Echo2Pheno: a deep-learning application to uncover echocardiographic phenotypes in conscious mice.

Echocardiography, a rapid and cost-effective imaging technique, assesses cardiac function and structure. Despite its popularity in cardiovascular medicine and clinical research, image-derived phenotypic measurements are manually performed, requiring expert knowledge and training. Notwithstanding great progress in deep-learning applications in small animal echocardiography, the focus has so far only been on images of anesthetized rodents. We present here a new algorithm specifically designed for echocardiograms acquired in conscious mice called Echo2Pheno, an automatic statistical learning workflow for analyzing and interpreting high-throughput non-anesthetized transthoracic murine echocardiographic images in the presence of genetic knockouts. Echo2Pheno comprises a neural network module for echocardiographic image analysis and phenotypic measurements, including a statistical hypothesis-testing framework for assessing phenotypic differences between populations. Using 2159 images of 16 different knockout mouse strains of the German Mouse Clinic, Echo2Pheno accurately confirms known cardiovascular genotype-phenotype relationships (e.g., Dystrophin) and discovers novel genes (e.g., CCR4-NOT transcription complex subunit 6-like, Cnot6l, and synaptotagmin-like protein 4, Sytl4), which cause altered cardiovascular phenotypes, as verified by H&E-stained histological images. Echo2Pheno provides an important step toward automatic end-to-end learning for linking echocardiographic readouts to cardiovascular phenotypes of interest in conscious mice.

Objective hearing threshold identification from auditory brainstem response measurements using supervised and self-supervised approaches.

Hearing loss is a major health problem and psychological burden in humans. Mouse models offer a possibility to elucidate genes involved in the underlying developmental and pathophysiological mechanisms of hearing impairment. To this end, large-scale mouse phenotyping programs include auditory phenotyping of single-gene knockout mouse lines. Using the auditory brainstem response (ABR) procedure, the German Mouse Clinic and similar facilities worldwide have produced large, uniform data sets of averaged ABR raw data of mutant and wildtype mice. In the course of standard ABR analysis, hearing thresholds are assessed visually by trained staff from series of signal curves of increasing sound pressure level. This is time-consuming and prone to be biased by the reader as well as the graphical display quality and scale.In an attempt to reduce workload and improve quality and reproducibility, we developed and compared two methods for automated hearing threshold identification from averaged ABR raw data: a supervised approach involving two combined neural networks trained on human-generated labels and a self-supervised approach, which exploits the signal power spectrum and combines random forest sound level estimation with a piece-wise curve fitting algorithm for threshold finding.We show that both models work well and are suitable for fast, reliable, and unbiased hearing threshold detection and quality control. In a high-throughput mouse phenotyping environment, both methods perform well as part of an automated end-to-end screening pipeline to detect candidate genes for hearing involvement. Code for both models as well as data used for this work are freely available.

Soft windowing application to improve analysis of high-throughput phenotyping data.

MOTIVATION: High-throughput phenomic projects generate complex data from small treatment and large control groups that increase the power of the analyses but introduce variation over time. A method is needed to utlize a set of temporally local controls that maximizes analytic power while minimizing noise from unspecified environmental factors. RESULTS: Here we introduce 'soft windowing', a methodological approach that selects a window of time that includes the most appropriate controls for analysis. Using phenotype data from the International Mouse Phenotyping Consortium (IMPC), adaptive windows were applied such that control data collected proximally to mutants were assigned the maximal weight, while data collected earlier or later had less weight. We applied this method to IMPC data and compared the results with those obtained from a standard non-windowed approach. Validation was performed using a resampling approach in which we demonstrate a 10% reduction of false positives from 2.5 million analyses. We applied the method to our production analysis pipeline that establishes genotype-phenotype associations by comparing mutant versus control data. We report an increase of 30% in significant P-values, as well as linkage to 106 versus 99 disease models via phenotype overlap with the soft-windowed and non-windowed approaches, respectively, from a set of 2082 mutant mouse lines. Our method is generalizable and can benefit large-scale human phenomic projects such as the UK Biobank and the All of Us resources. AVAILABILITY AND IMPLEMENTATION: The method is freely available in the R package SmoothWin, available on CRAN http://CRAN.R-project.org/package=SmoothWin. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A comprehensive and comparative phenotypic analysis of the collaborative founder strains identifies new and known phenotypes.

The collaborative cross (CC) is a large panel of mouse-inbred lines derived from eight founder strains (NOD/ShiLtJ, NZO/HILtJ, A/J, C57BL/6J, 129S1/SvImJ, CAST/EiJ, PWK/PhJ, and WSB/EiJ). Here, we performed a comprehensive and comparative phenotyping screening to identify phenotypic differences and similarities between the eight founder strains. In total, more than 300 parameters including allergy, behavior, cardiovascular, clinical blood chemistry, dysmorphology, bone and cartilage, energy metabolism, eye and vision, immunology, lung function, neurology, nociception, and pathology were analyzed; in most traits from sixteen females and sixteen males. We identified over 270 parameters that were significantly different between strains. This study highlights the value of the founder and CC strains for phenotype-genotype associations of many genetic traits that are highly relevant to human diseases. All data described here are publicly available from the mouse phenome database for analyses and downloads.

Costs of Implementing Quality in Research Practice.

Using standardized guidelines in preclinical research has received increased interest in light of recent concerns about transparency in data reporting and apparent variation in data quality, as evidenced by irreproducibility of results. Although the costs associated with supporting quality through a quality management system are often obvious line items in laboratory budgets, the treatment of the costs associated with quality failure is often overlooked and difficult to quantify. Thus, general estimations of quality costs can be misleading and inaccurate, effectively undervaluing costs recovered by reducing quality defects. Here, we provide examples of quality costs in preclinical research and describe how we have addressed misconceptions of quality management implementation as only marginally beneficial and/or unduly burdensome. We provide two examples of implementing a quality management system (QMS) in preclinical experimental (animal) research environments - one in Europe, the German Mouse Clinic, having established ISO 9001 and the other in the United States, the University of Kentucky (UK), having established Good Laboratory Practice-compliant infrastructure. We present a summary of benefits to having an effective QMS, as may be useful in guiding discussions with funders or administrators to promote interest and investment in a QMS, which ultimately supports shared, mutually beneficial outcomes.

Principles and application of LIMS in mouse clinics.

Large-scale systemic mouse phenotyping, as performed by mouse clinics for more than a decade, requires thousands of mice from a multitude of different mutant lines to be bred, individually tracked and subjected to phenotyping procedures according to a standardised schedule. All these efforts are typically organised in overlapping projects, running in parallel. In terms of logistics, data capture, data analysis, result visualisation and reporting, new challenges have emerged from such projects. These challenges could hardly be met with traditional methods such as pen & paper colony management, spreadsheet-based data management and manual data analysis. Hence, different Laboratory Information Management Systems (LIMS) have been developed in mouse clinics to facilitate or even enable mouse and data management in the described order of magnitude. This review shows that general principles of LIMS can be empirically deduced from LIMS used by different mouse clinics, although these have evolved differently. Supported by LIMS descriptions and lessons learned from seven mouse clinics, this review also shows that the unique LIMS environment in a particular facility strongly influences strategic LIMS decisions and LIMS development. As a major conclusion, this review states that there is no universal LIMS for the mouse research domain that fits all requirements. Still, empirically deduced general LIMS principles can serve as a master decision support template, which is provided as a hands-on tool for mouse research facilities looking for a LIMS.

Integrating modelling and smart sensors for environmental and human health.

Sensors are becoming ubiquitous in everyday life, generating data at an unprecedented rate and scale. However, models that assess impacts of human activities on environmental and human health, have typically been developed in contexts where data scarcity is the norm. Models are essential tools to understand processes, identify relationships, associations and causality, formalize stakeholder mental models, and to quantify the effects of prevention and interventions. They can help to explain data, as well as inform the deployment and location of sensors by identifying hotspots and areas of interest where data collection may achieve the best results. We identify a paradigm shift in how the integration of models and sensors can contribute to harnessing 'Big Data' and, more importantly, make the vital step from 'Big Data' to 'Big Information'. In this paper, we illustrate current developments and identify key research needs using human and environmental health challenges as an example.

Mouse large-scale phenotyping initiatives: overview of the European Mouse Disease Clinic (EUMODIC) and of the Wellcome Trust Sanger Institute Mouse Genetics Project.

Two large-scale phenotyping efforts, the European Mouse Disease Clinic (EUMODIC) and the Wellcome Trust Sanger Institute Mouse Genetics Project (SANGER-MGP), started during the late 2000s with the aim to deliver a comprehensive assessment of phenotypes or to screen for robust indicators of diseases in mouse mutants. They both took advantage of available mouse mutant lines but predominantly of the embryonic stem (ES) cells resources derived from the European Conditional Mouse Mutagenesis programme (EUCOMM) and the Knockout Mouse Project (KOMP) to produce and study 799 mouse models that were systematically analysed with a comprehensive set of physiological and behavioural paradigms. They captured more than 400 variables and an additional panel of metadata describing the conditions of the tests. All the data are now available through EuroPhenome database (www.europhenome.org) and the WTSI mouse portal (http://www.sanger.ac.uk/mouseportal/), and the corresponding mouse lines are available through the European Mouse Mutant Archive (EMMA), the International Knockout Mouse Consortium (IKMC), or the Knockout Mouse Project (KOMP) Repository. Overall conclusions from both studies converged, with at least one phenotype scored in at least 80% of the mutant lines. In addition, 57% of the lines were viable, 13% subviable, 30% embryonic lethal, and 7% displayed fertility impairments. These efforts provide an important underpinning for a future global programme that will undertake the complete functional annotation of the mammalian genome in the mouse model.

Innovations in phenotyping of mouse models in the German Mouse Clinic.

Under the label of the German Mouse Clinic (GMC), a concept has been developed and implemented that allows the better understanding of human diseases on the pathophysiological and molecular level. This includes better understanding of the crosstalk between different organs, pleiotropy of genes, and the systemic impact of envirotypes and drugs. In the GMC, experts from various fields of mouse genetics and physiology, in close collaboration with clinicians, work side by side under one roof. The GMC is an open-access platform for the scientific community by providing phenotypic analysis in bilateral collaborations ("bottom-up projects") and as a partner and driver in international large-scale biology projects ("top-down projects"). Furthermore, technology development is a major topic in the GMC. Innovative techniques for primary and secondary screens are developed and implemented into the phenotyping pipelines (e.g., detection of volatile organic compounds, VOCs).

Mouse phenotyping.

Model organisms like the mouse are important tools to learn more about gene function in man. Within the last 20 years many mutant mouse lines have been generated by different methods such as ENU mutagenesis, constitutive and conditional knock-out approaches, knock-down, introduction of human genes, and knock-in techniques, thus creating models which mimic human conditions. Due to pleiotropic effects, one gene may have different functions in different organ systems or time points during development. Therefore mutant mouse lines have to be phenotyped comprehensively in a highly standardized manner to enable the detection of phenotypes which might otherwise remain hidden. The German Mouse Clinic (GMC) has been established at the Helmholtz Zentrum München as a phenotyping platform with open access to the scientific community (www.mousclinic.de; [1]). The GMC is a member of the EUMODIC consortium which created the European standard workflow EMPReSSslim for the systemic phenotyping of mouse models (http://www.eumodic.org/[2]).

EuroPhenome: a repository for high-throughput mouse phenotyping data.

The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and disease. The EuroPhenome project (http://www.EuroPhenome.org) is a comprehensive resource for raw and annotated high-throughput phenotyping data arising from projects such as EUMODIC. EUMODIC is gathering data from the EMPReSSslim pipeline (http://www.empress.har.mrc.ac.uk/) which is performed on inbred mouse strains and knock-out lines arising from the EUCOMM project. The EuroPhenome interface allows the user to access the data via the phenotype or genotype. It also allows the user to access the data in a variety of ways, including graphical display, statistical analysis and access to the raw data via web services. The raw phenotyping data captured in EuroPhenome is annotated by an annotation pipeline which automatically identifies statistically different mutants from the appropriate baseline and assigns ontology terms for that specific test. Mutant phenotypes can be quickly identified using two EuroPhenome tools: PhenoMap, a graphical representation of statistically relevant phenotypes, and mining for a mutant using ontology terms. To assist with data definition and cross-database comparisons, phenotype data is annotated using combinations of terms from biological ontologies.

Water quality modeling in sewer networks: Review and future research directions.

Urban sewer networks (SNs) are increasingly facing water quality issues as a result of many challenges, such as population growth, urbanization and climate change. A promising way to addressing these issues is by developing and using water quality models. Many of these models have been developed in recent years to facilitate the management of SNs. Given the proliferation of different water quality models and the promise they have shown, it is timely to assess the state-of-the-art in this field, to identify potential challenges and suggest future research directions. In this review, model types, modeled quality parameters, modeling purpose, data availability, type of case studies and model performance evaluation are critically analyzed and discussed based on a review of 110 papers published between 2010 and 2019. The review identified that applications of empirical and kinetic models dominate those of data-driven models for addressing water quality issues. The majority of models are developed for prediction and process understanding using experimental or field sampled data. While many models have been applied to real problems, the corresponding prediction accuracies are overall moderate or, in some cases, low, especially when dealing with larger SNs. The review also identified the most common issues associated with water quality modeling of SNs and based on these proposed several future research directions. These include the identification of appropriate data resolutions for the development of different SN models, the need and opportunity to develop hybrid SN models and the improvement of SN model transferability.

Microinjection of Cre recombinase protein into zygotes enables specific deletion of two eukaryotic selection cassettes and enhances the expression of a DsRed2 reporter gene in Ccr2/Ccr5 double-deficient mice.

The chemokine receptors CCR2 and CCR5 represent potential novel therapeutic targets to treat important inflammatory and infectious diseases, including atherosclerosis and HIV infection. To study the functions of both receptors in vivo, we aimed to generate Ccr2/Ccr5 double-deficient mice. As these genes are separated by <20 kb, they were inactivated consecutively by two rounds of gene targeting in embryonic stem (ES) cells. Thereby neomycin and hygromycin selection cassettes flanked by four identical loxP recognition sequences for Cre recombinase were integrated into the ES cell genome together with EGFP and DsRed2 reporter genes. Both selection cassettes could be deleted in vitro by transiently transfecting ES cells with Cre expression vectors. However, after blastocyst microinjection these cells yielded only weak chimeras, and germline transmission was not achieved. Therefore, Ccr2/Ccr5 double-deficient mice were generated from ES cells still carrying both selection cassettes. Microinjection of zygotes with a recombinant fusion protein consisting of maltose-binding protein and Cre (MBP-Cre) allowed the selective deletion of both cassettes. All sequences in between and both reporter genes were left intact. Deletion of both selection cassettes resulted in enhanced DsRed2 reporter gene expression. Cre protein microinjection of zygotes represents a novel approach to perform complex recombination tasks.

MausDB: an open source application for phenotype data and mouse colony management in large-scale mouse phenotyping projects.

BACKGROUND: Large-scale, comprehensive and standardized high-throughput mouse phenotyping has been established as a tool of functional genome research by the German Mouse Clinic and others. In all these projects, vast amounts of data are continuously generated and need to be stored, prepared for data-mining procedures and eventually be made publicly available. Thus, central storage and integrated management of mouse phenotype data, genotype data, metadata and linked external data are highly important. Requirements most probably depend on the individual mouse housing unit or project and the demand for either very specific individual database solutions or very flexible solutions that can be easily adapted to local demands. Not every group has the resources and/or the know-how to develop software for this purpose. A database application has been developed for the German Mouse Clinic in order to meet all requirements mentioned above. RESULTS: We present MausDB, the German Mouse Clinic web-based database application that integrates standard mouse colony management, phenotyping workflow scheduling features and mouse phenotyping result data management. It links mouse phenotype data with genotype data, metadata and external data such as public web databases, which is a prerequisite for comprehensive data analysis and mining. We describe how this can be achieved with a lean and user-friendly system built on open standards. CONCLUSION: MausDB is suited for large-scale, high-throughput phenotyping facilities but can also be used exclusively for mouse colony management within smaller units or projects. The system is successfully used as the primary mouse and data management tool of the German Mouse Clinic and other mouse facilities. We offer MausDB to the scientific community as open source software to provide a system for storage of data from functional genomics projects in a well-structured, easily accessible form.

Understanding gene functions and disease mechanisms: Phenotyping pipelines in the German Mouse Clinic.

Since decades, model organisms have provided an important approach for understanding the mechanistic basis of human diseases. The German Mouse Clinic (GMC) was the first phenotyping facility that established a collaboration-based platform for phenotype characterization of mouse lines. In order to address individual projects by a tailor-made phenotyping strategy, the GMC advanced in developing a series of pipelines with tests for the analysis of specific disease areas. For a general broad analysis, there is a screening pipeline that covers the key parameters for the most relevant disease areas. For hypothesis-driven phenotypic analyses, there are thirteen additional pipelines with focus on neurological and behavioral disorders, metabolic dysfunction, respiratory system malfunctions, immune-system disorders and imaging techniques. In this article, we give an overview of the pipelines and describe the scientific rationale behind the different test combinations.

Regulatory context is a crucial part of gene function.

Information about the time and place of gene transcription, which until recently was only possible by extensive experimental analysis, can now be predicted through in silico analysis. Using the human RANTES/CCL5 promoter, we show that organizational features of promoters derived from promoter sequences contain information about the spatial and temporal 'functional context' of expression.

LitMiner and WikiGene: identifying problem-related key players of gene regulation using publication abstracts.

The LitMiner software is a literature data-mining tool that facilitates the identification of major gene regulation key players related to a user-defined field of interest in PubMed abstracts. The prediction of gene-regulatory relationships is based on co-occurrence analysis of key terms within the abstracts. LitMiner predicts relationships between key terms from the biomedical domain in four categories (genes, chemical compounds, diseases and tissues). Owing to the limitations (no direction, unverified automatic prediction) of the co-occurrence approach, the primary data in the LitMiner database represent postulated basic gene-gene relationships. The usefulness of the LitMiner system has been demonstrated recently in a study that reconstructed disease-related regulatory networks by promoter modelling that was initiated by a LitMiner generated primary gene list. To overcome the limitations and to verify and improve the data, we developed WikiGene, a Wiki-based curation tool that allows revision of the data by expert users over the Internet. LitMiner (http://andromeda.gsf.de/litminer) and WikiGene (http://andromeda.gsf.de/wiki) can be used unrestricted with any Internet browser.

The First Scube3 Mutant Mouse Line with Pleiotropic Phenotypic Alterations.

The vertebrate Scube (Signal peptide, CUB, and EGF-like domain-containing protein) family consists of three independent members, Scube1-3, which encode secreted cell surface-associated membrane glycoproteins. Limited information about the general function of this gene family is available, and their roles during adulthood. Here, we present the first Scube3 mutant mouse line (Scube3N294K/N294K), which clearly shows phenotypic alterations by carrying a missense mutation in exon 8, and thus contributes to our understanding of SCUBE3 functions. We performed a detailed phenotypic characterization in the German Mouse Clinic (GMC). Scube3N294K/N294K mutants showed morphological abnormalities of the skeleton, alterations of parameters relevant for bone metabolism, changes in renal function, and hearing impairments. These findings correlate with characteristics of the rare metabolic bone disorder Paget disease of bone (PDB), associated with the chromosomal region of human SCUBE3 In addition, alterations in energy metabolism, behavior, and neurological functions were detected in Scube3N294K/N294K mice. The Scube3N294K/N294K mutant mouse line may serve as a new model for further studying the effect of impaired SCUBE3 gene function.

Mouse Phenotype Database Integration Consortium: integration [corrected] of mouse phenome data resources.

Understanding the functions encoded in the mouse genome will be central to an understanding of the genetic basis of human disease. To achieve this it will be essential to be able to characterize the phenotypic consequences of variation and alterations in individual genes. Data on the phenotypes of mouse strains are currently held in a number of different forms (detailed descriptions of mouse lines, first-line phenotyping data on novel mutations, data on the normal features of inbred lines) at many sites worldwide. For the most efficient use of these data sets, we have initiated a process to develop standards for the description of phenotypes (using ontologies) and file formats for the description of phenotyping protocols and phenotype data sets. This process is ongoing and needs to be supported by the wider mouse genetics and phenotyping communities to succeed. We invite interested parties to contact us as we develop this process further.

Chemokine receptor Ccr2 deficiency reduces renal disease and prolongs survival in MRL/lpr lupus-prone mice.

MRL/MpJ-Fas(lpr)/J (MRL/lpr) mice represent a well-established mouse model of human systemic lupus erythematosus. MRL/lpr mice homozygous for the spontaneous lymphoproliferation mutation (lpr) are characterized by systemic autoimmunity, massive lymphadenopathy associated with proliferation of aberrant T cells, splenomegaly, hypergammaglobulinemia, arthritis, and fatal immune complex-mediated glomerulonephritis. It was reported previously that steady-state mRNA levels for the chemokine (C-C motif) receptor 2 (Ccr2) continuously increase in kidneys of MRL/lpr mice. For examining the role of Ccr2 for development and progression of immune complex-mediated glomerulonephritis, Ccr2-deficient mice were generated and backcrossed onto the MRL/lpr genetic background. Ccr2-deficient MRL/lpr mice developed less lymphadenopathy, had less proteinuria, had reduced lesion scores, and had less infiltration by T cells and macrophages in the glomerular and tubulointerstitial compartment. Ccr2-deficient MRL/lpr mice survived significantly longer than MRL/lpr wild-type mice despite similar levels of circulating immunoglobulins and comparable immune complex depositions in the glomeruli of both groups. Anti-dsDNA antibody levels, however, were reduced in the absence of Ccr2. The frequency of CD8+ T cells in peripheral blood was significantly lower in Ccr2-deficient MRL/lpr mice. Thus Ccr2 deficiency influenced not only monocyte/macrophage and T cell infiltration in the kidney but also the systemic T cell response in MRL/lpr mice. These data suggest an important role for Ccr2 both in the general development of autoimmunity and in the renal involvement of the lupus-like disease. These results identify Ccr2 as an additional possible target for the treatment of lupus nephritis.