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The Age of CT Pulmonary Angiography.

With the introduction of multi detector-row CT (MDCT), computed tomography (CT) has been firmly established as the de facto first line test for imaging patients with suspected pulmonary embolism (PE). However, remaining concerns regarding CT's accuracy for diagnosis of isolated peripheral emboli have prevented the unanimous acceptance of this test as the standard of reference for imaging PE. Consequently, many patients with a chest CT scan negative for PE undergo additional testing for a definitive rule-out of PE, increasing radiation burden, risk of complications, and health care cost. After a decade of uncertainty, there is now conclusive evidence that computed tomography (CT), if positive, provides reliable confirmation of the presence of PE and, more importantly, if negative effectively rules out clinically significant PE. Current endeavors to streamline and facilitate workflow for CT diagnosis of PE will further improve the acceptance, utility, and importance of this test. Thus, rather than seeking further confirmation for the accuracy of CT for PE diagnosis, future efforts ought to be directed at harnessing the unique strengths of this test. Examples include improvements in workflow, CT derivation of right ventricular function parameters for triage and prognostication of patients with acute PE, and the comprehensive assessment of patients with acute chest pain for PE, coronary disease, aortic disease, and pulmonary disease by means of a single, contrast enhanced, ECG-synchronized CT scan. At the same time, efforts must be directed at refining clinical pathways to ensure appropriate use and avoid overutilization of this test.

Humans↗

Microbiology Galaxy Lab: The first community-driven gateway for reproducible and FAIR analysis of microbial data.

The explosion of microbial omics data has outpaced the ability of many researchers to analyze it, with complex tools and limited computational resources creating barriers to discovery. To address this gap, we present the Microbiology Galaxy Lab: a free, globally accessible, community-supported platform that combines state-of-the-art analytical power with user-friendly accessibility. Supported by the Galaxy and global microbiology communities, this platform integrates over 315 tool suites and 115 curated workflows, enabling comprehensive metabarcoding, (meta)genomic, (meta)transcriptomic, and (meta)proteomic data analysis within a FAIR-aligned environment. It also supports research in the health and infectious disease sectors, as well as in environmental microbiology. The platform's utility is exemplified through various use cases, including antimicrobial resistance tracking, biomarker prediction, microbiome classification, and functional annotation of key microbes. Built on reproducibility and community engagement, it supports creation, sharing, and updating of best-practice workflows. Over 35 tutorials and learning paths empower scientists, fostering an ecosystem that keeps resources at the forefront of microbial science. The Microbiology Galaxy Lab enables collective analysis, democratising research, thereby accelerating discovery across the global microbiology community (microbiology.usegalaxy.org, .eu, .org.au, .fr).

Journal Article↗

Automated chromatin profiling with spa-ChIP-seq uncovers the impacts of condition variations.

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is widely used to study the genomic localization of DNA-associated proteins. However, conventional protocols include multiple manual steps that can introduce inconsistency and limit scalability, thereby restricting the inclusion of appropriate replicates and controls. Although the introduction of liquid handling platforms has improved reproducibility, most existing efforts have automated only a subset of the workflow, and extending automation to efficiently map non-histone proteins, such as chromatin regulators, remains challenging. Here, we present a fully automated implementation of our previously developed single-pot ChIP-seq protocol (Texari et al. 2021), named spa-ChIP-seq, which enables scalable processing of 8 to 96 ChIP-seq samples from crosslinked cells to sequencing-ready library in approximately three days with an estimated cost of $70 per sample. Benchmarking spa-ChIP-seq against manual ChIP-seq performed in parallel demonstrates comparable signal-to-noise ratio between the two workflows. Using spa-ChIP-seq, we systematically evaluate multiple parameters including shearing and crosslinking conditions, buffer compositions, and the ratio of antibody to cell-number. We find, for the first time to our knowledge, that weaker genomic localization signals are sensitive to changing the antibody to cell-number ratio, whereas the stronger signals remain unaffected. This finding underscores the importance of maintaining consistent antibody-to-cell-number ratio for comparative studies, such as treatment responses or chromatin-QTL mapping. The spa-ChIP-seq protocol is publicly available, including deck setups, operational parameters, and scripts. We envision that this robust, cost-efficient protocol will facilitate high-throughput, reproducible ChIP-seq analyses, supporting large-scale studies of antibody validation, compound screening, population genomics, and diagnostic frameworks.

Journal Article↗

Gene Specific Pathogenicity Predictor for Chromatin-Remodeling BAF Complex-Associated Neurodevelopmental Disorders.

Advancements in whole genome sequencing have increased the number of variants of uncertain significance (VUS) identified in patient genomes. This has created a diagnostic bottleneck for genetic counselors tasked with sifting through these variants and determining those most likely to be causative for a patient's clinical presentation. Machine learning (ML) tools can aid in identifying pathogenic variants from VUS, but there is a need for gene-specific algorithms that predict pathogenic variants with high accuracy. To address this need, we present a workflow for developing gene-specific, ensemble-learning ML tools, that leverage outputs from other algorithms, locations of variants within the gene, and evolutionary conservation data to make a prediction of pathogenicity. Variants in SMARCA2 and SMARCA4 that are associated with rare neurodevelopmental diseases were used to screen 15 ML algorithms. A random forest learner was tuned to yield a final accuracy of 0.93 on holdout data. Generalizing this predictor to other BAF complex proteins resulted in a sharp decline in performance. We trained a final predictor for all genes in the study to create a predictor that identifies pathogenic variants in these BAF subunits with an accuracy of 0.91 on holdout data. This predictor specific to BAF complex proteins performs with higher accuracy and AUROC than any other predictor. The decline in performance when generalized to other proteins emphasizes the need for the gene-specific calibration of predictors. Our workflow for the development of such models provides a quick, computationally inexpensive route for improving the ML tools available to genetic counselors.

Journal Article↗

Parameter-space screening: a powerful tool for high-throughput crystal structure determination.

The determination of protein structures on a genomic scale requires both computing capacity and efficiency increases at many stages along the complex process. By combining bioinformatics workflow-management techniques, cluster-based computing and popular crystallographic structure-determination software packages, an efficient and powerful new tool for structural biology/genomics has been developed. Using the workflow manager and a simple web interface, the researcher can, in a few easy steps, set up hundreds of structure-determination jobs, each using a slightly different set of program input parameters, thus efficiently screening parameter space for the optimal input-parameter combination, i.e. a set of parameters that leads to a successful structure determination. Upon completion, results from the programs are harvested, analyzed, sorted based on success and presented to the user via the web interface. This approach has been applied with success in more than 30 cases. Examples of successful structure determinations based on single-wavelength scattering (SAS) are described and include cases where the 'rational' crystallographer-based selection of input parameters values had failed.

Computational Biology↗

Is There a Fly in My Soup? To What Extent Do Metabarcoding and Individual Barcoding Tell the Same Story?

Metabarcoding has become the method of choice for characterizing complex arthropod communities. The extent to which metabarcoded bulk samples will recover the same community composition as individual sequencing of all individuals in the sample remains poorly quantified. Biases such as unequal extraction of DNA from different taxa, primer mismatches and non-random PCR may cause the selective drop-out of species from metabarcoding data. At the same time, DNA metabarcoding may reveal arthropod taxa present not as individuals, but as DNA residues on the surface or in the gut of insects. To quantify the consistency in sample contents established by different means, we metabarcoded 45 bulk insect samples, then extracted all arthropods and sequenced them individually. Metabarcoding targeted 418 bp at the 3' end of the Folmer barcoding region, while individual barcodes captured the entire 658 bp Folmer region. The metabarcoding workflow, including PCR amplification, sequencing and bioinformatics, was performed in three replicates from three separate lysate aliquots per sample. For the main analyses, sequences were assigned to Barcode Index Numbers (BINs) as identical taxonomic categories across data types, thereby allowing the detection of even rare but biologically true taxa. Since such reference-based validation will be unavailable to any researcher dealing with metabarcoding data alone, we validated our key findings through an alternative workflow, i.e., de novo clustering of sequences. We found that metabarcoding is replicable, as different replicates of the same sample recover similar species richness and composition. Individual barcoding and metabarcoding provide similar impressions of relative differences in community structure: species-rich vs. species-poor samples rank similarly among data types (Spearman's ⍴ = 0.88-0.99) as do differences in relative dissimilarity between sample pairs (Spearman's ⍴ = 0.55-0.90). Dissimilarity between data types varies with BIN richness in the sample, but this relationship reflects nestedness rather than turnover: metabarcoding recovers the same set of core species as individual barcoding but adds hundreds of species on top. Any BIN recovered as an individual occurred with high probability in the metabarcoding data, and any BIN found in high read abundances by metabarcoding was likely found as an individual (p > 0.8). In terms of abundances, the number of individual insects per BIN was well predicted by the number of metabarcoding reads (R2 > 0.68 for a model including taxonomy as a random effect). Our analysis suggests that metabarcoding data will be informative of the sample contents in terms of arthropod species richness, composition and taxon-specific abundances. Taxa recovered in low copy numbers in metabarcoding sequence data will likely represent DNA left as residues from past biotic interactions. Barring sequencing errors, both types of data yield biologically relevant insights into the taxa present in the source community.

Animals↗

Comfort and Usability of Digital Versus Conventional Custom-Fit Mouthguards: A Randomized Clinical Trial.

BACKGROUND/OBJECTIVES: The use of mouthguards protects teeth and the supporting tissues against impacts. Digital impressions and 3D-printed models can reduce manufacturing steps and minimize discomfort. This study evaluated the fit, comfort, and usability of custom-made mouthguards, obtained by conventional and digital workflow, in amateur athletes. MATERIALS AND METHODS: Amateur athletes were recruited for this randomized, double-blind, crossover clinical study. Each participant received two 4-mm-thick custom-fit mouthguards made of ethylene vinyl acetate (EVA) sheets using two protocols: conventional impression using alginate to produce dental stone cast (CMP) and intraoral digital scanning to produce 3D-printed resin models (DMP). Each mouthguard was worn during all training and matches over 3&#x2009;months. The order of mouthguard use was randomly assigned. Patient satisfaction with the impression protocol and mouthguard use, model accuracy, and mouthguard fit were assessed. RESULTS: Overall, 46 participants completed the study. The DMP protocol required less execution time (p&#x2009;=&#x2009;0.023), caused less discomfort (p&#x2009;=&#x2009;0.018), anxiety (p&#x2009;=&#x2009;0.008), nausea (p&#x2009;=&#x2009;0.027), difficulty breathing (p&#x2009;<&#x2009;0.001), and unpleasant taste (p&#x2009;=&#x2009;0.006) compared to the CMP protocol. The pain (p&#x2009;=&#x2009;0.971) perceived by the participants was similar in both impression protocols. The CMP-mouthguards were considered to be better fitting by the majority of participants (p&#x2009;=&#x2009;0.027). Between-group comparisons revealed that DMP-mouthguard caused less discomfort immediately postadaptation (p&#x2009;=&#x2009;0.034), with no significant differences observed at 30 or 90&#x2009;days. CONCLUSIONS: The digital workflow demonstrated to be efficient in the fabrication of mouthguards. Digital impression was more comfortable, requiring less execution time, with more accurate printed models and produced mouthguards with reported comfort and fit levels similar to those manufactured conventionally.

Humans↗

Turbo-charging crop improvement: harnessing multiplex editing for polygenic trait engineering and beyond.

Multiplex CRISPR editing has emerged as a transformative platform for plant genome engineering, enabling the simultaneous targeting of multiple genes, regulatory elements, or chromosomal regions. This approach is effective for dissecting gene family functions, addressing genetic redundancy, engineering polygenic traits, and accelerating trait stacking and de novo domestication. Its applications now extend beyond standard gene knockouts to include epigenetic and transcriptional regulation, chromosomal engineering, and transgene-free editing. These capabilities are advancing crop improvement not only in annual species but also in more complex systems such as polyploids, undomesticated wild relatives, and species with long generation times. At the same time, multiplex editing presents technical challenges, including complex construct design and the need for robust, scalable mutation detection. We discuss current toolkits and recent innovations in vector architecture, such as promoter and scaffold engineering, that streamline workflows and enhance editing efficiency. High-throughput sequencing technologies, including long-read platforms, are improving the resolution of complex editing outcomes such as structural rearrangements-often missed by standard genotyping-when targeting repetitive or tandemly spaced loci. To fully realize the potential of multiplex genome engineering, there is growing demand for user-friendly, synthetic biology-compatible, and scalable computational workflows for gRNA design, construct assembly, and mutation analysis. Experimentally validated inducible or tissue-specific promoters are also highly desirable for achieving spatiotemporal control. As these tools continue to evolve, multiplex CRISPR editing is poised to become a foundational technology of next-generation crop improvement to address challenges in agriculture, sustainability, and climate resilience.

Gene Editing↗

Synchrony, waves, and spatial hierarchies in the spread of influenza.

Quantifying long-range dissemination of infectious diseases is a key issue in their dynamics and control. Here, we use influenza-related mortality data to analyze the between-state progression of interpandemic influenza in the United States over the past 30 years. Outbreaks show hierarchical spatial spread evidenced by higher pairwise synchrony between more populous states. Seasons with higher influenza mortality are associated with higher disease transmission and more rapid spread than are mild ones. The regional spread of infection correlates more closely with rates of movement of people to and from their workplaces (workflows) than with geographical distance. Workflows are described in turn by a gravity model, with a rapid decay of commuting up to around 100 km and a long tail of rare longer range flow. A simple epidemiological model, based on the gravity formulation, captures the observed increase of influenza spatial synchrony with transmissibility; high transmission allows influenza to spread rapidly beyond local spatial constraints.

Adult↗

Diagnostic performance of the Sanity 2.0 assay to detect resistance to rifampicin, isoniazid, and fluoroquinolones in tuberculosis.

UNLABELLED: Effective tuberculosis (TB) management relies on prompt diagnosis of Mycobacterium tuberculosis complex (MTBC) and associated drug resistance. The Sanity 2.0 assay is a high-resolution melting assay designed for direct respiratory sample testing, enabling simultaneous detection of MTBC and resistance to rifampicin (RIF), isoniazid (INH), and fluoroquinolones (FQ) in a single step. This study evaluated its diagnostic performance in two registered multicenter trials among bacteriologically confirmed TB patients. Diagnostic performance was evaluated for MTBC detection, as well as for the identification of resistance to RIF, INH, and FQ, using phenotypic drug susceptibility testing, whole-genome sequencing, and a composite reference standard. Agreement analyses were conducted between the Sanity 2.0 assay and Xpert MTB/RIF and Xpert MTB/XDR. Among 611 patients, the Sanity 2.0 assay detected MTBC in 563 patients, exhibiting a sensitivity of 92.1% (95% CI: 89.7-94.0). For detecting resistance to RIF, INH, and FQ, sensitivities exceeded 90%, with specificities of 95.8% (95% CI: 88.5-98.6), 100.0% (95% CI: 96.4-100.0), and 97.8% (95% CI: 93.8-99.3) against the composite reference standard, respectively. The agreement with Xpert MTB/RIF for RIF detection was 98.6% (95% CI: 96.9-99.3). For INH and FQ resistance, the agreement with Xpert MTB/XDR was 92.0% (95% CI: 88.5-94.5) and 94.3% (95% CI: 91.2-96.3), respectively. The Sanity 2.0 assay is a rapid and user-friendly platform capable of detecting both MTBC and key drug resistance. It demonstrated good diagnostic performance and could potentially be an effective alternative to guide individualized anti-TB treatment, especially in resource-limited settings. IMPORTANCE: Rapid and accurate detection of both Mycobacterium tuberculosis complex (MTBC) and key drug resistance is critical to improving tuberculosis treatment outcomes and reducing transmission. However, current molecular diagnostic workflows often require sequential testing, which can delay the initiation of effective and individualized therapy. We evaluated the Sanity 2.0 assay, an integrated high-resolution melting test that simultaneously detects MTBC and resistance to rifampicin, isoniazid, and fluoroquinolone resistance directly from respiratory samples in about 2-3 hours. The assay demonstrated excellent performance, with MTBC detection sensitivity of 92.1% and drug resistance sensitivities exceeding 90% and specificities over 95% against a composite reference standard, as well as strong concordance with World Health Organization-endorsed molecular assays. Implementation of the Sanity 2.0 assay could streamline TB diagnostic workflows; enable rapid, single-step resistance profiling; and facilitate timely, individualized treatment-particularly in resource-limited settings where rapid and comprehensive resistance testing remains a critical unmet need.

Humans↗

Optimized methods for the targeted surveillance of extended-spectrum beta-lactamase-producing Escherichia coli in human stool.

Understanding transmission pathways of important opportunistic, drug-resistant pathogens, such as extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli, is essential to implementing targeted prevention strategies to interrupt transmission and reduce the number of infections. To link transmission of ESBL-producing E. coli (ESBL-EC) between two sources, single-nucleotide resolution of E. coli strains, as well as E. coli diversity within and between samples, is required. However, the microbiological methods to best track these pathogens are unclear. Here, we compared different steps in the microbiological workflow to determine the impact different pre-enrichment broths, pre-enrichment incubation times, selection in pre-enrichment, selective plating, and DNA extraction methods had on recovering ESBL-EC from human stool samples, with the aim to acquire high-quality DNA for sequencing and genomic epidemiology. We demonstrate that using a 4-h pre-enrichment in Buffered Peptone Water, plating on cefotaxime-supplemented MacConkey agar and extracting DNA using Lucigen MasterPure DNA Purification kit improves the recovery of ESBL-EC from human stool and produced high-quality DNA for whole-genome sequencing. We conclude that our optimized workflow can be applied for single-nucleotide variant analysis of an ESBL-EC from stool.IMPORTANCEDrug-resistant infections are increasingly difficult to treat with antibiotics. Preventing infections is thus highly beneficial. To do this, we need to understand how drug-resistant bacteria spread to take action to stop infection and transmission. This requires us to accurately trace these bacteria between different sources. In this study, we compared different laboratory methods to see which worked best for detecting extended-spectrum beta-lactamase (ESBL)-producing E. coli, a common cause of urinary tract or bloodstream infections, from human stool samples. We found that enriching stool in a nutrient broth for 4 h, then plating the bacterial suspension on antibiotic-selective MacConkey agar, and finally extracting DNA from the bacteria using a specific DNA purification kit resulted in improved recovery of ESBL E. coli and high-quality DNA. Sequencing multiple isolates from stool allowed us to distinguish unambiguously and at high resolution between different variants of ESBL E. coli present in stool.

Humans↗

Targeted next-generation sequencing for drug-resistant tuberculosis diagnosis: implementation considerations for bacterial load, regimen selection and diagnostic algorithm placement.

INTRODUCTION: Early and accurate diagnosis of drug-resistant tuberculosis (DR-TB) is essential for improving treatment outcomes. Phenotypic drug susceptibility testing (pDST) is comprehensive but slow, while rapid molecular assays provide resistance information for a limited number of drugs. Targeted next-generation sequencing (tNGS) offers the potential for broad and rapid resistance detection, but its integration into diagnostic algorithms has been hindered by uncertainty about its placement within existing workflows. METHODS: This study evaluated the extent to which two tNGS solutions-Deeplex Myc-TB (GenoScreen) and TB Drug Resistance Test (Oxford Nanopore Technologies, ONT)-provided interpretable drug resistance results that could inform regimen design, in comparison to other WHO-recommended molecular assays and pDST. Data were collected from three high-burden DR-TB settings under the Seq&Treat study. Sequencing success rates and drug resistance detection were analysed based on: (1) the initial Xpert MTB/RIF result (very low, low, medium, high), (2) resistance results for drugs in WHO-recommended regimens and (3) performance relative to other WHO-endorsed assays. The potential impact of different algorithms on the estimates was also considered. Key factors influencing successful tNGS adoption within diagnostic pathways were identified, leveraging insights from the Seq&Treat diagnostic accuracy study. RESULTS: Sequencing success rates were 88.5% (GenoScreen) and 93.1% (ONT) across 763 samples. While tNGS provided complete resistance data for 73%-86% of drugs in recommended regimens, pDST achieved 92%-93%. Both tNGS solutions matched or exceeded the sensitivity of WHO-recommended molecular assays. CONCLUSIONS: This study highlights the critical role of tNGS as a centralised tool for comprehensive drug resistance testing to inform DR-TB treatment decisions following initial screening assays. By complementing existing molecular tests with tNGS, diagnostic workflows can be optimised to ensure timely and comprehensive resistance detection. These findings support policy updates to integrate tNGS into global TB diagnostic algorithms. TRIAL REGISTRATION NUMBER: NCT04239326.

Humans↗

Getting teams to talk: development and pilot implementation of a checklist to promote interprofessional communication in the OR.

BACKGROUND: Pilot studies of complex interventions such as a team checklist are an essential precursor to evaluating how these interventions affect quality and safety of care. We conducted a pilot implementation of a preoperative team communication checklist. The objectives of the study were to assess the feasibility of the checklist (that is, team members' willingness and ability to incorporate it into their work processes); to describe how the checklist tool was used by operating room (OR) teams; and to describe perceived functions of the checklist discussions. METHODS: A checklist prototype was developed and OR team members were asked to implement it before 18 surgical procedures. A research assistant was present to prompt the participants, if necessary, to initiate each checklist discussion. Trained observers recorded ethnographic field notes and 11 brief feedback interviews were conducted. Observation and interview data were analyzed for trends. RESULTS: The checklist was implemented by the OR team in all 18 study cases. The rate of team participation was 100% (33 vascular surgery team members). The checklist discussions lasted 1-6 minutes (mean 3.5) and most commonly took place in the OR before the patient's arrival. Perceived functions of the checklist discussions included provision of detailed case related information, confirmation of details, articulation of concerns or ambiguities, team building, education, and decision making. Participants consistently valued the checklist discussions. The most significant barrier to undertaking the team checklist was variability in team members' preoperative workflow patterns, which sometimes presented a challenge to bringing the entire team together. CONCLUSIONS: The preoperative team checklist shows promise as a feasible and efficient tool that promotes information exchange and team cohesion. Further research is needed to determine the sustainability and generalizability of the checklist intervention, to fully integrate the checklist routine into workflow patterns, and to measure its impact on patient safety.

Communication↗

Exploring obstacles to proper timing of prophylactic antibiotics for surgical site infections.

BACKGROUND: Surgical site infections remain one of the leading types of nosocomial infections. The administration of prophylactic antibiotics within a specific interval has been shown to reduce the burden of surgical site infections, but adherence to proper timing guidelines remains problematic. This study examined perceived obstacles to the use of evidence-based guidelines for the timely administration of prophylactic antibiotics to prevent surgical site infections. METHODS: 27 semi-structured interviews were conducted with anesthesiologists (n = 12), surgeons (n = 11), and perioperative administrators (n = 4) in two large academic hospitals to elicit their perceptions of the factors that prevent the timely administration of prophylactic antibiotics. Using a grounded theory approach, transcripts were analyzed for recurrent themes. RESULTS: Despite having knowledge of guidelines, participants perceived consistent failure in the proper timing of antibiotic administration. Thematic analysis revealed a number of obstacles to the observance of guidelines including: (1) low priority, (2) inconvenience, (3) workflow, (4) organizational communication, and (5) role perception. Workflow and role perception were the dominant obstacles. CONCLUSION: This study suggests that proper antibiotic timing is thwarted by significant obstacles. The gap between evidence-based guidelines and practice is populated by individual values, professional conflicts, and organizational conflicts which must be addressed in order to achieve optimal practice in this domain. Using group interviews to reveal these factors to team members and managers may be a first step to resolving the gap and reducing surgical site infections.

Anesthesiology↗

Spatial Integration of Protein and Chromosomal States Reveals Early Copy-Number Changes and Genotype-Associated Immune Neighborhoods in Serous Ovarian Cancer Evolution.

UNLABELLED: Detecting chromosomal copy-number alterations together with protein-defined cell states in intact tissue is critical for understanding early clonal evolution and microenvironmental interactions in cancer. We developed ORION-FISH, which integrates high-plex tissue imaging with a morphology-preserving DNA fluorescence in situ hybridization (DNA-FISH) workflow and single-cell registration, yielding measurements concordant with clinical FISH. In high-grade serous ovarian carcinoma (HGSOC), ORION-FISH recapitulated known chromosomal changes while revealing subclonal heterogeneity missed by targeted sequencing. Applied to serous tubal intraepithelial carcinomas, precursors of HGSOC, ORION-FISH identified intermixed epithelial cells with MYC or CCNE1 copy-number gains, as well as concurrent alterations associated with distinct immune microenvironments. In addition, epithelial cells with MYC and CCNE1 copy-number gains were detected in morphologically normal fallopian tube epithelium, along with rare MDM4 increases across epithelial lineages. Together, ORION-FISH provides a framework linking chromosomal copy-number states to protein-defined phenotypes within preserved tissue architecture, enabling context-aware interrogation of early copy-number diversification at single-cell resolution. SIGNIFICANCE: We introduce ORION-FISH, a spatially resolved workflow integrating multiplexed protein imaging with DNA-FISH to map genomic alterations within intact tissues. Applying this approach to ovarian cancer precursors reveals early copy-number diversification and associations with the local immune context, providing a foundation for studying how genomic and microenvironmental states coevolve during tumor initiation.

Female↗

Spatial proteomic mapping of the human and mouse retina using IBEX.

We generated a comparative spatial proteomic atlas of the human and mouse retina using a highly multiplexed immunohistochemistry technique called iterative bleaching extends multiplexity (IBEX). We refined the IBEX workflow by integrating an antibody dissociation option alongside chemical bleaching. This dual strategy enabled removal of the entire antibody complex, permitting the flexible use of antibodies from the same host species across iterative cycles. We coupled this workflow with super-resolution imaging via deconvolution and applied it to the retina of healthy humans and WT mice and the Crb1rd8 mouse model. We successfully imaged over 25 protein markers on human and mouse tissue sections, generating spatial atlases of the major retinal cell populations. Cross-species protein expression was compared to scRNA-seq datasets to identify protein and transcript disparities. Super-resolution IBEX delineated the ultrastructural features of the outer limiting membrane (OLM), identifying CD44 as a core structural component tightly colocalized with a highly organized F-actin belt within M&#xfc;ller glial endfeet. Using the Crb1rd8 mouse model, disruption of this complex was spatially associated with rosette formation and OLM structural failure. In summary, spatial proteomic atlases of the human and mouse retina were used to reveal insights into the arrangement of major retinal cell populations and OLM structure.

Animals↗

A summarization approach for Affymetrix GeneChip data using a reference training set from a large, biologically diverse database.

BACKGROUND: Many of the most popular pre-processing methods for Affymetrix expression arrays, such as RMA, gcRMA, and PLIER, simultaneously analyze data across a set of predetermined arrays to improve precision of the final measures of expression. One problem associated with these algorithms is that expression measurements for a particular sample are highly dependent on the set of samples used for normalization and results obtained by normalization with a different set may not be comparable. A related problem is that an organization producing and/or storing large amounts of data in a sequential fashion will need to either re-run the pre-processing algorithm every time an array is added or store them in batches that are pre-processed together. Furthermore, pre-processing of large numbers of arrays requires loading all the feature-level data into memory which is a difficult task even with modern computers. We utilize a scheme that produces all the information necessary for pre-processing using a very large training set that can be used for summarization of samples outside of the training set. All subsequent pre-processing tasks can be done on an individual array basis. We demonstrate the utility of this approach by defining a new version of the Robust Multi-chip Averaging (RMA) algorithm which we refer to as refRMA. RESULTS: We assess performance based on multiple sets of samples processed over HG U133A Affymetrix GeneChip arrays. We show that the refRMA workflow, when used in conjunction with a large, biologically diverse training set, results in the same general characteristics as that of RMA in its classic form when comparing overall data structure, sample-to-sample correlation, and variation. Further, we demonstrate that the refRMA workflow and reference set can be robustly applied to naïve organ types and to benchmark data where its performance indicates respectable results. CONCLUSION: Our results indicate that a biologically diverse reference database can be used to train a model for estimating probe set intensities of exclusive test sets, while retaining the overall characteristics of the base algorithm. Although the results we present are specific for RMA, similar versions of other multi-array normalization and summarization schemes can be developed.

Algorithms↗

A procedure for the detection of linkage with high density SNP arrays in a large pedigree with colorectal cancer.

BACKGROUND: The apparent dominant model of colorectal cancer (CRC) inheritance in several large families, without mutations in known CRC susceptibility genes, suggests the presence of so far unidentified genes with strong or moderate effect on the development of CRC. Linkage analysis could lead to identification of susceptibility genes in such families. In comparison to classical linkage analysis with multi-allelic markers, single nucleotide polymorphism (SNP) arrays have increased information content and can be processed with higher throughput. Therefore, SNP arrays can be excellent tools for linkage analysis. However, the vast number of SNPs on the SNP arrays, combined with large informative pedigrees (e.g. >35-40 bits), presents us with a computational complexity that is challenging for existing statistical packages or even exceeds their capacity. We therefore setup a procedure for linkage analysis in large pedigrees and validated the method by genotyping using SNP arrays of a colorectal cancer family with a known MLH1 germ line mutation. METHODS: Quality control of the genotype data was performed in Alohomora, Mega2 and SimWalk2, with removal of uninformative SNPs, Mendelian inconsistencies and Mendelian consistent errors, respectively. Linkage disequilibrium was measured by SNPLINK and Merlin. Parametric linkage analysis using two flanking markers was performed using MENDEL. For multipoint parametric linkage analysis and haplotype analysis, SimWalk2 was used. RESULTS: On chromosome 3, in the MLH1-region, a LOD score of 1.9 was found by parametric linkage analysis using two flanking markers. On chromosome 11 a small region with LOD 1.1 was also detected. Upon linkage disequilibrium removal, multipoint linkage analysis yielded a LOD score of 2.1 in the MLH1 region, whereas the LOD score dropped to negative values in the region on chromosome 11. Subsequent haplotype analysis in the MLH1 region perfectly matched the mutation status of the family members. CONCLUSION: We developed a workflow for linkage analysis in large families using high-density SNP arrays and validated this workflow in a family with colorectal cancer. Linkage disequilibrium has to be removed when using SNP arrays, because it can falsely inflate the LOD score. Haplotype analysis is adequate and can predict the carrier status of the family members.

Adaptor Proteins, Signal Transducing↗