Plant compartment and genetic variation drive microbiome composition in switchgrass roots.

Switchgrass (Panicum virgatum) is a promising biofuel crop native to the United States with genotypes that are adapted to a wide range of distinct ecosystems. Various plants have been shown to undergo symbioses with plant growth-promoting bacteria and fungi, however, plant-associated microbial communities of switchgrass have not been extensively studied to date. We present 16S ribosomal RNA gene and internal transcribed spacer (ITS) data of rhizosphere and root endosphere compartments of four switchgrass genotypes to test the hypothesis that host selection of its root microbiota prevails after transfer to non-native soil. We show that differences in bacterial, archaeal and fungal community composition and diversity are strongly driven by plant compartment and switchgrass genotypes and ecotypes. Plant-associated microbiota show an enrichment in Alphaproteobacteria and Actinobacteria as well as Sordariales and Pleosporales compared with the surrounding soil. Root associated compartments display low-complexity communities dominated and enriched in Actinobacteria, in particular Streptomyces, in the lowland genotypes, and in Alphaproteobacteria, specifically Sphingobium, in the upland genotypes. Our comprehensive root analysis serves as a snapshot of host-specific bacterial and fungal associations of switchgrass in the field and confirms that host-selected microbiomes persist after transfer to non-native soil

Evaluation of Cognitive Architectures for Cyber-Physical Production Systems

Cyber-physical production systems (CPPS) integrate physical and computational resources due to increasingly available sensors and processing power. This enables the usage of data, to create additional benefit, such as condition monitoring or optimization. These capabilities can lead to cognition, such that the system is able to adapt independently to changing circumstances by learning from additional sensors information. Developing a reference architecture for the design of CPPS and standardization of machines and software interfaces is crucial to enable compatibility of data usage between different machine models and vendors. This paper analysis existing reference architecture regarding their cognitive abilities, based on requirements that are derived from three different use cases. The results from the evaluation of the reference architectures, which include two instances that stem from the field of cognitive science, reveal a gap in the applicability of the architectures regarding the generalizability and the level of abstraction. While reference architectures from the field of automation are suitable to address use case specific requirements, and do not address the general requirements, especially w.r.t. adaptability, the examples from the field of cognitive science are well usable to reach a high level of adaption and cognition. It is desirable to merge advantages of both classes of architectures to address challenges in the field of CPPS in Industrie 4.0

Midlatitude ClO during the maximum atmospheric chlorine burden : in situ balloon measurements and model simulations

Chlorine monoxide (ClO) plays a key role in stratospheric ozone loss processes at midlatitudes. We present two balloonborne in situ measurements of ClO conducted in northern hemisphere midlatitudes during the period of the maximum of total inorganic chlorine loading in the atmosphere. Both ClO measurements were conducted on board the TRIPLE balloon payload, launched in November 1996 in Le´on, Spain, and in May 1999 in Aire sur l’Adour, France. For both flights a ClO daylight and night time vertical profile could be derived over an altitude range of approximately 15–31 km. ClO mixing ratios are compared to model simulations performed with the photochemical box model version of the Chemical Lagrangian Model of the Stratosphere (CLaMS). Simulations along 24-h backward trajectories were performed to study the diurnal variation of ClO in the midlatitude lower stratosphere. Model simulations for the flight launched in Aire sur l’Adour 1999 show a good agreement with the ClO measurements. For the flight launched in Le´on 1996, a similar good agreement is found, except at around ~ 650 K potential temperature (~26km altitude). However, a tendency is found that for solar zenith angles greater than 86°–87° the simulated ClO mixing ratios substantially overestimate measured ClO by approximately a factor of 2.5 or more for both flights. Therefore we conclude that no indication can be deduced from the presented ClO measurements that substantial uncertainties exist in midlatitude chlorine chemistry of the stratosphere. An exception is the situation at solar zenith angles greater than 86°–87° where model simulations substantial overestimate ClO observations

Impact of harvest on switchgrass leaf microbial communities

Switchgrass is a promising feedstock for biofuel production, with potential for leveraging its native microbial community to increase productivity and resilience to environmental stress. Here, we characterized the bacterial, archaeal and fungal diversity of the leaf microbial community associated with four switchgrass (Panicum virgatum) genotypes, subjected to two harvest treatments (annual harvest and unharvested control), and two fertilization levels (fertilized and unfertilized control), based on 16S rRNA gene and internal transcribed spacer (ITS) region amplicon sequencing. Leaf surface and leaf endosphere bacterial communities were significantly different with Alphaproteobacteria enriched in the leaf surface and Gammaproteobacteria and Bacilli enriched in the leaf endosphere. Harvest treatment significantly shifted presence/absence and abundances of bacterial and fungal leaf surface community members: Gammaproteobacteria were significantly enriched in harvested and Alphaproteobacteria were significantly enriched in unharvested leaf surface communities. These shifts were most prominent in the upland genotype DAC where the leaf surface showed the highest enrichment of Gammaproteobacteria, including taxa with 100% identity to those previously shown to have phytopathogenic function. Fertilization did not have any significant impact on bacterial or fungal communities. We also identified bacterial and fungal taxa present in both the leaf surface and leaf endosphere across all genotypes and treatments. These core taxa were dominated by Methylobacterium, Enterobacteriaceae, and Curtobacterium, in addition to Aureobasidium, Cladosporium, Alternaria and Dothideales. Local core leaf bacterial and fungal taxa represent promising targets for plant microbe engineering and manipulation across various genotypes and harvest treatments. Our study showcases, for the first time, the significant impact that harvest treatment can have on bacterial and fungal taxa inhabiting switchgrass leaves and the need to include this factor in future plant microbial community studies

Cognitive Capabilities for the CAAI in Cyber-Physical Production Systems

This paper presents the cognitive module of the cognitive architecture for artificial intelligence (CAAI) in cyber-physical production systems (CPPS). The goal of this architecture is to reduce the implementation effort of artificial intelligence (AI) algorithms in CPPS. Declarative user goals and the provided algorithm-knowledge base allow the dynamic pipeline orchestration and configuration. A big data platform (BDP) instantiates the pipelines and monitors the CPPS performance for further evaluation through the cognitive module. Thus, the cognitive module is able to select feasible and robust configurations for process pipelines in varying use cases. Furthermore, it automatically adapts the models and algorithms based on model quality and resource consumption. The cognitive module also instantiates additional pipelines to test algorithms from different classes. CAAI relies on well-defined interfaces to enable the integration of additional modules and reduce implementation effort. Finally, an implementation based on Docker, Kubernetes, and Kafka for the virtualization and orchestration of the individual modules and as messaging-technology for module communication is used to evaluate a real-world use case

Complete genome sequence of Parvibaculum lavamentivorans type strain (DS-1T)

Parvibaculum lavamentivorans DS-1T is the type species of the novel genus Parvibaculum in the novel family Rhodobiaceae (formerly Phyllobacteriaceae) of the order Rhizobiales of Alphaproteobacteria. Strain DS-1T is a non-pigmented, aerobic, heterotrophic bacterium and represents the first tier member of environmentally important bacterial communities that catalyze the complete degradation of synthetic laundry surfactants. Here we describe the features of this organism, together with the complete genome sequence and annotation. The 3,914,745 bp long genome with its predicted 3,654 protein coding genes is the first completed genome sequence of the genus Parvibaculum, and the first genome sequence of a representative of the family Rhodobiaceae