Biology subjects

Lund, E.

Publications and source records attributed to Lund, E..

7 recordsLinked to original sources

bioRxiv2019

Reproducible data management and analysis using R

BackgroundStandardizing and documenting computational analyses are necessary to ensure reproducible results. It is especially important for large and complex projects where data collection, analysis, and interpretation may span decades. Our objective is therefore to provide methods, tools, and best practice guidelines adapted for analyses in epidemiological studies that use -omics data.\n\nResultsWe describe an R-based implementation of data management and preprocessing. The method is well-integrated with the analysis tools typically used for statistical analysis of -omics data. We document all datasets thoroughly and use version control to track changes to both datasets and code over time. We provide a web application to perform the standardized preprocessing steps for gene expression datasets. We provide best practices for reporting data analysis results and sharing analyses.\n\nConclusionWe have used these tools to organize data storage and documentation, and to standardize the analysis of gene expression data, in the Norwegian Women and Cancer (NOWAC) system epidemiology study. We believe our approach and lessons learned are applicable to analyses in other large and complex epidemiology projects.

bioinformatics↗

bioRxiv2019

Design and assessment of TRAP-CSP fusion antigens as effective malaria vaccines

The circumsporozoite protein (CSP) and thrombospondin-related adhesion protein (TRAP) are major targets for pre-erythrocytic malaria vaccine development. However, the most advanced CSP-based vaccine RTS,S provides only partial protection, highlighting the need for innovative approaches for vaccine design and development. Here we design and characterize TRAP-CSP fusion antigens, and evaluate their immunogenicity and protection against malaria infection. TRAP N-terminal folded domains were fused to CSP C-terminal fragments consisting of the C-terminal TSR domain with or without the intervening repeat region. Homogenous, monomeric and properly folded fusion proteins were purified from mammalian transfectants. Notably, fusion improved expression of chimeras relative to the TRAP or CSP components alone. Immunization of BALB/c mice with the P. berghei TRAP-CSP fusion antigens formulated in AddaVax adjuvant elicited antigen-specific antibody responses. Remarkably, fusion antigens containing the CSP repeat region conferred complete sterile protection against P. berghei sporozoite challenge, and furthermore, mice that survived the challenge were completely protected from re-challenge 16 weeks after the first challenge. In contrast, fusion antigens lacking the CSP repeat region were less effective, indicating that the CSP repeat region provided enhanced protection, which correlated with higher antibody titers elicited by fusion antigens containing the CSP repeat region. In addition, we demonstrated that N-linked glycans had no significant effect on antibody elicitation or protection. Our results show that TRAP-CSP fusion antigens could be highly effective vaccine candidates. Our approach provides a platform for designing multi-antigen/multi-stage fusion antigens as next generation more effective malaria vaccines.

microbiology↗

bioRxiv2019

A 50-year series of mark-recapture data of large-sized brown trout (Salmo trutta) from Lake Mjosa, Norway

BackgroundLong-term data from marked animals provide a wealth of opportunities for studies with high relevance to both basic ecological understanding and successful management in a changing world. The key strength of such data is that they allow to quantify individual variation in vital rates (e.g. survival, growth, reproduction) and then link it mechanistically to dynamics at the population level. However, maintaining the collection of individual-based data over long time periods comes with large logistic efforts and costs, and studies spanning over decades are therefore rare. This is the case particularly for migratory aquatic species, many of which are in decline despite their high ecological, cultural, and economical value. New informationThis paper describes two unique publicly available time series of individual-based data originating from a 51-year mark-recapture study of a land-locked population of large-sized migratory brown trout (Salmo trutta) in Norway: the Hunder trout. In the period 1966-2015, nearly 14,000 adult Hunder trout have been captured and individually marked during their spawning migration from Lake Mjosa to the river Gubrandsdalsl[a]gen. Almost a third of those individuals were later recaptured alive during a later spawning run and/or captured by fishermen and reported dead or alive. This has resulted in the first data series: a mark-recapture-recovery dataset spanning half a century and more than 18,000 capture records. The second data series consists of additional data on juvenile and adult growth and life-history schedules from half of the marked individuals, obtained by means of scale sample analysis. The two datasets offer a rare long-term perspective on individuals and population dynamics and provide unique opportunities to gain insights into questions surrounding management, conservation, and restoration of migratory salmonid populations and freshwater ecosystems.

ecology↗

bioRxiv2018

Spatiotemporally controlled Myosin relocalization and internal pressure cause biased cortical extension to generate sibling cell size asymmetry

Metazoan cells can generate unequal sized sibling cells during cell division. This form of asymmetric cell division depends on spindle geometry and Myosin distribution but the underlying mechanics are unclear. Here, we use atomic force microscopy and live cell imaging to elucidate the biophysical forces involved in the establishment of physical asymmetry in Drosophila neural stem cells. We show that the force driving initial apical membrane expansion is provided by hydrostatic pressure, peaking shortly after anaphase onset, and enabled by a relieve of actomyosin contractile tension on the apical cell cortex. The subsequent increase in contractile forces at the cleavage furrow, combined with the relocalization of basally located Myosin results in basal membrane extension and sustained apical expansion. We propose that spatiotemporally controlled actomyosin contractile tension and hydrostatic pressure enables stereotypic biased membrane expansion to generate sibling cell size asymmetry.

cell biology↗

bioRxiv2017

A Standard Operating Procedure For Outlier Removal In Large-Sample Epidemiological Transcriptomics Datasets

Transcriptome measurements and other -omics type data are increasingly more used in epidemiological studies. Most of omics studies to date are small with samples sizes in the tens, or sometimes low hundreds, but this is changing. Our Norwegian Woman and Cancer (NOWAC) datasets are to date one or two orders of magnitude larger. The NOWAC biobank contains about 50000 blood samples from a prospective study. Around 125 breast cancer cases occur in this cohort each year. The large biological variation in gene expression means that many observations are needed to draw scientific conclusions. This is true for both microarray and RNA-seq type data. Hence, larger datasets are likely to become more common soon.\n\nTechnical outliers are observations that somehow were distorted at the lab or during sampling. If not removed these observations add bias and variance in later statistical analyses, and may skew the results. Hence, quality assessment and data cleaning are important. We find common quality assessment libraries difficult to work with for large datasets for two reasons: slow execution speed and unsuitable visualizations.\n\nIn this paper, we present our standard operating procedure (SOP) for large-sample transcriptomics datasets. Our SOP combines automatic outlier detection with manual evaluation to avoid removing valuable observations. We use laboratory quality measures and statistical measures of deviation to aid the analyst. These are available in the nowaclean R package, currently available on GitHub (https://github.com/3inar/nowaclean). Finally, we evaluate our SOP on one of our larger datasets with 832 observations.

epidemiology↗

bioRxiv2017

Building Applications For Interactive Data Exploration In Systems Biology

As the systems biology community generates and collects data at an unprecedented rate, there is a growing need for interactive data exploration tools to explore the datasets. These tools need to combine advanced statistical analyses, relevant knowledge from biological databases, and interactive visualizations in an application with clear user interfaces. To answer specific research questions tools must provide specialized user interfaces and visualizations. While these are application-specific, the underlying components of a data analysis tool can be shared and reused later. Application developers can therefore compose applications of reusable services rather than implementing a single monolithic application from the ground up for each project.\n\nOur approach for developing data exploration applications in systems biology builds on the microservice architecture. Microservice architectures separates an application into smaller components that communicate using language-agnostic protocols. We show that this design is suitable in bioinformatics applications where applications often use different tools, written in different languages, by different research groups. Packaging each service in a software container enables re-use and sharing of key components between applications, reducing development, deployment, and maintenance time.\n\nWe demonstrate the viability of our approach through a web application, MIxT blood-tumor, for exploring and comparing transcriptional profiles from blood and tumor samples in breast cancer patients. The application integrates advanced statistical software, up-to-date information from biological databases, and modern data visualization libraries.\n\nThe web application for exploring transcriptional profiles, MIxT, is online at mixt-blood-tumor.bci.mcgill.ca and open-sourced at github.com/fjukstad/mixt. Packages to build the supporting microservices are open-sourced as a part of Kvik at github.com/fjukstad/kvik.

bioinformatics↗

bioRxiv2017

Curve Selection For Predicting Breast Cancer Metastasis From Prospective Gene Expression In Blood

We investigate whether there is information in gene expression levels in blood that predicts breast cancer metastasis. Our data comes from the NOWAC epidemiological cohort study where blood samples were provided at enrollment. This could be anywhere from years to weeks before any cancer diagnosis. When and if a cancer is diagnosed, it could be so in different ways: at a screening, between screenings, or in the clinic, outside of the screening program. To build predictive models we propose that variable selection should include followup time and stratify by detection method. We show by simulations that this improves the probability of selecting relevant predictor genes. We also demonstrate that it leads to improved predictions and more stable gene signatures in our data. There is some indication that blood gene expression levels hold predictive information about metastasis. With further development such information could be used for early detection of metastatic potential and as such aid in cancer treatment.

bioinformatics↗