Improved sampling and DNA extraction procedures for microbiome analysis in food-processing environmentsBarcenilla, Coral; Cobo-Díaz, José F.; De Filippis, Francesca; Valentino, Vincenzo; Cabrera Rubio, Raul; O’Neil, Dominic; Mahler de Sanchez, Lisa; Armanini, Federica; Carlino, Niccolò; Blanco-Míguez, Aitor; Pinto, Federica; Calvete-Torre, Inés; Sabater, Carlos; Delgado, Susana; Ruas-Madiedo, Patricia; Quijada, Narciso M.; Dzieciol, Monika; Skírnisdóttir, Sigurlaug; Knobloch, Stephen; Puente, Alba; López, Mercedes; Prieto, Miguel; Marteinsson, Viggó Thór; Wagner, Martin; Margolles, Abelardo; Segata, Nicola; Cotter, Paul D.; Ercolini, Danilo; Alvarez-Ordóñez, Avelino
doi: 10.1038/s41596-023-00949-xpmid: 38267717
Deep investigation of the microbiome of food-production and food-processing environments through whole-metagenome sequencing (WMS) can provide detailed information on the taxonomic composition and functional potential of the microbial communities that inhabit them, with huge potential benefits for environmental monitoring programs. However, certain technical challenges jeopardize the application of WMS technologies with this aim, with the most relevant one being the recovery of a sufficient amount of DNA from the frequently low-biomass samples collected from the equipment, tools and surfaces of food-processing plants. Here, we present the first complete workflow, with optimized DNA-purification methodology, to obtain high-quality WMS sequencing results from samples taken from food-production and food-processing environments and reconstruct metagenome assembled genomes (MAGs). The protocol can yield DNA loads >10 ng in >98% of samples and >500 ng in 57.1% of samples and allows the collection of, on average, 12.2 MAGs per sample (with up to 62 MAGs in a single sample) in ~1 week, including both laboratory and computational work. This markedly improves on results previously obtained in studies performing WMS of processing environments and using other protocols not specifically developed to sequence these types of sample, in which <2 MAGs per sample were obtained. The full protocol has been developed and applied in the framework of the European Union project MASTER (Microbiome applications for sustainable food systems through technologies and enterprise) in 114 food-processing facilities from different production sectors.
Using high-resolution microscopy data to generate realistic structures for electromagnetic FDTD simulations from complex biological modelsBall, John M.; Li, Wei
doi: 10.1038/s41596-023-00947-zpmid: 38332306
Finite-difference time-domain (FDTD) electromagnetic simulations are a computational method that has seen much success in the study of biological optics; however, such simulations are often hindered by the difficulty of faithfully replicating complex biological microstructures in the simulation space. Recently, we designed simulations to calculate the trajectory of electromagnetic light waves through realistically reconstructed retinal photoreceptors and found that cone photoreceptor mitochondria play a substantial role in shaping incoming light. In addition to vision research and ophthalmology, such simulations are broadly applicable to studies of the interaction of electromagnetic radiation with biological tissue. Here, we present our method for discretizing complex 3D models of cellular structures for use in FDTD simulations using MEEP, the MIT Electromagnetic Equation Propagation software, including subpixel smoothing at mesh boundaries. Such models can originate from experimental imaging or be constructed by hand. We also include sample code for use in MEEP. Implementation of this algorithm in new code requires understanding of 3D mathematics and may require several weeks of effort, whereas use of our sample code requires knowledge of MEEP and C++ and may take up to a few hours to prepare a model of interest for 3D FDTD simulation. In all cases, access to a facility supercomputer with parallel processing capabilities is recommended. This protocol offers a practical solution to a significant challenge in the field of computational electrodynamics and paves the way for future advancements in the study of light interaction with biological structures.
Engineering megabase-sized genomic deletions with MACHETE (Molecular Alteration of Chromosomes with Engineered Tandem Elements)Barriga, Francisco M.; Lowe, Scott W.
doi: 10.1038/s41596-024-00953-9pmid: 38326496
The elimination of large genomic regions has been enabled by the advent of site-specific nucleases. However, as the intended deletions get larger, the efficiency of successful engineering decreases to a point where it is not feasible to retrieve edited cells due to the rarity of on-target events. To address this issue, we developed a system called molecular alteration of chromosomes with engineered tandem elements (MACHETE). MACHETE is a CRISPR–Cas9-based system involving two stages: the initial insertion of a bicistronic positive/negative selection cassette to the locus of interest. This is followed by the introduction of single-guide RNAs flanking the knockin cassette to engineer the intended deletion, where only cells that have lost the locus survive the negative selection. In contrast to other approaches optimizing the activity of sequence-specific nucleases, MACHETE selects for the deletion event itself, thus greatly enriching for cells with the engineered alteration. The procedure routinely takes 4–6 weeks from design to selection of polyclonal populations bearing the deletion of interest. We have successfully deployed MACHETE to engineer deletions of up to 45 Mb, as well as the rapid creation of allelic series to map the relevant activities within a locus. This protocol details the design and step-by-step procedure to engineer megabase-sized deletions in cells of interest, with potential application for cancer genetics, transcriptional regulation, genome architecture and beyond.
BridGE: a pathway-based analysis tool for detecting genetic interactions from GWASHajiaghabozorgi, Mehrad; Fischbach, Mathew; Albrecht, Michael; Wang, Wen; Myers, Chad L.
doi: 10.1038/s41596-024-00954-8pmid: 38514837
Genetic interactions have the potential to modulate phenotypes, including human disease. In principle, genome-wide association studies (GWAS) provide a platform for detecting genetic interactions; however, traditional methods for identifying them, which tend to focus on testing individual variant pairs, lack statistical power. In this protocol, we describe a novel computational approach, called Bridging Gene sets with Epistasis (BridGE), for discovering genetic interactions between biological pathways from GWAS data. We present a Python-based implementation of BridGE along with instructions for its application to a typical human GWAS cohort. The major stages include initial data processing and quality control, construction of a variant-level genetic interaction network, measurement of pathway-level genetic interactions, evaluation of statistical significance using sample permutations and generation of results in a standardized output format. The BridGE software pipeline includes options for running the analysis on multiple cores and multiple nodes for users who have access to computing clusters or a cloud computing environment. In a cluster computing environment with 10 nodes and 100 GB of memory per node, the method can be run in less than 24 h for typical human GWAS cohorts. Using BridGE requires knowledge of running Python programs and basic shell script programming experience.
Web-based multi-omics integration using the Analyst software suiteEwald, Jessica D.; Zhou, Guangyan; Lu, Yao; Kolic, Jelena; Ellis, Cara; Johnson, James D.; Macdonald, Patrick E.; Xia, Jianguo
doi: 10.1038/s41596-023-00950-4pmid: 38355833
The growing number of multi-omics studies demands clear conceptual workflows coupled with easy-to-use software tools to facilitate data analysis and interpretation. This protocol covers three key components involved in multi-omics analysis, including single-omics data analysis, knowledge-driven integration using biological networks and data-driven integration through joint dimensionality reduction. Using the dataset from a recent multi-omics study of human pancreatic islet tissue and plasma samples, the first section introduces how to perform transcriptomics/proteomics data analysis using ExpressAnalyst and lipidomics data analysis using MetaboAnalyst. On the basis of significant features detected in these workflows, the second section demonstrates how to perform knowledge-driven integration using OmicsNet. The last section illustrates how to perform data-driven integration from the normalized omics data and metadata using OmicsAnalyst. The complete protocol can be executed in ~2 h. Compared with other available options for multi-omics integration, the Analyst software suite described in this protocol enables researchers to perform a wide range of omics data analysis tasks via a user-friendly web interface.
Profiling native pulmonary basement membrane stiffness using atomic force microscopyHartmann, Bastian; Fleischhauer, Lutz; Nicolau, Monica; Jensen, Thomas Hartvig Lindkær; Taran, Florin-Andrei; Clausen-Schaumann, Hauke; Reuten, Raphael
doi: 10.1038/s41596-024-00955-7pmid: 38429517
Mammalian cells sense and react to the mechanics of their immediate microenvironment. Therefore, the characterization of the biomechanical properties of tissues with high spatial resolution provides valuable insights into a broad variety of developmental, homeostatic and pathological processes within living organisms. The biomechanical properties of the basement membrane (BM), an extracellular matrix (ECM) substructure measuring only ∼100–400 nm across, are, among other things, pivotal to tumor progression and metastasis formation. Although the precise assignment of the Young’s modulus E of such a thin ECM substructure especially in between two cell layers is still challenging, biomechanical data of the BM can provide information of eminent diagnostic potential. Here we present a detailed protocol to quantify the elastic modulus of the BM in murine and human lung tissue, which is one of the major organs prone to metastasis. This protocol describes a streamlined workflow to determine the Young’s modulus E of the BM between the endothelial and epithelial cell layers shaping the alveolar wall in lung tissues using atomic force microscopy (AFM). Our step-by-step protocol provides instructions for murine and human lung tissue extraction, inflation of these tissues with cryogenic cutting medium, freezing and cryosectioning of the tissue samples, and AFM force-map recording. In addition, it guides the reader through a semi-automatic data analysis procedure to identify the pulmonary BM and extract its Young’s modulus E using an in-house tailored user-friendly AFM data analysis software, the Center for Applied Tissue Engineering and Regenerative Medicine processing toolbox, which enables automatic loading of the recorded force maps, conversion of the force versus piezo-extension curves to force versus indentation curves, calculation of Young’s moduli and generation of Young’s modulus maps, where the pulmonary BM can be identified using a semi-automatic spatial filtering tool. The entire protocol takes 1–2 d.
Rapid reaction optimization by robust and economical quantitative benchtop 19F NMR spectroscopyHeinrich, G.; Kondratiuk, M.; Gooßen, L. J.; Wiesenfeldt, M. P.
doi: 10.1038/s41596-023-00951-3pmid: 38409535
The instrumental analysis of reaction mixtures is usually the rate-determining step in the optimization of chemical processes. Traditionally, reactions are analyzed by gas chromatography, HPLC or quantitative NMR spectroscopy on high-field spectrometers. However, chromatographic methods require elaborate work-up and calibration protocols, and high-field NMR spectrometers are expensive to purchase and operate. This protocol describes an inexpensive and highly effective analysis method based on low-field benchtop NMR spectroscopy. Its key feature is the use of fluorine-labeled model substrates that, because of the wide chemical shift range and high sensitivity of 19F, enable separate, quantitative detection of product and by-product signals even on low-field, permanent magnet spectrometers. An external lock/shim device obviates the need for deuterated solvents, permitting the direct, noninvasive measurement of crude reaction mixtures with minimal workup. The low field-strength facilitates a homogeneous excitation over a wide chemical shift range, minimizing systematic integration errors. The addition of the optimal amount of the nonshifting relaxation agent tris(acetylacetonato) iron(III) minimizes relaxation delays at full resolution, reducing the analysis time to 32 s per sample. The correct choice of processing parameters is also crucial. A step-by-step guideline is provided, the influence of all parameters, including adjustments needed when using high-field spectrometers, is discussed and potential pitfalls are highlighted. The wide applicability of the analytical protocol for reaction optimization is illustrated by three examples: a Buchwald-Hartwig amination, a Suzuki coupling and a C–H arylation reaction.
Design and fabrication of wearable electronic textiles using twisted fiber-based threadsZhang, Kailin; Shi, Xiang; Jiang, Haibo; Zeng, Kaiwen; Zhou, Zihao; Zhai, Peng; Zhang, Lihua; Peng, Huisheng
doi: 10.1038/s41596-024-00956-6pmid: 38429518
Mono-dimensional fiber-based electronics can effectively address the growing demand for improved wearable electronic devices because of their exceptional flexibility and stretchability. For practical applications, functional fiber electronic devices need to be integrated into more powerful and versatile systems to execute complex tasks that cannot be completed by single-fiber devices. Existing techniques, such as printing and sintering, reduce the flexibility and cause low connection strength of fiber-based electronic devices because of the high curvature of the fiber. Here, we outline a twisting fabrication process for fiber electrodes, which can be woven into functional threads and integrated within textiles. The design of the twisted thread structure for fiber devices ensures stable interfacing and good flexibility, while the textile structure features easily accessible, interlaced points for efficient circuit connections. Electronic textiles can be customized to act as displays, health monitors and power sources. We detail three main fabrication sections, including the fabrication of the fiber electrodes, their twisting into electronic threads and their assembly into functional textile-based devices. The procedures require ~10 d and are easily reproducible by researchers with expertise in fabricating energy and electronic devices.