Developmental structuring of phenotypic variation: A case study with a cellular automata model of ontogeny

Developmental mechanisms not only produce an organismal phenotype, but they also structure the way genetic variation maps to phenotypic variation. Here, we revisit a computational model for the evolution of ontogeny based on cellular automata, in which evolution regularly discovered two alternative mechanisms for achieving a selected phenotype, one showing high modularity, the other showing morphological integration. We measure a primary variational property of the systems, their distribution of fitness effects of mutation. We find that the modular ontogeny shows the evolution of mutational robustness and ontogenic simplification, while the integrated ontogeny does not. We discuss the wider use of this methodology on other computational models of development as well as real organisms.     

Soil fauna diversity increases CO2 but suppresses N2O emissions from soil

Soil faunal activity can be a major control of greenhouse gas (GHG) emissions from soil. Effects of single faunal species, genera or families have been investigated, but it is unknown how soil fauna diversity may influence emissions of both carbon dioxide (CO₂, end product of decomposition of organic matter) and nitrous oxide (N₂O, an intermediate product of N transformation processes, in particular denitrification). Here, we studied how CO₂ and N₂O emissions are affected by species and species mixtures of up to eight species of detritivorous/fungivorous soil fauna from four different taxonomic groups (earthworms, potworms, mites, springtails) using a microcosm set‐up. We found that higher species richness and increased functional dissimilarity of species mixtures led to increased faunal‐induced CO₂ emission (up to 10%), but decreased N₂O emission (up to 62%). Large ecosystem engineers such as earthworms were key drivers of both CO₂ and N₂O emissions. Interestingly, increased biodiversity of other soil fauna in the presence of earthworms decreased faunal‐induced N₂O emission despite enhanced C cycling. We conclude that higher soil fauna functional diversity enhanced the intensity of belowground processes, leading to more complete litter decomposition and increased CO₂ emission, but concurrently also resulting in more complete denitrification and reduced N₂O emission. Our results suggest that increased soil fauna species diversity has the potential to mitigate emissions of N₂O from soil ecosystems. Given the loss of soil biodiversity in managed soils, our findings call for adoption of management practices that enhance soil biodiversity and stimulate a functionally diverse faunal community to reduce N₂O emissions from managed soils.     

Cholesterol accumulation caused by low density lipoprotein receptor deficiency or a cholesterol-rich diet results in ectopic bone formation during experimental osteoarthritis

Introduction

Osteoarthritis (OA) is associated with the metabolic syndrome, however the underlying mechanisms remain unclear. We investigated whether low density lipoprotein (LDL) accumulation leads to increased LDL uptake by synovial macrophages and affects synovial activation, cartilage destruction and enthesophyte/osteophyte formation during experimental OA in mice.

Methods

LDL receptor deficient (LDLr^−/−) mice and wild type (WT) controls received a cholesterol-rich or control diet for 120 days. Experimental OA was induced by intra-articular injection of collagenase twelve weeks after start of the diet. OA knee joints and synovial wash-outs were analyzed for OA-related changes. Murine bone marrow derived macrophages were stimulated with oxidized LDL (oxLDL), whereupon growth factor presence and gene expression were analyzed.

Results

A cholesterol-rich diet increased apolipoprotein B (ApoB) accumulation in synovial macrophages. Although increased LDL levels did not enhance thickening of the synovial lining, S100A8 expression within macrophages was increased in WT mice after receiving a cholesterol-rich diet, reflecting an elevated activation status. Both a cholesterol-rich diet and LDLr deficiency had no effect on cartilage damage; in contrast, ectopic bone formation was increased within joint ligaments (fold increase 6.7 and 6.1, respectively). Moreover, increased osteophyte size was found at the margins of the tibial plateau (4.4 fold increase after a cholesterol-rich diet and 5.3 fold increase in LDLr^−/− mice). Synovial wash-outs of LDLr^−/− mice and supernatants of macrophages stimulated with oxLDL led to increased transforming growth factor-beta (TGF-β) signaling compared to controls.

Conclusions

LDL accumulation within synovial lining cells leads to increased activation of synovium and osteophyte formation in experimental OA. OxLDL uptake by macrophages activates growth factors of the TGF-superfamily.     

Oestrogenic activity of CPRG (chlorophenol red-β-D-galactopyranoside), a β-galactosidase substrate commonly used in recombinant yeast oestrogenic assays

The finding that a variety of chemicals display oestrogenic activity has resulted in the development of in vitro and in vivo assays to assess oestrogenic activity. One such assay, the yeast oestrogen assay (YES) makes use of recombinant yeast cells that harbour an oestrogen receptor expression cassette and a reporter construct, coding for bgalactosidase. The induction mechanism starts with the binding of oestrogenic compounds to the oestrogen receptor. This complex activates the production of β-galactosidase. The β-galactosidase activity is thus a measure of the oestrogenic activity of chemical compounds. In the YES assay, the β-galactosidase activity may be quantified with the chromogenic substrate chlorophenol red-β-d-galactopyranoside (CPRG). In the present study it is reported that CPRG or its β-galactosidase degradation product chlorophenol red act in the YES as an oestrogenic compound itself. The implications of this finding are described. It is especially argued that chlorophenol red production after prolonged incubation of the assay might be misinterpreted as an oestrogenic effect of the test compound.     

A Model for the Early Identification of Sources of Airborne Pathogens in an Outdoor Environment

Background

Source identification in areas with outbreaks of airborne pathogens is often time-consuming and expensive. We developed a model to identify the most likely location of sources of airborne pathogens.

Methods

As a case study, we retrospectively analyzed three Q fever outbreaks in the Netherlands in 2009, each with suspected exposure from a single large dairy goat farm. Model input consisted only of case residential addresses, day of first clinical symptoms, and human population density data. We defined a spatial grid and fitted an exponentially declining function to the incidence-distance data of each grid point. For any grid point with a fit significant at the 95% confidence level, we calculated a measure of risk. For validation, we used results from abortion notifications, voluntary (2008) and mandatory (2009) bulk tank milk sampling at large (i.e. >50 goats and/or sheep) dairy farms, and non-systematic vaginal swab sampling at large and small dairy and non-dairy goat/sheep farms. In addition, we performed a two-source simulation study.

Results

Hotspots – areas most likely to contain the actual source – were identified at early outbreak stages, based on the earliest 2–10% of the case notifications. Distances between the hotspots and suspected goat farms varied from 300–1500 m. In regional likelihood rankings including all large dairy farms, the suspected goat farms consistently ranked first. The two-source simulation study showed that detection of sources is most clear if the distance between the sources is either relatively small or relatively large.

Conclusions

Our model identifies the most likely location of sources in an airborne pathogen outbreak area, even at early stages. It can help to reduce the number of potential sources to be investigated by microbial testing and to allow rapid implementation of interventions to limit the number of human infections and to reduce the risk of source-to-source transmission.     

Serum proteomics in amnestic mild cognitive impairment

We have explored proteins related to mild cognitive impairment (MCI). The serum proteome of 35 amnestic MCI patients and 35 cognitively healthy persons was investigated by LC MS. We identified 108 differentially expressed peptides between MCI patients and controls, belonging to 39 proteins. Eight proteins were selected for further investigation by quantitative protein measurements using a MRM assay; apolipoprotein E, carboxypeptidase N subunit 2, complement factor B (CFAB), galectin‐3 binding protein (LG3BP), lumican, serum amyloid A‐4 protein (SAA4), serum amyloid P‐component, and sex hormone binding globulin. Results of the quantitative protein measurements showed significantly decreased levels of carboxypeptidase N subunit 2, CFAB, LG3BP, SAA4, and serum amyloid P‐component in serum from amnestic MCI patients compared with cognitive healthy controls (two‐sided t‐test; p < 0.05). Apolipoprotein E and lumican showed no significant difference in protein levels, sex hormone binding globulin could not be quantified since the MRM assay did not reach the required sensitivity. A model based on the three most significantly decreased proteins (CFAB, LG3BP, and SAA4) showed a sensitivity and specificity of 73 and 66%, respectively, for the initial sample set. A small external validation set yielded 77% sensitivity and 75% specificity.