Predicting plankton net community production in the Atlantic Ocean

We present, test and implement two contrasting models to predict euphotic zone net community production (NCP), which are based on 14C primary production (PO14CP) to NCP relationships over two latitudinal (ca. 30°S–45°N) transects traversing highly productive and oligotrophic provinces of the Atlantic Ocean (NADR, CNRY, BENG, NAST-E, ETRA and SATL, Longhurst et al., 1995 [An estimation of global primary production in the ocean from satellite radiometer data. Journal of Plankton Research 17, 1245–1271]). The two models include similar ranges of PO14CP and community structure, but differ in the relative influence of allochthonous organic matter in the oligotrophic provinces. Both models were used to predict NCP from PO14CP measurements obtained during 11 local and three seasonal studies in the Atlantic, Pacific and Indian Oceans, and from satellite-derived estimates of PO14CP. Comparison of these NCP predictions with concurrent in situ measurements and geochemical estimates of NCP showed that geographic and annual patterns of NCP can only be predicted when the relative trophic importance of local vs. distant processes is similar in both modeled and predicted ecosystems. The system-dependent ability of our models to predict NCP seasonality suggests that trophic-level dynamics are stronger than differences in hydrodynamic regime, taxonomic composition and phytoplankton growth. The regional differences in the predictive power of both models confirm the existence of biogeographic differences in the scale of trophic dynamics, which impede the use of a single generalized equation to estimate global marine plankton NCP. This paper shows the potential of a systematic empirical approach to predict plankton NCP from local and satellite-derived P estimates

Human Galectins Induce Conversion of Dermal Fibroblasts into Myofibroblasts and Production of Extracellular Matrix: Potential Application in Tissue Engineering and Wound Repair

Members of the galectin family of endogenous lectins are potent adhesion/growth-regulatory effectors. Their multi-functionality opens possibilities for their use in bioapplications. We studied whether human galectins induce the conversion of human dermal fibroblasts into myofibroblasts (MFBs) and the production of a bioactive extracellular matrix scaffold is suitable for cell culture. Testing a panel of galectins of all three subgroups, including natural and engineered variants, we detected activity for the proto-type galectin-1 and galectin-7, the chimera-type galectin-3 and the tandem-repeat-type galectin-4. The activity of galectin-1 required the integrity of the carbohydrate recognition domain. It was independent of the presence of TGF-beta 1, but it yielded an additive effect. The resulting MFBs, relevant, for example, for tumor progression, generated a matrix scaffold rich in fibronectin and galectin-1 that supported keratinocyte culture without feeder cells. Of note, keratinocytes cultured on this substratum presented a stem-like cell phenotype with small size and keratin-19 expression. In vivo in rats, galectin-1 had a positive effect on skin wound closure 21 days after surgery. In conclusion, we describe the differential potential of certain human galectins to induce the conversion of dermal fibroblasts into MFBs and the generation of a bioactive cell culture substratum. Copyright (C) 2011 S. Karger AG, Base

Molecular Pathogenesis of Post-Transplant Acute Kidney Injury: Assessment of Whole-Genome mRNA and MiRNA Profiles.

Acute kidney injury (AKI) affects roughly 25% of all recipients of deceased donor organs. The prevention of post-transplant AKI is still an unmet clinical need. We prospectively collected zero-hour, indication as well as protocol kidney biopsies from 166 allografts between 2011 and 2013. In this cohort eight cases with AKI and ten matched allografts without pathology serving as control group were identified with a follow-up biopsy within the first twelve days after engraftment. For this set the zero-hour and follow-up biopsies were subjected to genome wide microRNA and mRNA profiling and analysis, followed by validation in independent expression profiles of 42 AKI and 21 protocol biopsies for strictly controlling the false discovery rate. Follow-up biopsies of AKI allografts compared to time-matched protocol biopsies, further baseline adjustment for zero-hour biopsy expression level and validation in independent datasets, revealed a molecular AKI signature holding 20 mRNAs and two miRNAs (miR-182-5p and miR-21-3p). Next to several established biomarkers such as lipocalin-2 also novel candidates of interest were identified in the signature. In further experimental evaluation the elevated transcript expression level of the secretory leukocyte peptidase inhibitor (SLPI) in AKI allografts was confirmed in plasma and urine on the protein level (p<0.001 and p = 0.003, respectively). miR-182-5p was identified as a molecular regulator of post-transplant AKI, strongly correlated with global gene expression changes during AKI. In summary, we identified an AKI-specific molecular signature providing the ground for novel biomarkers and target candidates such as SLPI and miR-182-5p in addressing AKI

Modularization of biochemical networks based on classification of Petri net t-invariants

<p>Abstract</p> <p>Background</p> <p>Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.</p> <p>With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system.</p> <p>Methods</p> <p>Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied.</p> <p>Results</p> <p>We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in <it>Saccharomyces cerevisiae</it>) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability.</p> <p>Conclusion</p> <p>We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis.</p

Forest-Stream Linkages: Effects of Terrestrial Invertebrate Input and Light on Diet and Growth of Brown Trout (Salmo trutta) in a Boreal Forest Stream

Subsidies of energy and material from the riparian zone have large impacts on recipient stream habitats. Human-induced changes, such as deforestation, may profoundly affect these pathways. However, the strength of individual factors on stream ecosystems is poorly understood since the factors involved often interact in complex ways. We isolated two of these factors, manipulating the flux of terrestrial input and the intensity of light in a 2×2 factorial design, where we followed the growth and diet of two size-classes of brown trout (Salmo trutta) and the development of periphyton, grazer macroinvertebrates, terrestrial invertebrate inputs, and drift in twelve 20 m long enclosed stream reaches in a five-month-long experiment in a boreal coniferous forest stream. We found that light intensity, which was artificially increased 2.5 times above ambient levels, had an effect on grazer density, but no detectable effect on chlorophyll a biomass. We also found a seasonal effect on the amount of drift and that the reduction of terrestrial prey input, accomplished by covering enclosures with transparent plastic, had a negative impact on the amount of terrestrial invertebrates in the drift. Further, trout growth was strongly seasonal and followed the same pattern as drift biomass, and the reduction of terrestrial prey input had a negative effect on trout growth. Diet analysis was consistent with growth differences, showing that trout in open enclosures consumed relatively more terrestrial prey in summer than trout living in covered enclosures. We also predicted ontogenetic differences in the diet and growth of old and young trout, where we expected old fish to be more affected by the terrestrial prey reduction, but we found little evidence of ontogenetic differences. Overall, our results showed that reduced terrestrial prey inputs, as would be expected from forest harvesting, shaped differences in the growth and diet of the top predator, brown trout

X-linked primary ciliary dyskinesia due to mutations in the cytoplasmic axonemal dynein assembly factor PIH1D3

By moving essential body fluids and molecules, motile cilia and flagella govern respiratory mucociliary clearance, laterality determination and the transport of gametes and cerebrospinal fluid. Primary ciliary dyskinesia (PCD) is an autosomal recessive disorder frequently caused by non-assembly of dynein arm motors into cilia and flagella axonemes. Before their import into cilia and flagella, multi-subunit axonemal dynein arms are thought to be stabilized and pre-assembled in the cytoplasm through a DNAAF2–DNAAF4–HSP90 complex akin to the HSP90 co-chaperone R2TP complex. Here, we demonstrate that large genomic deletions as well as point mutations involving PIH1D3 are responsible for an X-linked form of PCD causing disruption of early axonemal dynein assembly. We propose that PIH1D3, a protein that emerges as a new player of the cytoplasmic pre-assembly pathway, is part of a complementary conserved R2TP-like HSP90 co-chaperone complex, the loss of which affects assembly of a subset of inner arm dyneins

Cold and dry winter conditions are associated with greater SARS-CoV-2 transmission at regional level in western countries during the first epidemic wave

International audienceHigher transmissibility of SARS-CoV-2 in cold and dry weather conditions has been hypothesized since the onset of the COVID-19 pandemic but the level of epidemiological evidence remains low. During the first wave of the pandemic, Spain, Italy, France, Portugal, Canada and USA presented an early spread, a heavy COVID-19 burden, and low initial public health response until lockdowns. In a context when testing was limited, we calculated the basic reproduction number (R 0) in 63 regions from the growth in regional death counts. After adjusting for population density, early spread of the epidemic, and age structure, temperature and humidity were negatively associated with SARS-CoV-2 transmissibility. A reduction of mean absolute humidity by 1 g/m 3 was associated with a 0.15-unit increase of R 0. Below 10 °C, a temperature reduction of 1 °C was associated with a 0.16-unit increase of R 0. Our results confirm a dependency of SARS-CoV-2 transmissibility to weather conditions in the absence of control measures during the first wave. The transition from summer to winter, corresponding to drop in temperature associated with an overall decrease in absolute humidity, likely contributed to the intensification of the second wave in northwest hemisphere countries. Non-pharmaceutical interventions must be adjusted to account for increased transmissibility in winter conditions