Literature DB >> 16329948

Dynamics in bacterial surface properties of a natural bacterial community in the coastal North Sea during a spring phytoplankton bloom.

Karen Elisabeth Stoderegger1, Gerhard J Herndl.   

Abstract

The hydrophilic and hydrophobic properties of single cells of natural bacterioplankton communities were determined using a recently developed staining method combined with confocal laser scanning microscopy and advanced image analysis. On an average, about 50% of the bacterial cell area was covered by hydrophobic and only 16% by hydrophilic properties, while about 72% was covered by the genome. However, the size of these properties was independent of the bacterial cell size. Bacterial hydrophobicity was positively correlated with ambient NH(4)(+) concentrations and negatively correlated with overall bacterial abundance. The expression of hydrophilicity was more dynamic. Over the spring phytoplankton bloom, the bacterioplankton ratio(phil/phob) repeatedly reached highest values shortly before peaks in bacterioplankton abundance were observed, indicating a direct and fast response of bacterial surface properties, especially hydrophilicity, to changing environmental conditions. Compared to bacterial strains, recently studied with the same method, cells of marine bacterioplankton communities are much smaller and less frequently covered by hydrophobic or hydrophilic properties. While the percentage area covered by the genome is essentially the same, the percentage area covered by hydrophobic or hydrophilic properties is much smaller.

Entities:  

Mesh:

Year:  2005        PMID: 16329948     DOI: 10.1016/j.femsec.2005.01.015

Source DB:  PubMed          Journal:  FEMS Microbiol Ecol        ISSN: 0168-6496            Impact factor:   4.194


  2 in total

Review 1.  Master recyclers: features and functions of bacteria associated with phytoplankton blooms.

Authors:  Alison Buchan; Gary R LeCleir; Christopher A Gulvik; José M González
Journal:  Nat Rev Microbiol       Date:  2014-08-19       Impact factor: 60.633

2.  A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep learning approaches.

Authors:  Jiawei Zhang; Chen Li; Md Mamunur Rahaman; Yudong Yao; Pingli Ma; Jinghua Zhang; Xin Zhao; Tao Jiang; Marcin Grzegorzek
Journal:  Artif Intell Rev       Date:  2021-09-29       Impact factor: 9.588

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.