ALBERT

Description: Lactobacillus kunkeei is the most abundant bacterial species in the honey crop and food products of honeybees. The 16 S rRNA genes of strains isolated from different bee species are nearly identical in sequence and therefore inadequate as markers for studies of coevolutionary patterns. Here, we have compared the 1.5 Mb genomes of ten L. kunkeei strains isolated from all recognized Apis species and another two strains from Meliponini species. A gene flux analysis, including previously sequenced Lactobacillus species as outgroups, indicated the influence of reductive evolution. The genome architecture is unique in that vertically inherited core genes are located near the terminus of replication, whereas genes for secreted proteins and putative host-adaptive traits are located near the origin of replication. We suggest that these features have resulted from a genome-wide loss of genes, with integrations of novel genes mostly occurring in regions flanking the origin of replication. The phylogenetic analyses showed that the bacterial topology was incongruent with the host topology, and that strains of the same microcluster have recombined frequently across the host species barriers, arguing against codiversification. Multiple genotypes were recovered in the individual hosts and transfers of mobile elements could be demonstrated for strains isolated from the same host species. Unlike other bacteria with small genomes, short generation times and multiple rRNA operons suggest that L. kunkeei evolves under selection for rapid growth in its natural growth habitat. The results provide an extended framework for reductive genome evolution and functional genome organization in bacteria.

Description: Discoba (Excavata) is an ancient group of eukaryotes with great morphological and ecological diversity. Unlike the other major divisions of Discoba (Jakobida and Euglenozoa), little is known about the mitochondrial DNAs (mtDNAs) of Heterolobosea. We have assembled a complete mtDNA genome from the aggregating heterolobosean amoeba, Acrasis kona , which consists of a single circular highly AT-rich (83.3%) molecule of 51.5 kb. Unexpectedly, A. kona mtDNA is missing roughly 40% of the protein-coding genes and nearly half of the transfer RNAs found in the only other sequenced heterolobosean mtDNAs, those of Naegleria spp. Instead, over a quarter of A. kona mtDNA consists of novel open reading frames. Eleven of the 16 protein-coding genes missing from A. kona mtDNA were identified in its nuclear DNA and polyA RNA, and phylogenetic analyses indicate that at least 10 of these 11 putative nuclear-encoded mitochondrial (NcMt) proteins arose by direct transfer from the mitochondrion. Acrasis kona mtDNA also employs C-to-U type RNA editing, and 12 homologs of DYW-type pentatricopeptide repeat (PPR) proteins implicated in plant organellar RNA editing are found in A. kona nuclear DNA. A mapping of mitochondrial gene content onto a consensus phylogeny reveals a sporadic pattern of relative stasis and rampant gene loss in Discoba. Rampant loss occurred independently in the unique common lineage leading to Heterolobosea + Tsukubamonadida and later in the unique lineage leading to Acrasis. Meanwhile, mtDNA gene content appears to be remarkably stable in the Acrasis sister lineage leading to Naegleria and in their distant relatives Jakobida .

Description: This paper describes the pre-operational analysis and forecasting system developed during MACC (Monitoring Atmospheric Composition and Climate) and continued in the MACC-II (Monitoring Atmospheric Composition and Climate: Interim Implementation) European projects to provide air quality services for the European continent. This system is based on seven state-of-the art models developed and run in Europe (CHIMERE, EMEP, EURAD-IM, LOTOS-EUROS, MATCH, MOCAGE and SILAM). These models are used to calculate multi-model ensemble products. The paper gives an overall picture of its status at the end of MACC-II (summer 2014) and analyses the performance of the multi-model ensemble. The MACC-II system provides daily 96 h forecasts with hourly outputs of 10 chemical species/aerosols (O3, NO2, SO2, CO, PM10, PM2.5, NO, NH3, total NMVOCs (non-methane volatile organic compounds) and PAN+PAN precursors) over eight vertical levels from the surface to 5 km height. The hourly analysis at the surface is done a posteriori for the past day using a selection of representative air quality data from European monitoring stations. The performance of the system is assessed daily, weekly and every 3 months (seasonally) through statistical indicators calculated using the available representative air quality data from European monitoring stations. Results for a case study show the ability of the ensemble median to forecast regional ozone pollution events. The seasonal performances of the individual models and of the multi-model ensemble have been monitored since September 2009 for ozone, NO2 and PM10. The statistical indicators for ozone in summer 2014 show that the ensemble median gives on average the best performances compared to the seven models. There is very little degradation of the scores with the forecast day but there is a marked diurnal cycle, similarly to the individual models, that can be related partly to the prescribed diurnal variations of anthropogenic emissions in the models. During summer 2014, the diurnal ozone maximum is underestimated by the ensemble median by about 4 μg m−3 on average. Locally, during the studied ozone episodes, the maxima from the ensemble median are often lower than observations by 30–50 μg m−3. Overall, ozone scores are generally good with average values for the normalised indicators of 0.14 for the modified normalised mean bias and of 0.30 for the fractional gross error. Tests have also shown that the ensemble median is robust to reduction of ensemble size by one, that is, if predictions are unavailable from one model. Scores are also discussed for PM10 for winter 2013–1014. There is an underestimation of most models leading the ensemble median to a mean bias of −4.5 μg m−3. The ensemble median fractional gross error is larger for PM10 (~ 0.52) than for ozone and the correlation is lower (~ 0.35 for PM10 and ~ 0.54 for ozone). This is related to a larger spread of the seven model scores for PM10 than for ozone linked to different levels of complexity of aerosol representation in the individual models. In parallel, a scientific analysis of the results of the seven models and of the ensemble is also done over the Mediterranean area because of the specificity of its meteorology and emissions. The system is robust in terms of the production availability. Major efforts have been done in MACC-II towards the operationalisation of all its components. Foreseen developments and research for improving its performances are discussed in the conclusion.