LabKey Server NAb: A tool for analyzing, visualizing and sharing results from neutralizing antibody assays

<p>Abstract</p> <p>Background</p> <p>Multiple types of assays allow sensitive detection of virus-specific neutralizing antibodies. For example, the extent of antibody neutralization of HIV-1, SIV and SHIV can be measured in the TZM-bl cell line through the degree of luciferase reporter gene expression after infection. In the past, neutralization curves and titers for this standard assay have been calculated using an Excel macro. Updating all instances of such a macro with new techniques can be unwieldy and introduce non-uniformity across multi-lab teams. Using Excel also poses challenges in centrally storing, sharing and associating raw data files and results.</p> <p>Results</p> <p>We present LabKey Server's NAb tool for organizing, analyzing and securely sharing data, files and results for neutralizing antibody (NAb) assays, including the luciferase-based TZM-bl NAb assay. The customizable tool supports high-throughput experiments and includes a graphical plate template designer, allowing researchers to quickly adapt calculations to new plate layouts. The tool calculates the percent neutralization for each serum dilution based on luminescence measurements, fits a range of neutralization curves to titration results and uses these curves to estimate the neutralizing antibody titers for benchmark dilutions. Results, curve visualizations and raw data files are stored in a database and shared through a secure, web-based interface. NAb results can be integrated with other data sources based on sample identifiers. It is simple to make results public after publication by updating folder security settings.</p> <p>Conclusions</p> <p>Standardized tools for analyzing, archiving and sharing assay results can improve the reproducibility, comparability and reliability of results obtained across many labs. LabKey Server and its NAb tool are freely available as open source software at <url>http://www.labkey.com</url> under the Apache 2.0 license. Many members of the HIV research community can also access the LabKey Server NAb tool without installing the software by using the Atlas Science Portal (<url>https://atlas.scharp.org</url>). Atlas is an installation of LabKey Server.</p

Microbial interactions and differential protein expression in Staphylococcus aureus –Candida albicans dual-species biofilms

The fungal species Candida albicans and the bacterial species Staphylococcus aureus are responsible for a majority of hospital-acquired infections and often coinfect critically ill patients as complicating polymicrobial biofilms. To investigate biofilm structure during polymicrobial growth, dual-species biofilms were imaged with confocal scanning laser microscopy. Analyses revealed a unique biofilm architecture where S. aureus commonly associated with the hyphal elements of C. albicans. This physical interaction may provide staphylococci with an invasion strategy because candidal hyphae can penetrate through epithelial layers. To further understand the molecular mechanisms possibly responsible for previously demonstrated amplified virulence during coinfection, protein expression studies were undertaken. Differential in-gel electrophoresis identified a total of 27 proteins to be significantly differentially produced by these organisms during coculture biofilm growth. Among the upregulated staphylococcal proteins was l-lactate dehydrogenase 1, which confers resistance to host-derived oxidative stressors. Among the downregulated proteins was the global transcriptional repressor of virulence factors, CodY. These findings demonstrate that the hyphae-mediated enhanced pathogenesis of S. aureus may not only be due to physical interactions but can also be attributed to the differential regulation of specific virulence factors induced during polymicrobial growth. Further characterization of the intricate interaction between these pathogens at the molecular level is warranted, as it may aid in the design of novel therapeutic strategies aimed at combating fungal–bacterial polymicrobial infection

LabKey Server: An open source platform for scientific data integration, analysis and collaboration

<p>Abstract</p> <p>Background</p> <p>Broad-based collaborations are becoming increasingly common among disease researchers. For example, the Global HIV Enterprise has united cross-disciplinary consortia to speed progress towards HIV vaccines through coordinated research across the boundaries of institutions, continents and specialties. New, end-to-end software tools for data and specimen management are necessary to achieve the ambitious goals of such alliances. These tools must enable researchers to organize and integrate heterogeneous data early in the discovery process, standardize processes, gain new insights into pooled data and collaborate securely.</p> <p>Results</p> <p>To meet these needs, we enhanced the LabKey Server platform, formerly known as CPAS. This freely available, open source software is maintained by professional engineers who use commercially proven practices for software development and maintenance. Recent enhancements support: (i) Submitting specimens requests across collaborating organizations (ii) Graphically defining new experimental data types, metadata and wizards for data collection (iii) Transitioning experimental results from a multiplicity of spreadsheets to custom tables in a shared database (iv) Securely organizing, integrating, analyzing, visualizing and sharing diverse data types, from clinical records to specimens to complex assays (v) Interacting dynamically with external data sources (vi) Tracking study participants and cohorts over time (vii) Developing custom interfaces using client libraries (viii) Authoring custom visualizations in a built-in R scripting environment.</p> <p>Diverse research organizations have adopted and adapted LabKey Server, including consortia within the Global HIV Enterprise. Atlas is an installation of LabKey Server that has been tailored to serve these consortia. It is in production use and demonstrates the core capabilities of LabKey Server. Atlas now has over 2,800 active user accounts originating from approximately 36 countries and 350 organizations. It tracks roughly 27,000 assay runs, 860,000 specimen vials and 1,300,000 vial transfers.</p> <p>Conclusions</p> <p>Sharing data, analysis tools and infrastructure can speed the efforts of large research consortia by enhancing efficiency and enabling new insights. The Atlas installation of LabKey Server demonstrates the utility of the LabKey platform for collaborative research. Stable, supported builds of LabKey Server are freely available for download at <url>http://www.labkey.org</url>. Documentation and source code are available under the Apache License 2.0.</p

Network Replication of Inequality in Medical Crowdsourced Funding

Thesis (Master's)--University of Washington, 2020In 2018, over 250,000 American families found themselves unable to pay for medical care and turned to the online “crowdfunding” service GoFundMe to raise money online. The $650 million dollars raised from these medical campaigns appear to have filled a sizable hole in the American social safety net. Yet crowdfunding is at heart a network process, and a large body of research shows that social networks can reproduce inequality. In this paper I show that medical crowdfunding replicates patterns of racial, ethnic, and geographic income stratification in ways that are consistent with network theory. Using 2,618 GoFundMe campaigns hand-coded for perceived race and ethnicity of the recipient, I show that Black and Hispanic beneficiaries receive substantially less money via their networks than White and Asian beneficiaries. Hierarchical linear models show that social network access via online sharing does not vary by race and ethnicity. However, network mobilization, measured in terms of the number and size of donations, varies substantially and produces unequal returns to campaigns. Variations in the number of donations can largely be explained by differences in estimated network financial capacity, but variations in donation size are not fully accounted for even in models including proxies for network income. Estimates of donor race and ethnicity indicate that donors of all races and ethnicities tend to give White recipients the largest donations and Black recipients the smallest. Overall, I demonstrate that the use of “crowd insurance” in place of sufficient medical insurance reproduces existing patterns of inequality

A mouse model repository for cancer biomarker discovery.

Early detection of cancer using biomarkers obtained from blood or other easily accessible tissues would have a significant impact on reducing cancer mortality. However, identifying new blood-based biomarkers has been hindered by the dynamic complexity of the human plasma proteome, confounded by genetic and environmental variability, and the scarcity of high quality controlled samples. In this report, we discuss a new paradigm for biomarker discovery through the use of mouse models. Inbred mouse models of cancer recapitulate many critical features of human cancer, while eliminating sources of environmental and genetic variability. The ability to collect samples from highly matched cases and controls under identical conditions further reduces variability which is critical for successful biomarker discovery. We describe the establishment of a repository containing tumor, plasma, urine, and other tissues from 10 different mouse models of human cancer, including two breast, two lung, two prostate, two gastrointestinal, one ovarian, and one skin tumor model. We present the overall design of this resource and its potential use by the research community for biomarker discovery

Ancillary study management systems: a review of needs

BACKGROUND: The valuable clinical data, specimens, and assay results collected during a primary clinical trial or observational study can enable researchers to answer additional, pressing questions with relatively small investments in new measurements. However, management of such follow-on, “ancillary” studies is complex. It requires coordinating across institutions, sites, repositories, and approval boards, as well as distributing, integrating, and analyzing diverse data types. General-purpose software systems that simplify the management of ancillary studies have not yet been explored in the research literature. METHODS: We have identified requirements for ancillary study management primarily as part of our ongoing work with a number of large research consortia. These organizations include the Center for HIV/AIDS Vaccine Immunology (CHAVI), the Immune Tolerance Network (ITN), the HIV Vaccine Trials Network (HVTN), the U.S. Military HIV Research Program (MHRP), and the Network for Pancreatic Organ Donors with Diabetes (nPOD). We also consulted with researchers at a range of other disease research organizations regarding their workflows and data management strategies. Lastly, to enhance breadth, we reviewed process documents for ancillary study management from other organizations. RESULTS: By exploring characteristics of ancillary studies, we identify differentiating requirements and scenarios for ancillary study management systems (ASMSs). Distinguishing characteristics of ancillary studies may include the collection of additional measurements (particularly new analyses of existing specimens); the initiation of studies by investigators unaffiliated with the original study; cross-protocol data pooling and analysis; pre-existing participant consent; and pre-existing data context and provenance. For an ASMS to address these characteristics, it would need to address both operational requirements (e.g., allocating existing specimens) and data management requirements (e.g., securely distributing and integrating primary and ancillary data). CONCLUSIONS: The scenarios and requirements we describe can help guide the development of systems that make conducting ancillary studies easier, less expensive, and less error-prone. Given the relatively consistent characteristics and challenges of ancillary study management, general-purpose ASMSs are likely to be useful to a wide range of organizations. Using the requirements identified in this paper, we are currently developing an open-source, general-purpose ASMS based on LabKey Server (http://www.labkey.org) in collaboration with CHAVI, the ITN and nPOD

Ancillary study management systems: a review of needs

Abstract Background The valuable clinical data, specimens, and assay results collected during a primary clinical trial or observational study can enable researchers to answer additional, pressing questions with relatively small investments in new measurements. However, management of such follow-on, “ancillary” studies is complex. It requires coordinating across institutions, sites, repositories, and approval boards, as well as distributing, integrating, and analyzing diverse data types. General-purpose software systems that simplify the management of ancillary studies have not yet been explored in the research literature. Methods We have identified requirements for ancillary study management primarily as part of our ongoing work with a number of large research consortia. These organizations include the Center for HIV/AIDS Vaccine Immunology (CHAVI), the Immune Tolerance Network (ITN), the HIV Vaccine Trials Network (HVTN), the U.S. Military HIV Research Program (MHRP), and the Network for Pancreatic Organ Donors with Diabetes (nPOD). We also consulted with researchers at a range of other disease research organizations regarding their workflows and data management strategies. Lastly, to enhance breadth, we reviewed process documents for ancillary study management from other organizations. Results By exploring characteristics of ancillary studies, we identify differentiating requirements and scenarios for ancillary study management systems (ASMSs). Distinguishing characteristics of ancillary studies may include the collection of additional measurements (particularly new analyses of existing specimens); the initiation of studies by investigators unaffiliated with the original study; cross-protocol data pooling and analysis; pre-existing participant consent; and pre-existing data context and provenance. For an ASMS to address these characteristics, it would need to address both operational requirements (e.g., allocating existing specimens) and data management requirements (e.g., securely distributing and integrating primary and ancillary data). Conclusions The scenarios and requirements we describe can help guide the development of systems that make conducting ancillary studies easier, less expensive, and less error-prone. Given the relatively consistent characteristics and challenges of ancillary study management, general-purpose ASMSs are likely to be useful to a wide range of organizations. Using the requirements identified in this paper, we are currently developing an open-source, general-purpose ASMS based on LabKey Server (http://www.labkey.org) in collaboration with CHAVI, the ITN and nPOD.</p