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      Cold Shock Response in Bacteria

      1 , 1 , 2 , 3
      Annual Review of Genetics
      Annual Reviews

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          Abstract

          Bacteria often encounter temperature fluctuations in their natural habitats and must adapt to survive. The molecular response of bacteria to sudden temperature upshift or downshift is termed the heat shock response (HSR) or the cold shock response (CSR), respectively. Unlike the HSR, which activates a dedicated transcription factor that predominantly copes with heat-induced protein folding stress, the CSR is mediated by a diverse set of inputs. This review provides a picture of our current understanding of the CSR across bacteria. The fundamental aspects of CSR involved in sensing and adapting to temperature drop, including regulation of membrane fluidity, protein folding, DNA topology, RNA metabolism, and protein translation, are discussed. Special emphasis is placed on recent findings of a CSR circuitry in Escherichia coli mediated by cold shock family proteins and RNase R that monitors and modulates messenger RNA structure to facilitate global translation recovery during acclimation.

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          Most cited references149

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          Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling.

          Techniques for systematically monitoring protein translation have lagged far behind methods for measuring messenger RNA (mRNA) levels. Here, we present a ribosome-profiling strategy that is based on the deep sequencing of ribosome-protected mRNA fragments and enables genome-wide investigation of translation with subcodon resolution. We used this technique to monitor translation in budding yeast under both rich and starvation conditions. These studies defined the protein sequences being translated and found extensive translational control in both determining absolute protein abundance and responding to environmental stress. We also observed distinct phases during translation that involve a large decrease in ribosome density going from early to late peptide elongation as well as widespread regulated initiation at non-adenine-uracil-guanine (AUG) codons. Ribosome profiling is readily adaptable to other organisms, making high-precision investigation of protein translation experimentally accessible.
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            High resolution two-dimensional electrophoresis of proteins.

            A technique has been developed for the separation of proteins by two-dimensional polyacrylamide gel electrophoresis. Due to its resolution and sensitivity, this technique is a powerful tool for the analysis and detection of proteins from complex biological sources. Proteins are separated according to isoelectric point by isoelectric focusing in the first dimension, and according to molecular weight by sodium dodecyl sulfate electrophoresis in the second dimension. Since these two parameters are unrelated, it is possible to obtain an almost uniform distribution of protein spots across a two-diminsional gel. This technique has resolved 1100 different components from Escherichia coli and should be capable of resolving a maximum of 5000 proteins. A protein containing as little as one disintegration per min of either 14C or 35S can be detected by autoradiography. A protein which constitutes 10 minus 4 to 10 minus 5% of the total protein can be detected and quantified by autoradiography. The reproducibility of the separation is sufficient to permit each spot on one separation to be matched with a spot on a different separation. This technique provides a method for estimation (at the described sensitivities) of the number of proteins made by any biological system. This system can resolve proteins differing in a single charge and consequently can be used in the analysis of in vivo modifications resulting in a change in charge. Proteins whose charge is changed by missense mutations can be identified. A detailed description of the methods as well as the characteristics of this system are presented.
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              Quantifying absolute protein synthesis rates reveals principles underlying allocation of cellular resources.

              Quantitative views of cellular functions require precise measures of rates of biomolecule production, especially proteins-the direct effectors of biological processes. Here, we present a genome-wide approach, based on ribosome profiling, for measuring absolute protein synthesis rates. The resultant E. coli data set transforms our understanding of the extent to which protein synthesis is precisely controlled to optimize function and efficiency. Members of multiprotein complexes are made in precise proportion to their stoichiometry, whereas components of functional modules are produced differentially according to their hierarchical role. Estimates of absolute protein abundance also reveal principles for optimizing design. These include how the level of different types of transcription factors is optimized for rapid response and how a metabolic pathway (methionine biosynthesis) balances production cost with activity requirements. Our studies reveal how general principles, important both for understanding natural systems and for synthesizing new ones, emerge from quantitative analyses of protein synthesis. Copyright © 2014 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Annual Review of Genetics
                Annu. Rev. Genet.
                Annual Reviews
                0066-4197
                1545-2948
                November 23 2021
                November 23 2021
                : 55
                : 1
                : 377-400
                Affiliations
                [1 ]Department of Microbiology and Immunology, University of California, San Francisco, California 94158, USA;
                [2 ]Department of Cell and Tissue Biology, University of California, San Francisco, California 94158, USA
                [3 ]California Institute of Quantitative Biology, University of California, San Francisco, California 94158, USA
                Article
                10.1146/annurev-genet-071819-031654
                34530639
                50463745-728b-4681-8c48-537b8327aa62
                © 2021
                History

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