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Sequencing databases contain enormous amounts of functional genomics data, making them an extensive resource for genome-scale analysis. Reanalyzing publicly available data, and integrating it with new, project-specific data sets, can be invaluable. With current technologies, genomic experiments have become feasible for virtually any species of interest. However, using and integrating this data comes with its challenges, such as standardized and reproducible analysis. Seq2science is a multi-purpose workflow that covers preprocessing, quality control, visualization, and analysis of functional genomics sequencing data. It facilitates the downloading of sequencing data from all major databases, including NCBI SRA, EBI ENA, DDBJ, GSA, and ENCODE. Furthermore, it automates the retrieval of any genome assembly available from Ensembl, NCBI, and UCSC. It has been tested on a variety of species, and includes diverse workflows such as ATAC-, RNA-, and ChIP-seq. It consists of both generic as well as advanced steps, such as differential gene expression or peak accessibility analysis and differential motif analysis. Seq2science is built on the Snakemake workflow language and thus can be run on a range of computing infrastructures. It is available at https://github.com/vanheeringen-lab/seq2science.

Solid-state fermentation is widely used in traditional food production, but most of the complex processes involved were designed and are carried out without a scientific basis. Often, mathematical models can be established to describe mass and heat transfer with the assistance of chemical engineering tools. However, due to the complex nature of solid-state fermentation, mathematical models alone cannot explain the many dynamic changes that occur during these processes. For example, it is hard to identify the most important variables influencing product yield and quality fluctuations. Here, using solid-state fermentation of Chinese liquor as a case study, we established statistical models to correlate the final liquor yield with available industrial data, including the starting content of starch, water and acid; starting temperature; and substrate temperature profiles throughout the process. Models based on starting concentrations and temperature profiles gave unsatisfactory yield predictions. Although the most obvious factor is the starting month, ambient temperature is unlikely to be the direct driver of differences. A lactic-acid-inhibition model indicates that lactic acid from lactic acid bacteria is likely the reason for the reduction in yield between April and December. Further integrated study strategies are necessary to confirm the most crucial variables from both microbiological and engineering perspectives. Our findings can facilitate better understanding and improvement of complex solid-state fermentations.

Objectives It is well-known that long-term osteoarthritis prognosis is not improved by corticosteroid treatments. Here we investigate what could underlie this phenomenon by measuring the short term corticosteroid response of osteoarthritic joint synovial macrophages (OA-Mf). Methods We determined the genome-wide transcriptomic response to corticosteroids of end-stage OA-Mf. This was compared with lipopolysaccharide-tolerized and β-glucan-trained circulating blood monocyte-derived macrophage models. Results Upon corticosteroid stimulation, the trained and tolerized macrophages significantly altered the abundance of 201 and 257 RNA transcripts, respectively. By contrast, by the same criteria, OA-Mf had a very restricted corticosteroid response of only 12 RNA transcripts. Furthermore, while metalloproteinases 1, 2, 3 and 10 expression clearly distinguish OA-Mf from both the tolerized and trained macrophage models, OA-Mf IL-1, chemokine (CXCL) and cytokine (CCL) family member profiles resembled the tolerized macrophage model, with the exception that OA-Mf showed high levels of CCL20. Conclusion Terminal osteoarthritis joints harbour macrophages with an inflammatory state that closely resembles the tolerized macrophage state, and this is compounded by a weak corticosteroid response capacity that may explain the lack of positive long-term effects of corticosteroid treatment for osteoarthritis patients. [ABSTRACT FROM AUTHOR]

Abstract Carcass decomposition largely depends on vertebrate scavengers. However, how behavioral differences between vertebrate scavenger species, the dominance of certain species, and the diversity of the vertebrate scavenger community affect the speed of carcass decomposition is poorly understood. As scavenging is an overlooked trophic interaction, studying the different functional roles of vertebrate species in the scavenging process increases our understanding about the effect of the vertebrate scavenger community on carcass decomposition. We used motion‐triggered infrared camera trap footages to profile the behavior and activity of vertebrate scavengers visiting carcasses in Dutch nature areas. We grouped vertebrate scavengers with similar functional roles. We found a clear distinction between occasional scavengers and more specialized scavengers, and we found wild boar (Sus scrofa) to be the dominant scavenger species in our study system. We showed that these groups are functionally different within the scavenger community. We found that overall vertebrate scavenger diversity was positively correlated with carcass decomposition speed. With these findings, our study contributes to the understanding about the different functional roles scavengers can have in ecological communities.

Dispersal is an essential component of plant life, especially under the current threats of anthropogenic habitat fragmentation and climate change. For many wetland species, water is a key dispersal vector, as it can presumably disperse seeds long distances and towards suitable sites for establishment. Seed dispersal distance is affected by stream characteristics and seed traits. Yet, the effect of relevant seed traits, such as size, remains largely unknown.Here, we report on an experimental field study examining the effect of seed size on dispersal distance in lowland streams. We released cork seed mimics of different sizes in four Dutch lowland streams in restored and channelized sections. After 24 hr, we recorded their entrapment location, entrapment mechanism, and the vegetation type in which they were caught.Large seeds generally dispersed over longer distances than smaller seeds. This effect of seed size is likely caused by the different entrapment mechanisms—net trapping, surface tension, and wake trapping—which were highly correlated with seed size. Especially net trapping was responsible for the capture of a large proportion of small seed mimics in vegetation such as aquatic and riparian grasses, starwort, and reed. Due to the prevalent occurrence of these vegetation types in lowland streams, particularly during summer, smaller seeds are more likely to become entrapped and, hence, disperse less far. Our analysis on existing seed data reveals that water‐dispersed riparian plants have relatively large seeds and are thereby evolutionarily adapted to long‐distance dispersal. Furthermore, our results indicate that median dispersal distances are 0.02–1.8 km (99‐percentile <8.5 km) in lowland streams in summer. In winter, less vegetation is present in and surrounding the streams, which leads to median dispersal distances of 0.12–14.2 km (99‐percentile <65 km).Synthesis. This study demonstrates that (a) large seeds generally disperse further than smaller seeds in lowland steams and (b) distances depend strongly on stream vegetation. This information should inform future restoration, for instance, by planning efforts to coincide with times or conditions of open water which are more favourable for the dispersal of target plant species—especially those with small seeds (<10 mm). This study demonstrates that (a) large seeds generally disperse further than smaller seeds in lowland steams and (b) distances depend strongly on stream vegetation. This information should inform future restoration, for instance, by planning efforts to coincide with times or conditions of open water which are more favourable for the dispersal of target plant species—especially those with small seeds (<10 mm). [ABSTRACT FROM AUTHOR]

The loss of carbon dioxide (CO 2 ) to the environment during microalgae cultivation is undesirable for both environmental and economic reasons. In this study, a phototrophic biofilm growth model was developed and validated with the objective to maximize both CO 2 utilization efficiency and production of microalgae in biofilms. The model was validated in growth experiments with CO 2 as the limiting substrate. The CO 2 utilization and biomass productivity were maximized by changing the gas flow rate, the number of biofilm reactors in series and gas composition. Based on simulations, the maximum CO 2 utilization efficiency that was reached was 96% based on a process employing flue gas. The corresponding drop in productivity was only 2% in comparison to the non-CO 2 limited reference situation. In order to achieve this, 25 biofilm reactors units, or more, must be operated in series. Based on these results, it was concluded that concentrated CO 2 streams and plug flow behavior of the gaseous phase over the biofilm surface are essential for high productivity and CO 2 utilization efficiency. Biotechnol. Bioeng. 2017;114: 769-776. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)