Nature Protocols

Nuclei isolation from myelin-rich adult mouse brain regions remains challenging for single-nucleus RNA sequencing because myelin and debris can reduce nuclei quality. We describe an optimized protocol for mouse hippocampi and cerebella using tube-and-pestle homogenization and low-volume sucrose-gradient pelleting with a standard benchtop centrifuge, with optional magnetic enrichment of nuclei to reduce debris/non-nuclear carryover. Under the tested conditions, the workflow produces intact, debris-reduced nuclei and supports downstream 10x Genomics Flex and PARSE WT library preparation. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=196 HEIGHT=200 SRC="FIGDIR/small/716374v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@ccbd87org.highwire.dtl.DTLVardef@1aef4bcorg.highwire.dtl.DTLVardef@14569a8org.highwire.dtl.DTLVardef@1bc261_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIBenchtop sucrose-gradient pelleting enables rapid nuclei purification from myelin-rich adult mouse brain C_LIO_LIScales across tissue inputs (e.g., hippocampus [~]15-20 mg; cerebellum [~]50-70 mg) without ultracentrifugation or 15 mL gradients C_LIO_LIMagnetic enrichment as the recommended final cleanup step further reduces myelin/debris carryover and is compatible with 10x Flex and PARSE WT workflows. C_LI

To the EditorCRISPR technologies have been widely adopted as powerful tools for targeted genomic manipulation 1. Recently, a new CRISPR-based strategy for precision genome editing was developed that enables diverse genomic alterations to be directly written into target sites without requiring double-strand breaks (DSBs) or donor templates 2. Termed prime editing, this approach involves two key components: 1) a catalytically impaired Cas9 nickase fused to a reverse transcriptase (PE2), and 2) a multifunctional prime editing guide RNA (pegRNA) that specifies the target site and further acts as a template for reverse transcription (RT). pegRNAs are similar to standard single-guide RNAs (sgRNAs), but additionally have a customizable extension on the 3 end. The 3 extension is composed of a RT template that encodes the desired edit and a primer binding site (PBS) that anneals to the target genomic site to prime the RT reaction 2. These additional components considerably increase the complexity of pegRNA design compared to standard sgRNAs. While many tools have been developed for identifying candidate sgRNAs in a target DNA sequence 3-8, no user-friendly web application currently exists for designing pegRNAs. We therefore developed pegFinder, a streamlined web tool that rapidly designs candidate pegRNAs (Figure 1). The pegFinder web portal is freely available at http://pegfinder.sidichenlab.org/ (Supplementary Figure 1). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=168 SRC="FIGDIR/small/081612v1_fig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@1494188org.highwire.dtl.DTLVardef@6d80ccorg.highwire.dtl.DTLVardef@122eaf1org.highwire.dtl.DTLVardef@16e8e71_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1:C_FLOATNO pegFinder: A pegRNA designer for CRISPR prime editing Schematic of the pegFinder workflow for designing CRISPR prime editing pegRNAs. The user provides the wildtype DNA sequence, and the edited DNA sequence. Optionally, the user can include the results from sgRNA designer tools to pegFinder, or specify a preselected sgRNA spacer to be used for pegRNA design. pegFinder then generates a pegRNA that can be used to engineer the desired alterations. pegFinder also reports alternative RT templates and PBS sequences of varying lengths that can be swapped into the pegRNA for downstream experimental optimization. pegFinder further reports secondary nicking sgRNAs that can increase prime editing efficiency (PE3 method). C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=154 SRC="FIGDIR/small/081612v1_figS1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@149ba2corg.highwire.dtl.DTLVardef@15da377org.highwire.dtl.DTLVardef@96fe3borg.highwire.dtl.DTLVardef@10cfee0_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOSupplementary Figure 1:C_FLOATNO pegFinder web interface Screenshot of the pegFinder web interface, available at http://pegfinder.sidichenlab.org. C_FIG

The isolation of specific cell types of the brain is essential to study cell-type-specific differences in complex neurological diseases such as Alzheimers disease. This protocol isolates oligodendrocytes, microglia, endothelial cells, astrocytes, and neurons from a single mouse brain. The process involves gentle tissue homogenization, debris removal, and sequential sorting of five distinct cell types. We validate cell purity and viability using flow cytometry and RT-qPCR. This protocol is well-suited for a range of downstream applications, including genomics, transcriptomics, and proteomics. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/666877v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@1426b97org.highwire.dtl.DTLVardef@1a5bb77org.highwire.dtl.DTLVardef@1b69f32org.highwire.dtl.DTLVardef@8da416_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundIt is not a trivial step to move from single-cell RNA-seq (scRNA-seq) data production to data analysis. There is a lack of intuitive training materials and easy-to-use analysis tools, and researchers can find it difficult to master the basics of scRNA-seq quality control and analysis.\n\nResultsWe have developed a range of easy-to-use scripts, together with their corresponding Galaxy wrappers, that make scRNA-seq training and analysis accessible to researchers previously daunted by the prospect of scRNA-seq analysis. The simple command-line tools and the point-and-click nature of Galaxy makes it easy to assess, visualise, and quality control scRNA-seq data.\n\nConclusionWe have developed a suite of scRNA-seq tools that can be used for both training and more in-depth analyses.

Compared to traditional enzyme-based in situ amplification methods, Hybridization Chain Reaction v3.0 (HCR v3.0) offers high specificity for spatial RNA visualization but lacks the sensitivity needed for short or low-abundance targets, especially in thick tissue with high autofluorescence. We describe next-generation HCR detection methods that combine the specificity of HCR v3.0 with enzyme-based signal amplification through catalysis (HCR-Cat) or immunostaining (HCR-Immuno, HCR-Multi). These methods enhance sensitivity for robust spatial detection of both short and low-abundance targets, work well in challenging tissue environments, and enable broad utility across basic research and translational applications. These methods allow spatial detection of challenging targets that are poorly-accessible using HCR v3.0, as well as quantitative analysis of single transcripts even when targeting short RNAs with a limited number of probes.

Covaris g-TUBEs can be used to fragment DNA to pre-determined sizes based on the relative centrifugal force that they are run at. They are recommended for use while preparing Oxford Nanopore Technology libraries by the manufacturer. However, the volumes and DNA concentration typically used for ONT libraries are outside the range of the example data provided by Covaris. Here, we ran g-TUBEs at three different relative centrifugal forces and determined the effect on DNA fragmentation in the range 0.5 - 4 {micro}g. This dataset can be used to inform the effective fragmentation of DNA for creating Oxford Nanopore libraries of an optimal size.

Efficient access to soluble recombinant proteins remains a major bottleneck in biochemical and structural studies. We describe an aqueous, solvent-centric, fully miniaturized 96-well workflow to screen extraction conditions that preserve soluble recombinant protein during lysis and clarification in a single working day. Liquid-nitrogen-frozen E. coli pellets are cryogenically bead-milled with stainless-steel beads, retaining the native intracellular milieu while ensuring uniform disruption. The resulting wet, frozen cell powder can therefore be extracted with user-defined solvent, enabling systematic exploration of pH, ionic strength, detergents, and chaotropes. Protein solubility is assessed by a 1 {micro}L chromogenic anti-His dot-blot. We demonstrate the use of the protocol by solubilizing a set of highly challenging de novo-generated proteins and show that dot-blot intensity provides a practical semi-quantitative proxy for successful extraction of soluble proteins. We also provide experimentally supported guidelines on the influence of solvent reagents on subsequent steps of protein production, SDS-PAGE, and Ni-NTA purification. This workflow is compatible with upstream genetic solubility-enhancement, chassis- and cultivation-based strategies and enables direct transition from screening hits to scale-up. Because the workflow uses standard molecular biology equipment and inexpensive consumables, it can be readily adopted or automated in most laboratories.

Single-cell RNA sequencing (scRNAseq) is a robust technology for parsing gene expression in individual cells from a tissue or other complex source. One application involves experiments where cells from multiple species are recovered from a single sample, such as when human cells are transplanted into an animal model. We transplanted microglial precursor cells into newborn mouse brain and then recovered unenriched cortical tissue six months later. Dissociated cells were assessed by scRNAseq. The default method for analyzing these results begins by aligning sequencing reads with a mixture of both mouse and human reference genomes. While this clearly identifies the human cells as a distinct cluster, the clustering is artificially driven by expression from non-comparable gene identifiers from different species. We devised a method for translating expression counts from human to mouse and evaluated four algorithms for parsing mixed-species scRNAseq data. Our optimal approach split raw sequencing reads according to the best alignment score in each genome, and then re-aligned reads only with the appropriate genome. After gene symbol translation, pooled results indicate that cell types are more appropriately clustered and that differential expression analysis identifies species-specific patterns. This method should be applicable to any mixed-species scRNAseq experiment.\n\nSummary of optimal strategyO_LIMixed-species scRNAseq data are aligned with mixture of mouse and human reference genomes\nC_LIO_LIThe BAM file is scanned to find the best alignment score for each sequencing read identifier; these are used to split the paired FASTQ files into two sets of files\nC_LIO_LIEach set of species-specific, paired FASTQ files is re-aligned with only the appropriate reference genome\nC_LIO_LIRaw counts imported into Seurat\nC_LIO_LIThe human counts table is translated to mouse gene symbols using a custom HomoloGene translation table\nC_LIO_LIResults are merged and analyzed\nC_LI

RNA-sequencing provides high-dimensional, quantitative measurements of the states of cells, tissues, organs, and whole organisms. Plate-based RNA-seq protocols allow for a wider range of experimental designs than droplet sequencing methods, but are less scalable due to the practical challenges of plate-based liquid handling. Here, we present STOMP-seq, a method that extends SMART RNA-seq protocols, like Smart-seq2 and Smart-seq3, to include sample-identifying barcodes on the 5 end of each amplified transcript. These barcodes allow samples to be pooled immediately after reverse transcription, enabling a 12-fold multiplexing strategy that reduces liquid handling complexity and enzyme costs several-fold. Suitable for both manual and robotic library preparation approaches, STOMP-seq reduces protocol execution times four-fold while improving library complexity and coverage. Together, these advantages combine to make possible new large-scale experimental designs, in particular population-scale sequencing projects like the multi-generational study of gene-expression heritability presented here. STOMP-seq offers a "drop-in" replacement for Smart-seq2 and Smart-seq3, removing practical barriers that currently limit the quality and scope of plate-based transcriptomic data. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/645277v2_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@83f1b4org.highwire.dtl.DTLVardef@717012org.highwire.dtl.DTLVardef@174e34forg.highwire.dtl.DTLVardef@f790b3_HPS_FORMAT_FIGEXP M_FIG C_FIG

An automated ultra-microtome capable of sectioning thousands of ultrathin sections onto standard TEM slot grids was developed and used to section: a complete Drosophila melanogaster first-instar larva, three sections per grid, into 4,866 34-nm-thick sections with a cutting and pickup success rate of 99.74%; 30 microns of mouse cortex measuring roughly 400 um x 2000 um at 40 nm per slice; and a full adult Drosophila brain and ventral nerve column into 9,300 sections with a pickup success rate of 99.95%. The apparatus uses optical interferometers to monitor a reference distance between the cutting knife and multiple sample blocks. Cut sections are picked up from the knife-boat water surface while they are still anchored to the cutting knife. Blocks without embedded tissue are used to displace tissue-containing sections away from the knife edge so that the tissue regions end up in the grid slot instead of on the grid rim.

In this work, we have focused on the study of the Basic Local Alignment Search Tool (BLAST) and Multiple Sequence Alignment (Clustal-X) of different monoclonal mice antibodies to understand better the multiple alignments of sequences. Our strategy was to compare the light chains of multiple monoclonal antibodies to each other, calculating their identity percentage and in which amino acid portion. (See below figure 2) Subsequently, the same survey of heavy chains was carried out with the same methodology. (See below figure 3) Finally, sequence alignment between the light chain of one antibody and the heavy chain of another antibody was studied to understand what happens if chains are exchanged between antibodies. (See below figure 4) From our results of BLAST estimation alignment, we have reported that the Light Chains (Ls) of Monoclonal Antibodies in Comparison have a sequence Homology of about 60-80% and they have a part identical in sequence zone in range 100-210 residues amino acids, except ID PDB 4ISV, which it turns out to have a 40% lower homology than the others antibodies. As far as, the heavy chains (Hs) of Monoclonal Antibodies are concerned, however they tend to have a less homology of sequences, compared to lights chains consideration, equal to 60%-70% and they have an identical part in the sequence zone between 150-210 residues amino acids; with the exception of ID PDB 3I9G-3W9D antibodies that have an equal homology at 50%. (See supporting part) Summing up: about 70-80% identity among 2 light chains of 2 antibodies, 60-70% identity between 2 heavy chains of 2 antibodies, 30% identity between the two chains of a antibody and 30% if you compare the light chain of one antibody with the heavy chain of another antibody. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=190 SRC="FIGDIR/small/451785v2_fig2.gif" ALT="Figure 2"> View larger version (61K): org.highwire.dtl.DTLVardef@1a5d6b1org.highwire.dtl.DTLVardef@b214daorg.highwire.dtl.DTLVardef@176fed3org.highwire.dtl.DTLVardef@153eb17_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig 2C_FLOATNO Comparison of two light chains between 5 antibodies C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=190 SRC="FIGDIR/small/451785v2_fig3.gif" ALT="Figure 3"> View larger version (57K): org.highwire.dtl.DTLVardef@6f66f9org.highwire.dtl.DTLVardef@1d19afforg.highwire.dtl.DTLVardef@17119forg.highwire.dtl.DTLVardef@85fe98_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig 3C_FLOATNO Comparison of two heavy chains between 5 antibodies C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/451785v2_fig4.gif" ALT="Figure 4"> View larger version (43K): org.highwire.dtl.DTLVardef@10dc2f7org.highwire.dtl.DTLVardef@7b0885org.highwire.dtl.DTLVardef@16c72c8org.highwire.dtl.DTLVardef@e3c1d1_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig 4C_FLOATNO Comparison of two light chains (ID PDB 1PSK and ID PDB 1F11) of antibodies, estimated on the left side by ClustalX and on the right side by BLAST C_FIG

Preparation of single-cell sequencing libraries includes adding nucleotide barcodes to assist with pooling samples or cells together for sequencing. The popularity of droplet-based single-cell protocols has spurred the development of computational tools that expect the read structure of the assay to include a cell barcode (CB). Microwell plate-based protocols, such as the Switching Mechanism At the 5 end of the RNA Transcript (SMART) single-cell RNA sequencing (scRNA-seq) family of methods, typically do not add a CB as part of the library preparation method as there is typically one cell per well and standard unique dual indices are sufficient for multiplexing. While several tools exist to manipulate and parse varying single-cell read structures, no tool is currently available to easily add synthetic CBs to enable use of computational tooling that expects the presence of a CB, such as STARsolo, zUMIs, and Alevin. Synthbar fills this gap as a lightweight tool that is assay agnostic, can add user-defined CBs, and modify read structures. Availability and ImplementationSource code and binaries are freely available at https://github.com/jamorrison/synthbar under the MIT license. Synthbar is implemented in C and is supported on macOS and Linux. Supplementary informationSupplementary data are available at the end of the document.

MOTIVATIONLongitudinal molecular studies of the mouse brain are limited by the need for terminal tissue collection. This prevents analysis of preexisting molecular states and their evolution within the same individual. We developed a stereotactic microbiopsy technique that enables minimally invasive sampling of defined brain regions in vivo. The method preserves survival while yielding material suitable for RNA and nuclei isolation. It provides a practical solution for linking baseline molecular states to subsequent behavioural, pharmacological, or disease-related outcomes. SUMMARYThis study presents a stereotactic microbiopsy technique for sampling defined brain regions in living mice, enabling transcriptomic and epigenomic analyses without sacrificing the animal. The method will allow pre-intervention tissue collection, making it possible to separate preexisting molecular differences from experience- or treatment-induced changes. We show that microbiopsies yield sufficient, high-quality RNA and chromatin for sequencing, with minimal tissue damage that largely resolves over time. The procedure uses standard stereotactic equipment and achieves reproducible spatial precision when the syringe is stabilised. This approach provides a practical framework for within-subject molecular comparisons, reducing animal use and enabling longitudinal profiling of the living mouse brain. It establishes a foundation for investigating how baseline molecular states influence later physiological or behavioural outcomes.

The barcoded connectomics tool MAPseq enables highly multiplexed projection mapping of individual neurons by translating neuroanatomy into a format solvable by DNA sequencing. Here we present MAPseq2, a user-friendly protocol with up to [~]10-fold increased sensitivity and [~]10-fold decreased cost compared to the current state of the art. As MAPseq workflows are used across a range of barcoded connectomics methods, including BARseq, BRlCseq, and ConnectlD, all improvements in MAPseq2 directly transfer to these technologies.

SummaryThe combination of target capture metagenomics and long-read sequencing represents a powerful approach for the characterisation of rare microbial taxa and their functional genes. However, standard Nanopore library preparations are incompatible with established capture protocols. A possible workaround is the preparation of Illumina libraries prior to ONT sequencing. Currently, this hybrid approach is hindered by a lack of specialised demultiplexing software capable of handling residual adapter fragments; Nanopores higher error rates and positional variability. Here, we present deluxpore: a Nextflow pipeline that demultiplexes Nanopore reads from Illumina dual-indexed libraries (NEBNext and Nextera) using BLAST alignment and Levenshtein distance matching. Extensive benchmarking across 18 replicates validates the viability and precision of this hybrid indexing approach. Benchmarking demonstrates that accurate demultiplexing requires minimum Q20 data quality and strategic index selection. Unique index-to-sample designs achieved 91.7% sample recovery at Q20 versus 46.1% for combinatorial approaches. We also identified high-crosstalk index pairs within NEBNext Primer Set A and provide an optimized 8-sample configuration achieving ~95% accuracy at Q20. deluxpore enables reliable, automated demultiplexing for hybrid capture-long-read sequencing workflows. Availability and implementationdeluxpore is implemented in Nextflow, Python, and Bash under the GNU GPL v3.0. Source code, documentation, and benchmarking workflows are available at https://github.com/compgenomicslab/deluxpore and https://github.com/compgenomicslab/deluxpore-benchmarking.

Life science research often depends on the construction and analysis of recombinant DNA molecules, where sequence accuracy is critical. However, the field continues to face a reproducibility crisis, partly due to the lack of comprehensive, systematic, and verifiable documentation of genetic constructions. Although most cloning procedures are deterministic and theoretically describable in a complete and unambiguous way, published methods are typically described in a form free narrative, making them laborious to reproduce and assess for completeness. Tools like the Python package Pydna support programmable and reproducible cloning strategies but require coding expertise, which can be a barrier for some users. To address this, we developed Pydnaweb and dnaudit, two open-source and complementary web tools that build on Pydna. Pydnaweb offers simulation of unit operations such as PCR and restriction digestion providing results in text format. These results can be collected and combined to form complex cloning strategies in a bottom-up approach. Dnaudit can verify such collections for internal consistency and that the cloning strategy meet a specific goal such as the expression of a protein sequence. The tools are design for a low barrier of entry, and they can be used separately. This workflow enables fully automated validation, providing a no-code, reproducible solution for documenting and sharing molecular cloning workflows. These tools ease compliance with FAIR principles and align with emerging standards for the transparent and reproducible sharing of scientific methods and data.

Helicases have emerged as promising targets for the development of antiviral drugs; however, the family remains largely undrugged. To support the focused development of viral helicase inhibitors we identified, collected, and integrated all chemogenomics data for all available helicases from the ChEMBL database. After thoroughly curating and enriching the data with relevant annotations we have created a derivative database of helicase inhibitors which we dubbed Heli-SMACC (Helicase-targeting SMAll Molecule Compound Collection). The current version of Heli-SMACC contains 20,432 bioactivity entries for viral, human, and bacterial helicases. We have selected 30 compounds with promising viral helicase activity and tested them in a SARS-CoV-2 NSP13 ATPase assay. Twelve compounds demonstrated ATPase inhibition and a consistent dose-response curve. The Heli-SMACC database may serve as a reference for virologists and medicinal chemists working on the development of novel helicase inhibitors. Heli-SMACC is publicly available at https://smacc.mml.unc.edu. HighlightsO_LIWe created a curated Helicase-Targeting SMAll Molecule Compound Collection (Heli-SMACC). C_LIO_LIHeli-SMACC covers 29 human, viral, and bacterial helicases. C_LIO_LITwelve of thirty selected compounds demonstrated inhibitory activity in a SARS-CoV-2 NSP13 ATPase Assay. C_LIO_LIHeli-SMACC is freely available online at https://smacc.mml.unc.edu. C_LI TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/602122v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@8e098forg.highwire.dtl.DTLVardef@115cb2borg.highwire.dtl.DTLVardef@1cd9da3org.highwire.dtl.DTLVardef@2870a6_HPS_FORMAT_FIGEXP M_FIG C_FIG

The introduction of isobaric tagging reagents enabled more accurate, high-throughput quantitative proteomics by enabling multiple samples to be multiplexed. One drawback of these workflows is the relative expense of the proprietary isobaric reagents, which is often only second to the expense of the instruments themselves. These highly reactive chemical tags are only commercially available in relatively large aliquots compared to the typical amounts of peptides analyzed in proteomic workflows today. Excess reagents are typically disposed of following a single labeling experiment or those performed within a few days of opening a new kit. We present a simple procedure to aliquot commercial isobaric tagging reagents and demonstrate the successful and high efficiency labeling of multiple samples over a period of six months. The samples presented herein were selected as the most diverse ones labeled by prepared aliquots from a single labeling reagent kit over this period. We observe comparable labeling efficiency from 100 microgram to 100 picograms of peptide when labeling samples from both human digest standards, cancer cell lines prepared in-house and from cells directly obtained from human organ donors, despite differences in cell type, lysis, and digestion procedures. No labeling experiment of whole human proteomics samples achieved less than 92% labeling efficiency over this period. When preparing phosphoproteomic samples 6 months after the date of the aliquoting procedure, we observed a decrease in labeling efficiency to approximately 86%, indicating the end of the useful lifetime of aliquots prepared in this manner. Over this period, we have effectively reduced the reagent costs of each experiment to less than 10% of the predicted costs when following the manufacturer instructions for use and disposal. While aliquoting of reagents can be performed by hand, we provide a complete template for automatic aliquoting using an affordable liquid handling robot, including plans for 3D printing of two parts we have found useful for streamlining this procedure. Abstract Graphic O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/449560v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@18cd7eeorg.highwire.dtl.DTLVardef@1b48065org.highwire.dtl.DTLVardef@159761forg.highwire.dtl.DTLVardef@5a0896_HPS_FORMAT_FIGEXP M_FIG C_FIG

Introducing SimpliPyTEM, a Python library and accompanying GUI that simplifies the post-acquisition evaluation of transmission electron microscopy (TEM) images, helping streamline the workflow. After an imaging session, a folder of image and/or video files, typically containing low contrast and large file size 32-bit images, can be quickly processed via SimpliPyTEM into high-quality, high-contrast .jpg images with suitably sized scale-bars. The app can also generate HTML or PDF files containing the processed images for easy viewing and sharing. Additionally, SimpliPyTEM has a specific focus on in situ TEM videos, an emerging field of EM, allowing for fast data processing into preview movies, averages, image series, or motion corrected averages using MotionCor2. The accompanying Python library offers many standard image processing methods, all simplified to a single command, plus a module to analyse particle morphology and population. This latter application is particularly useful for life sciences investigations. User-friendly tutorials and clear documentation are included to help guide users through the processing and analysis. We invite the EM community to contribute to and further develop this open-source package.

Joint single-cell measurements of gene expression and DNA regulatory element activity holds great promise as a tool to understand transcriptional regulation. Towards this goal we have developed Smart3-ATAC, a highly sensitive method which allows joint mRNA and chromatin accessibility analysis genome wide in single cells. With Smart3-ATAC, we are able to obtain the highest possible quality measurements per cell. The method combines transcriptomic profiling based on the highly sensitive Smart-seq3 protocol on cytosolic mRNA, with a novel low-loss single-cell ATAC (scATAC) protocol to measure chromatin accessibility. Compared to current droplet multiome methods, the yield of both the scATAC protocol and mRNA-seq protocol is markedly higher.