Seasonal and annual variability in the phytoplankton community of the Raunefjord,west coast of Norway from 2001–2006

Changes in phytoplankton community composition potentially affect the entire marine food web. Because of seasonal cycles and inter-annual variations in species composition, long-term monitoring, covering many sequential years, is required to establish a baseline study and to reveal long-term trends. The current study describes the phytoplankton biomass variations and species composition in relation to hydrographic and meteorological conditions in the Raunefjord, western Norway, over a 6-year period from 2001 to 2006. The extent of inflow or upwelling in the fjord varied from year to year and resulted in pronounced differences in water column stability. The annual phytoplankton community succession showed some repeated seasonal patterns, but also high variability between years. Two to four diatom blooms were observed per year, and the spring blooms occurring before water column stratification in March were dominated by Skeletonema marinoi and Chaetoceros socialis, and other Chaetoceros and Thalassiosira spp. Blooms of the haptophytes Phaeocystis pouchetii and Emiliania huxleyi were irregular and in some years totally absent. Although E. huxleyi was present all year round it appeared in bloom concentrations only in 2003, when the summer was warm and the water column characterized by high surface temperatures and pronounced stratification. The annual average abundance of both diatoms and flagellates increased during the six years. Despite the high variation from year to year, our investigation provides valuable knowledge about annual phytoplankton community patterns in the region, and can be used as a reference to detect possible future changes.     

“A cleaner break”: Genetic divergence between geographic groups and sympatric phenotypes revealed in ballan wrasse (Labrus bergylta)

Capture and long‐distance translocation of cleaner fish to control lice infestations on marine salmonid farms has the potential to influence wild populations via overexploitation in source regions, and introgression in recipient regions. Knowledge of population genetic structure is therefore required. We studied the genetic structure of ballan wrasse, a phenotypically diverse and extensively used cleaner fish, from 18 locations in Norway and Sweden, and from Galicia, Spain, using 82 SNP markers. We detected two very distinct genetic groups in Scandinavia, northwestern and southeastern. These groups were split by a stretch of sandy beaches in southwest Norway, representing a habitat discontinuity for this rocky shore associated benthic egg‐laying species. Wrasse from Galicia were highly differentiated from all Scandinavian locations, but more similar to northwestern than southeastern locations. Distinct genetic differences were observed between sympatric spotty and plain phenotypes in Galicia, but not in Scandinavia. The mechanisms underlying the geographic patterns between phenotypes are discussed, but not identified. We conclude that extensive aquaculture‐mediated translocation of ballan wrasse from Sweden and southern Norway to western and middle Norway has the potential to mix genetically distinct populations. These results question the sustainability of the current cleaner fish practice.     

A comparison of performance of WP2 and MOCNESS

Zooplankton biomass in the Barents Sea was monitored during1988–97 using WP2 and MOCNESS plankton nets. These twosampling gears differ in their size and mode of operation. Theplankton samples were size fractionated into three categoriesand the dry weight per square metre was calculated. The smallestand the medium size fractions (< 2000 µm) representedmainly copepods, and the larger size fraction (> 2000 µm)consisted mainly of macrozooplankton such as krill and amphipods.WP2 biomass values were higher for the smallest size fraction,whereas the MOCNESS tended to give higher values for the largestsize fraction However, the total amount of zooplankton biomass(g m^–1) obtained by these two methods was not significantlydifferent.     

Bottom up proteomics data analysis strategies to explore protein modifications and genomic variants

The quest to understand biological systems requires further attention of the scientific community to the challenges faced in proteomics. In fact the complexity of the proteome reaches uncountable orders of magnitude. This means that significant technical and data‐analytic innovations will be needed for the full understanding of biology. Current state of art MS is probably our best choice for studying protein complexity and exploring new ways to use MS and MS derived data should be given higher priority. We present here a brief overview of visualization and statistical analysis strategies for quantitative peptide values on an individual protein basis. These analysis strategies can help pinpoint protein modifications, splice, and genomic variants of biological relevance. We demonstrate the application of these data analysis strategies using a bottom‐up proteomics dataset obtained in a drug profiling experiment. Furthermore, we have also observed that the presented methods are useful for studying peptide distributions from clinical samples from a large number of individuals. We expect that the presented data analysis strategy will be useful in the future to define functional protein variants in biological model systems and disease studies. Therefore robust software implementing these strategies is urgently needed.     

Quantitative proteomics suggests decrease in the secretogranin‐1 cerebrospinal fluid levels during the disease course of multiple sclerosis

Multiple sclerosis (MS) is a chronic inflammatory disease of the CNS with unknown cause. Proteins with different abundance in the cerebrospinal fluid (CSF) from relapsing‐remitting MS (RRMS) patients and neurological controls could give novel insight to the MS pathogenesis and be used to improve diagnosis, predict prognosis and disease course, and guide in therapy decisions. We combined iTRAQ labeling and Orbitrap mass spectrometry to discover proteins with different CSF abundance between six RRMS patients and 18 neurological disease controls. From 777 quantified proteins seven were selected as biomarker candidates, namely chitinase‐3‐like protein 1, secretogranin‐1 (Sg1), cerebellin‐1, neuroserpin, cell surface glycoprotein MUC18, testican‐2 and glutamate receptor 4. An independent sample set of 13 early‐MS patients, 13 RRMS patients and 13 neurological controls was used in a multiple reaction monitoring verification study. We found the intracellular calcium binding protein Sg1 to be increased in early‐MS patients compared to RRMS and neurological controls. Sg1 should be included in further studies to elucidate its role in the early phases of MS pathogenesis and its potential as a biomarker for this disease.     

Molecular Subtypes in Stage II-III Colon Cancer Defined by Genomic Instability: Early Recurrence-Risk Associated with a High Copy-Number Variation and Loss of RUNX3 and CDKN2A

Objective

We sought to investigate various molecular subtypes defined by genomic instability that may be related to early death and recurrence in colon cancer.

Methods

We sought to investigate various molecular subtypes defined by instability at microsatellites (MSI), changes in methylation patterns (CpG island methylator phenotype, CIMP) or copy number variation (CNV) in 8 genes. Stage II-III colon cancers (n = 64) were investigated by methylation-specific multiplex ligated probe amplification (MS-MLPA). Correlation of CNV, CIMP and MSI, with mutations in KRAS and BRAFV600E were assessed for overlap in molecular subtypes and early recurrence risk by uni- and multivariate regression.

Results

The CIMP phenotype occurred in 34% (22/64) and MSI in 27% (16/60) of the tumors, with noted CIMP/MSI overlap. Among the molecular subtypes, a high CNV phenotype had an associated odds ratio (OR) for recurrence of 3.2 (95% CI 1.1-9.3; P = 0.026). Losses of CACNA1G (OR of 2.9, 95% CI 1.4-6.0; P = 0.001), IGF2 (OR of 4.3, 95% CI 1.1-15.8; P = 0.007), CDKN2A (p16) (OR of 2.0, 95% CI 1.1-3.6; P = 0.024), and RUNX3 (OR of 3.4, 95% CI 1.3-8.7; P = 0.002) were associated with early recurrence, while MSI, CIMP, KRAS or BRAF V600E mutations were not. The CNV was significantly higher in deceased patients (CNV in 6 of 8) compared to survivors (CNV in 3 of 8). Only stage and loss of RUNX3 and CDKN2A were significant in the multivariable risk-model for early recurrence.

Conclusions

A high copy number variation phenotype is a strong predictor of early recurrence and death, and may indicate a dose-dependent relationship between genetic instability and outcome. Loss of tumor suppressors RUNX3 and CDKN2A were related to recurrence-risk and warrants further investigation.     

Temporal variation of Bistorta vivipara‐associated ectomycorrhizal fungal communities in the High Arctic

Ectomycorrhizal (ECM) fungi are important for efficient nutrient uptake of several widespread arctic plant species. Knowledge of temporal variation of ECM fungi, and the relationship of these patterns to environmental variables, is essential to understand energy and nutrient cycling in Arctic ecosystems. We sampled roots of Bistorta vivipara ten times over two years; three times during the growing‐season (June, July and September) and twice during winter (November and April) of both years. We found 668 ECM OTUs belonging to 25 different ECM lineages, whereof 157 OTUs persisted throughout all sampling time‐points. Overall, ECM fungal richness peaked in winter and species belonging to Cortinarius, Serendipita and Sebacina were more frequent in winter than during summer. Structure of ECM fungal communities was primarily affected by spatial factors. However, after accounting for spatial effects, significant seasonal variation was evident revealing correspondence with seasonal changes in environmental conditions. We demonstrate that arctic ECM richness and community structure differ between summer (growing‐season) and winter, possibly due to reduced activity of the core community, and addition of fungi adapted for winter conditions forming a winter‐active fungal community. Significant month × year interactions were observed both for fungal richness and community composition, indicating unpredictable between‐year variation. Our study indicates that addressing seasonal changes requires replication over several years.