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Cited by 213

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Identification and characterization of ecologically significant prokaryotes in the sediment of freshwater lakes: molecular and cultivation studies

Open access
Stefan Spring, Renate Schulze, Jörg Overmann, K. H. SCHLEIFER·2000·FEMS Microbiology Reviews

Abstract

The aim of this review is to interpret recent studies in which molecular methods were used to identify and characterize prokaryotes in lake sediments and related habitats. In the first part studies based on the phylogenetic diversity of prokaryotes found in lacustrine habitats are summarized. The application of various cultivation-independent methods for the characterization of distinct groups of sediment bacteria is exemplified with morphologically conspicuous, colorless sulfur bacteria in the second part of this review. Finally, traditional and recently developed methods are described which could be used for linking the function of microbial populations with their identification. The potential of these approaches for the study of lake sediments is discussed in order to give a perspective for future studies in this habitat.

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OpenAlex · 10.1016/s0168-6445(00)00046-2

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Metadata

Authors
Spring, S., Schulze, R., Overmann, J., & SCHLEIFER, K. H.
Venue
FEMS Microbiology Reviews
Publisher
Oxford University Press
Published
2000-12-01
Volume
24
Issue
5
Pages
573-590
ISSN
0168-6445 (ISSN-L)
OpenAlex
W2168439468
Cited by
213
References
1
FWCI
5.50
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Identification and characterization of ecologically significant prokaryotes in the sediment of freshwater lakes: molecular and cultivation studies. https://app.cochat.ai/papers/10.1016/s0168-6445(00)00046-2
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Spring, S., Schulze, R., Overmann, J., & SCHLEIFER, K. H. (2000). Identification and characterization of ecologically significant prokaryotes in the sediment of freshwater lakes: molecular and cultivation studies. FEMS Microbiology Reviews. https://doi.org/10.1016/s0168-6445(00)00046-2

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.