.</p>","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"10 1","pages":"bpaf002"},"PeriodicalIF":2.5,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11739462/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143013382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel method for detection of Aβ and Iso-D7-Aβ N-terminus-specific B cells and Iso-D7-Aβ-specific antibodies.","authors":"Elizaveta A Kolobova, Irina Yu Petrushanko, Vladimir A Mitkevich, Alexander A Makarov, Irina L Grigorova","doi":"10.1093/biomethods/bpaf001","DOIUrl":"https://doi.org/10.1093/biomethods/bpaf001","url":null,"abstract":"<p><p>Alzheimer's disease (AD) is a multifactorial systemic disease that is triggered, at least in part, by the accumulation of β-amyloid (Aβ) peptides in the brain, but it also depends on immune system-mediated regulation. Recent studies suggest that B cells may play a role in AD development and point to the accumulation of clonally expanded B cells in AD patients. However, the specificity of the clonally expanded B cells is unknown, and the contribution of Aβ-specific B cells to AD pathology development is unclear. In this study, we have developed a novel method to identify Aβ-specific B cells by flow cytometry using fluorescent tetramers. The suggested method also enables the identification of B-cell clones specific to a more pathology-provoking form of Aβ with an isomerized Asp7 residue (Iso-D7-Aβ) that accumulates in elderly people and in AD patients. The method has been verified using mice immunized with antigens containing the isomerized or non-isomerized Aβ N-terminus peptides. In addition, we describe a new method for the detection of Iso-D7-Aβ-specific antibodies, which was tested on mouse serum. These methods are of potential importance in research aimed at studying AD and may be also utilized for diagnostic and therapeutic purposes.</p>","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"10 1","pages":"bpaf001"},"PeriodicalIF":2.5,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11739456/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143013368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust RNA secondary structure prediction with a mixture of deep learning and physics-based experts.","authors":"Xiangyun Qiu","doi":"10.1093/biomethods/bpae097","DOIUrl":"10.1093/biomethods/bpae097","url":null,"abstract":"<p><p>A mixture-of-experts (MoE) approach has been developed to mitigate the poor out-of-distribution (OOD) generalization of deep learning (DL) models for single-sequence-based prediction of RNA secondary structure. The main idea behind this approach is to use DL models for in-distribution (ID) test sequences to leverage their superior ID performances, while relying on physics-based models for OOD sequences to ensure robust predictions. One key ingredient of the pipeline, named MoEFold2D, is automated ID/OOD detection via consensus analysis of an ensemble of DL model predictions without requiring access to training data during inference. Specifically, motivated by the clustered distribution of known RNA structures, a collection of distinct DL models is trained by iteratively leaving one cluster out. Each DL model hence serves as an expert on all but one cluster in the training data. Consequently, for an ID sequence, all but one DL model makes accurate predictions consistent with one another, while an OOD sequence yields highly inconsistent predictions among all DL models. Through consensus analysis of DL predictions, test sequences are categorized as ID or OOD. ID sequences are subsequently predicted by averaging the DL models in consensus, and OOD sequences are predicted using physics-based models. Instead of remediating generalization gaps with alternative approaches such as transfer learning and sequence alignment, MoEFold2D circumvents unpredictable ID-OOD gaps and combines the strengths of DL and physics-based models to achieve accurate ID and robust OOD predictions.</p>","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"10 1","pages":"bpae097"},"PeriodicalIF":2.5,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11729747/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142985008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real time-PCR a diagnostic tool for reporting copy number variation and relative gene-expression changes in pediatric B-cell acute lymphoblastic leukemia-a pilot study.","authors":"Zoha Sadaqat, Smitha Joseph, Chandrika Verma, Jyothi Muni Reddy, Anand Prakash, Tinku Thomas, Vandana Bharadwaj, Neha Vyas","doi":"10.1093/biomethods/bpae098","DOIUrl":"10.1093/biomethods/bpae098","url":null,"abstract":"<p><p>Real time-polymerase chain reaction (RT-PCR) is used routinely in clinical practice as a cost-effective method for molecular diagnostics. Research in pediatric B-cell Acute Lymphoblastic Leukemia (ped B-ALL) suggests that apart from cytogenetics and clinical features, there is a need to include Copy number variation (CNV) in select genes at diagnosis, for upfront stratification of patients. Using ped B-ALL as a model, we have developed a RT-PCR-based iterative probability scoring method for reporting CNVs, and relative gene-expression changes. Our work highlights that once genes of interest and hotspots of CNVs are identified in discovery phase, our proposed method can be used as a cost-effective and user-friendly diagnostic tool for the identification of changes at genomic or transcriptomic level. It has the potential to be incorporated in routine diagnostics in resource constrained settings and be tailored for different diseases as per need.</p>","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"10 1","pages":"bpae098"},"PeriodicalIF":2.5,"publicationDate":"2024-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11717350/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142972477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Functional and comparative analysis of the Fe^II/2-oxoglutarate-dependent dioxygenases without using any substrate.","authors":"Susmita Das, Nafeesa Shahnaz, Carmel Keerthana, Saumya Ranjan, Gayathri Seenivasan, Nikhil Tuti, Unnikrishnan P Shaji, Gargi Meur, Roy Anindya","doi":"10.1093/biomethods/bpae096","DOIUrl":"10.1093/biomethods/bpae096","url":null,"abstract":"<p><p>Non-haem iron (Fe^II) and 2-oxoglutarate(2OG)-dependent dioxygenases catalyse various biological reactions. These enzymes couple the oxidative decarboxylation of 2OG to the hydroxylation of the substrates. While some of these enzymes are reported to have multiple substrates, the substrate remains unknown for many of the enzymes. However, in the absence of the substrate, these enzymes catalyse oxidative decarboxylation of 2OG and generate succinate. We have determined succinate level to monitor this uncoupled reaction and compared the uncoupled 2OG turnover of different Fe^II/2OG-dependent dioxygenases. The uncoupled succinate production was used to verify the Ni^II-mediated inhibition and functionality of human dioxygenase ALKBH6.</p>","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"10 1","pages":"bpae096"},"PeriodicalIF":2.5,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11751636/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143024980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of a surrogate virus neutralization assay for detecting neutralizing antibodies against SARS-CoV-2 in an African population.","authors":"Lilian Nkinda, Victoria Shayo, Salim Masoud, Godfrey Barabona, Isaac Ngare, Ponsian P Kunambi, Emmanuel Nkuwi, Doreen Kamori, Frank Msafiri, Elisha Osati, Frank Eric Hassan, Juma Kisuse, Benson Kidenya, Sayoki Mfinanga, Mbazi Senkoro, Takamasa Ueno, Eligius Lyamuya, Emmanuel Balandya","doi":"10.1093/biomethods/bpae095","DOIUrl":"10.1093/biomethods/bpae095","url":null,"abstract":"<p><p>The global resurgence of coronaviruses and the move to incorporate COVID-19 vaccines into the expanded program for immunization have warranted for a high-throughput and low-cost assay to measure and quantify mounted neutralizing antibodies as an indicator for protection against SARS-CoV-2. Hence, we evaluated the surrogate-virus-neutralization-assay (sVNT) as an alternative assay to the pseudo-virus neutralization assay (pVNT). The sVNT was used to measure neutralizing antibodies among 119 infected and/or vaccinated blood samples, against wild-type SARS-CoV-2 (WT) and the Omicron-variant with reference to the pVNT. Four different cut-offs were assessed for suitability in distinguishing neutralizers: the manufacturer (>30%), literature-based (>50%) and (>80%), and population-based (>27.69%). The obtained data was analyzed using \"R\" through its integrated development environments; JAMOV and R-Studio. Using the WT strain, only the population-based cut-off was able to differentiate neutralizers from non-neutralizers beyond chance, with an area under the curve (AUC) of 0.833 (95%CI, 0.505-1.0; <i>P</i> = .049). Applying the population-based cut-off, improved the sensitivity to 100% from 91.4% obtained from the manufacturer cut-off (<i>P</i> = .002). However, the specificity remained low (67%). The negative-predictive-value also improved to 100% vs 16.4% (<i>P</i> = .006), but there was no difference in the positive-predictive-value (99.1% vs 99.1%) (<i>P</i> = .340). When we used the Omicron-variant, the sVNT titers were not able to predict the neutralizers and non-neutralizers with reference to pVNT (AUC of 0.649) (<i>P</i> = .221). The sVNT assay is a potential alternative for screening individuals harboring potent neutralizing antibody with high sensitivity, although we recommend continuous improvement of the assay in line with the viral mutations. Further, we recommend that individual users establish a population-based cut-off while using the sVNT assay.</p>","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"10 1","pages":"bpae095"},"PeriodicalIF":2.5,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11769676/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143048164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ImmuNet: a segmentation-free machine learning pipeline for immune landscape phenotyping in tumors by multiplex imaging.","authors":"Shabaz Sultan, Mark A J Gorris, Evgenia Martynova, Lieke L van der Woude, Franka Buytenhuijs, Sandra van Wilpe, Kiek Verrijp, Carl G Figdor, I Jolanda M de Vries, Johannes Textor","doi":"10.1093/biomethods/bpae094","DOIUrl":"10.1093/biomethods/bpae094","url":null,"abstract":"<p><p>Tissue specimens taken from primary tumors or metastases contain important information for diagnosis and treatment of cancer patients. Multiplex imaging allows <i>in situ</i> visualization of heterogeneous cell populations, such as immune cells, in tissue samples. Most image processing pipelines first segment cell boundaries and then measure marker expression to assign cell phenotypes. In dense tissue environments, this segmentation-first approach can be inaccurate due to segmentation errors or overlapping cells. Here, we introduce the machine-learning pipeline \"ImmuNet\", which identifies positions and phenotypes of cells without segmenting them. ImmuNet is easy to train: human annotators only need to click on an immune cell and score its expression of each marker-drawing a full cell outline is not required. We trained and evaluated ImmuNet on multiplex images from human tonsil, lung cancer, prostate cancer, melanoma, and bladder cancer tissue samples and found it to consistently achieve error rates below 5%-10% across tissue types, cell types, and tissue densities, outperforming a segmentation-based baseline method. Furthermore, we externally validate ImmuNet results by comparing them to flow cytometric cell count measurements from the same tissue. In summary, ImmuNet is an effective, simpler alternative to segmentation-based approaches when only cell positions and phenotypes, but not their shapes, are required for downstream analyses. Thus, ImmuNet helps researchers to analyze cell positions in multiplex tissue images more easily and accurately.</p>","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"10 1","pages":"bpae094"},"PeriodicalIF":2.5,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11769680/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143048178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Directed evolution of peroxidase DNAzymes by a function-based approach.","authors":"Soubhagya K Bhuyan, Weisi He, Jingyu Cui, Julian A Tanner","doi":"10.1093/biomethods/bpae088","DOIUrl":"10.1093/biomethods/bpae088","url":null,"abstract":"<p><p>Peroxidase DNAzymes are single-stranded, stable G-quadruplexes structures that exhibit catalytic activity with cofactor hemin. This class of DNAzymes offers several advantages over traditional protein and RNA catalysts, including thermal stability, resistance to hydrolysis, and easy of synthesis in the laboratory. However, their use in medicine, biology, and chemistry is limited due to their low catalytic rates. Selecting and evolving for higher catalytic rates has been challenging due to limitations in selection methodology which generally use affinity as the selection pressure instead of kinetics. We previously evolved a new peroxidase DNAzyme (mSBDZ-X-3) through a directed evolution method, which was subsequently used for proximity labelling in a proteomic experiment in cell culture. Herein, we present a detailed protocol for this function-based laboratory evolution method to evolve peroxidase DNAzymes for future laboratory implementation. This approach is based on capturing self-biotinylated DNA, which is catalyzed by intrinsic peroxidase activity to select for DNAzyme molecules. The selection method uses fluorescence-based real-time monitoring of the DNA pools, allowing for the enrichment of catalytic activity and capture of catalytic DNA across evolutionary selection rounds. The evolved mSBDZ-X-3 DNAzyme attributes parallel G-quadruplex structure and demonstrates better catalytic properties than DNAzyme variants evolved previously. The influence of critical reaction parameters is outlined. This protocol enables discovery of improved peroxidase DNAzyme/RNAzyme variants from natural or chemical-modified nucleotide libraries. The approach could be applicable for the selection of catalytic activities in a variety of directed molecular evolution contexts.</p>","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"10 1","pages":"bpae088"},"PeriodicalIF":2.5,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11780874/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143068431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}