35 Matching Annotations
  1. Jul 2020
  2. Jun 2020
  3. May 2020
  4. Apr 2020
    1. In the biosensor, the promoter regions of lasI, rhlI, pqsA, and ambB (QS genes) controlled the fluorescent reporter genes of Turbo YFP, mTag BFP2, mNEON Green, and E2-Orange
  5. Nov 2019
    1. It is challenging to study how pneumococci control virulence factor expression, because cues of natural environments and the presence of an immune system are difficult to simulate in vitro
  6. Oct 2019
    1. observations are consistent with a previous report showing that AHLs preferentially partition to the biofilm, reaching concentrations 600-fold in excess of the signal concentration in the surrounding bulk liquid medium
    1. Many QS-controlled genes relate to biofilm formation and function and may be important for some water and wastewater treatment biofilms
    2. Many QS-controlled genes relate to biofilm formation and function and may be important for some water and wastewater treatment biofilms
    1. For in situ studies of AHL-dependent signaling in complex habitats, biosensors utilizing fluorescent proteins (GFP and RFP) as reporter genes have been developed
    2. biosensors were employed to demonstrate AHL-mediated communication in swarm colonies of Serratia liquefaciens
    3. QS systems have been experimentally analyzed in more than 50 different bacterial species and shown to control expression of a wide spectrum of functions, including bioluminescence, virulence, symbiosis, different forms of motility, biofilm formation, production of antibiotics and toxins, and conjugation (49).
    1. PpuI, which directs the biosynthesis of the two AHLs 3-oxo-C10 and 3-oxo-C12 as major products; PpuR, the AHL receptor; and RsaL a repressor of ppul

      P. putida IsoF, isolated from tomato rhizosphere - quorum sensing

    1. it may be possible to tag specific organisms and use these as monitor systems to estimate local chemical composition directly in the biofilms
  7. Sep 2019
    1. Such biosensors can reveal intriguing aspects of the environment and the physiology of the free-living soil S. meliloti before and during the establishment of nodulation, and they provide a nondestructive, spatially explicit method for examining rhizosphere soil chemical composition
    1. Coordinated behaviours include bioluminescence3,4, virulence factor production5,6, secondary metabolite production7, competence for DNA uptake8,9 and biofilm formation10,11.
    2. We focus on how quorums are detected and how quorum sensing controls group behaviours in complex and dynamically changing environments such as multi-species bacterial communities, in the presence of flow, in 3D non-uniform biofilms and in hosts during infection.
    1. These carboxylated AHLs facilitated the transition from a short cell to filamentous growth, with an altered carbon metabolic flux that favoured the conversion of acetate to methane and a reduced yield in cellular biomass

      Carboxylated AHL signalling favours methanogenesis in Methanosaeta herundinacea 6Ac

    1. Deletion of genes thatproduceN-acyl-L-homoserine lactone signals resulted in an increase in denitrification activity, which wasrepressed by exogenous signal molecules.

      AHL is lowering denitrification in Psuedomonas aeruginosa

  8. Aug 2019
    1. endogenous AHL-based QS and QQ are existing and coexisting in biological wastewater treatments; the leading role for AHL-based QS or QQ phenomenon in biological wastewater treatments can be determined by bacterial AHL concentration.
    1. explosion of findings that other bacterial species controlled genes for conjugation, exoenzyme production and antibiotic synthesis with luxI–luxR-like systems
  9. Jun 2019
    1. QS represses biofilm formation in both S. aureus and V. cholerae
    2. Pseudomonas aeruginosa is motile upstream (a QS-off phenotype), but forms biofilms downstream (a QS-on phenotype) in flowing networks

      Psuedomonas QS on => biofilms

  10. May 2019
  11. Feb 2017
    1. Comparison of ITCD algorithms is challenging when there are differences in study focus, study area, data applied, and accuracy assessment method used. Before 2005, the few studies that compared methods generally tested approaches on a common dataset.

      This difficulty in comparing algorithms (due to differences in forest type, location, and assessment strategy used for different algorithms) indicates a clear need for set of open data and centralized assessment to allow different methods to be competed against one another to determine the best routes forward.

      This kind of approach has been very successful in other image analysis problems (e.g., ImageNET).

      The National Ecological Observatory Network data seems ideal for doing something like this. Data is/will be available for a variety of different systems and with LiDAR, Hyperspectral, RGB, and field data for large numbers of plots.

    2. Additionally, it is often challenging to apply an algorithm developed in one forest type to another area.

      This difficulty of applying across forest types is central to the challenges of developing approaches that can be applied to continental scale data collection like that being conducted by NEON. Overcoming this challenge will likely require incorporating ecological information into models, not just the remote sensing, and determining how to choose and adjust different approaches to get the best delineations possible based on information about the forest type/location.

    3. The most useful information that can be incorporated into ITCD studies is the expected crown size and stand density [25,67].

      This kind of data is available for NEON plots and so these methods could potentially be well leveraged with NEON data. This would be particularly true if the NEON plot data could be used to develop a spatial model for these features that could be used to predict their values across space.

    4. Only 23 studies actually integrated both active and passive data sources into the ITCD procedure since 2000 (Figure 2).

      Only a small fraction of studies combine LiDAR and Hyperspectral data for the crown delineation phase of analysis.

    5. Another limitation is that few approaches take full advantage of the information contained within remotely sensed data, e.g., using only one band of multispectral imagery [29] or only the canopy height model derived from LiDAR data [30]. Significant amounts of information are dismissed or neglected during data preparation or processing. The integration of multispectral data and discrete LiDAR data is commonly used to improve tree species classification [10] and fusion of passive and active remotely sensed data may reduce commission and omission errors in ITCD results [31].

      Excellent point about the importance of integrating all available data to make the best possible crown delineations. In the case of the National Ecological Observatory Network Airborne Observation Platform methods that leverage the LiDAR, hyperspectral, and high-resolution RGB photographic data should have the potential to outperform methods that ignore components of this data.

  12. Nov 2016
    1. MODIS provides consistent information on active fires, with omission and commission errors quantified in past work using ground observations and higher-resolution satellite imagery [e.g., (29–31)]

      More detailed data was required to supplement the MODIS based remote sensing to fully understand how it could be used for quantifying fire.