Parallelism and divergence in immune responses: a comparison of expression levels in two lakes

Question: How do immune phenotypes differ between infected and uninfected wild individuals, and is the effect the same in different populations? Organisms: Threespine stickleback (Gasterosteus aculeatus) from two lake populations on the island of North Uist, Scotland, sampled in May 2015. Methods: For each fish, we recorded length, sex, reproductive status, condition, and parasitic infection. We measured the expression levels of eight genes that act as key markers of immune system function using qPCR, and then examined the relationship between measured factors and immune gene expression profiles within each population. Conclusions: Populations differed significantly in their immune gene expression profiles. Within each population, multiple factors, including condition, reproductive status, and Schistocephalus solidus infection levels, were found to correlate with expression levels of different arms of the immune system

High-throughput, quantitative analyses of genetic interactions in E. coli.

Large-scale genetic interaction studies provide the basis for defining gene function and pathway architecture. Recent advances in the ability to generate double mutants en masse in Saccharomyces cerevisiae have dramatically accelerated the acquisition of genetic interaction information and the biological inferences that follow. Here we describe a method based on F factor-driven conjugation, which allows for high-throughput generation of double mutants in Escherichia coli. This method, termed genetic interaction analysis technology for E. coli (GIANT-coli), permits us to systematically generate and array double-mutant cells on solid media in high-density arrays. We show that colony size provides a robust and quantitative output of cellular fitness and that GIANT-coli can recapitulate known synthetic interactions and identify previously unidentified negative (synthetic sickness or lethality) and positive (suppressive or epistatic) relationships. Finally, we describe a complementary strategy for genome-wide suppressor-mutant identification. Together, these methods permit rapid, large-scale genetic interaction studies in E. coli

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

This work was in part supported by the PRIME-XS project, grant agreement number 262067, funded by the European Union seventh Framework Programme; The Netherlands Proteomics Centre, embedded in The Netherlands Genomics Initiative; The Netherlands Bioinformatics Centre; and the Centre for Biomedical Genetics (to S.C., B.B. and A.J.R.H); by NIH grants NCRR RR001614 and RR019934 (to the UCSF Mass Spectrometry Facility, director: A.L. Burlingame, P.B.); and by grants from the MRC, CR-UK, BBSRC and Barts and the London Charity (to P.C.

The dynamics of gene expression changes in a mouse model of oral tumorigenesis may help refine prevention and treatment strategies in patients with oral cancer.

A better understanding of the dynamics of molecular changes occurring during the early stages of oral tumorigenesis may help refine prevention and treatment strategies. We generated genome-wide expression profiles of microdissected normal mucosa, hyperplasia, dysplasia and tumors derived from the 4-NQO mouse model of oral tumorigenesis. Genes differentially expressed between tumor and normal mucosa defined the "tumor gene set" (TGS), including 4 non-overlapping gene subsets that characterize the dynamics of gene expression changes through different stages of disease progression. The majority of gene expression changes occurred early or progressively. The relevance of these mouse gene sets to human disease was tested in multiple datasets including the TCGA and the Genomics of Drug Sensitivity in Cancer project. The TGS was able to discriminate oral squamous cell carcinoma (OSCC) from normal oral mucosa in 3 independent datasets. The OSCC samples enriched in the mouse TGS displayed high frequency of CASP8 mutations, 11q13.3 amplifications and low frequency of PIK3CA mutations. Early changes observed in the 4-NQO model were associated with a trend toward a shorter oral cancer-free survival in patients with oral preneoplasia that was not seen in multivariate analysis. Progressive changes observed in the 4-NQO model were associated with an increased sensitivity to 4 different MEK inhibitors in a panel of 51 squamous cell carcinoma cell lines of the areodigestive tract. In conclusion, the dynamics of molecular changes in the 4-NQO model reveal that MEK inhibition may be relevant to prevention and treatment of a specific molecularly-defined subgroup of OSCC

A comparative study of ethylene emanation upon nitrogen deficiency in natural accessions of Arabidopsis thaliana

An original approach to develop sustainable agriculture with less nitrogen fertilizer inputs is to tackle the cross-talk between nitrogen nutrition and plant growth regulators. In particular the gaseous hormone, ethylene, is a prime target for that purpose. The variation of ethylene production in natural accessions of the model species Arabidopsis thaliana was explored in response to the nitrate supply. Ethylene was measured with a laser-based photoacoustic detector. First, experimental conditions were established with Columbia-0 (Col-0) accession, which was grown in vitro on horizontal plates across a range of five nitrate concentrations (0.5, 1, 2.5, 5, or 10 mM). The concentrations of 1 and 10 mM nitrate were retained for further characterization. Along with a decrease of total dry biomass and higher biomass allocation to the roots, the ethylene production was 50% more important at 1 mM than at 10 mM nitrate. The total transcript levels of 1-AMINOCYCLOPROPANE-1-CARBOXYLIC ACID SYNTHASES (ACS) in roots and those of ACC OXIDASES (ACO) in shoots increased by 100% between the same treatments. This was mainly due to higher transcript levels of ACS6 and of ACO2 and ACO4 respectively. The assumption was that during nitrogen deficiency, the greater biomass allocation in favor of the roots was controlled by ethylene being released in the shoots after conversion of ACC originating from the roots. Second, biomass and ethylene productions were measured in 20 additional accessions. Across all accessions, the total dry biomass and ethylene production were correlated negatively at 1 mM but positively at 10 mM nitrate. Furthermore, polymorphism was surveyed in ACC and ethylene biosynthesis genes and gene products among accessions. Very few substitutions modifying the amino acids properties in conserved motifs of the enzymes were found in the accessions. Natural variation of ethylene production could be further explored to improve Nitrogen Use Efficiency (NUE), in particular by manipulating features like the biomass production and the timing of senescence upon nitrogen limitation

Current advances in systems and integrative biology

Systems biology has gained a tremendous amount of interest in the last few years. This is partly due to the realization that traditional approaches focusing only on a few molecules at a time cannot describe the impact of aberrant or modulated molecular environments across a whole system. Furthermore, a hypothesis-driven study aims to prove or disprove its postulations, whereas a hypothesis-free systems approach can yield an unbiased and novel testable hypothesis as an end-result. This latter approach foregoes assumptions which predict how a biological system should react to an altered microenvironment within a cellular context, across a tissue or impacting on distant organs. Additionally, re-use of existing data by systematic data mining and re-stratification, one of the cornerstones of integrative systems biology, is also gaining attention. While tremendous efforts using a systems methodology have already yielded excellent results, it is apparent that a lack of suitable analytic tools and purpose-built databases poses a major bottleneck in applying a systematic workflow. This review addresses the current approaches used in systems analysis and obstacles often encountered in large-scale data analysis and integration which tend to go unnoticed, but have a direct impact on the final outcome of a systems approach. Its wide applicability, ranging from basic research, disease descriptors, pharmacological studies, to personalized medicine, makes this emerging approach well suited to address biological and medical questions where conventional methods are not ideal