Archives

  • 2018-07
  • 2018-10
  • 2018-11
  • 2019-04
  • 2019-05
  • 2019-06
  • 2019-07
  • 2019-08
  • 2019-09
  • 2019-10
  • 2019-11
  • 2019-12
  • 2020-01
  • 2020-02
  • 2020-03
  • 2020-04
  • 2020-05
  • 2020-06
  • 2020-07
  • 2020-08
  • 2020-09
  • 2020-10
  • 2020-11
  • 2020-12
  • 2021-01
  • 2021-02
  • 2021-03
  • 2021-04
  • 2021-05
  • 2021-06
  • 2021-07
  • 2021-08
  • 2021-09
  • 2021-10
  • 2021-11
  • 2021-12
  • 2022-01
  • 2022-02
  • 2022-03
  • 2022-04
  • 2022-05
  • 2022-06
  • 2022-07
  • 2022-08
  • 2022-09
  • 2022-10
  • 2022-11
  • 2022-12
  • 2023-01
  • 2023-02
  • 2023-03
  • 2023-04
  • 2023-05
  • 2023-06
  • 2023-07
  • 2023-08
  • 2023-09
  • 2023-10
  • 2023-11
  • 2023-12
  • 2024-01
  • 2024-02
  • 2024-03
  • 2024-04
  • 2024-05
  • 2024-06
  • 2024-07
  • In this report we introduce a new method

    2024-07-09

    In this report, we introduce a new method for identifying aminopeptidases. Because single substrates can be insufficient for enzyme identification, we used an entire library of substrates to obtain more information about enzyme activity and to directly detect aminopeptidases. Moreover, substrates can be monitored to restrict the identification to active enzymes and ignore inactive forms of the enzymes, thus providing an accurate picture of cellular proteolysis. As a proof of concept, in this study, we measured the aminopeptidase activity profiles in the membrane fractions of kidney lysates obtained from three species: human (Homo HG-10-102-01 sapiens), pig (Sus scrofa) and rat (Rattus norvegicus).
    Materials and methods
    Results
    Conclusions Aminopeptidases are considered terminal proteases because they are primarily responsible for the release of free HG-10-102-01 from peptides, which can be subsequently recovered and used to build new proteins. This function is usually performed by aminopeptidases with broad substrate specificity (for example, APN or LAP), whereas proteases with narrow specificity are usually responsible for controlling certain pathways (for example, MetAP hydrolyzes the N-terminal Met of newly expressed peptides) [23]. The currently used assays for determining aminopeptidase activity in tissues are based on single substrates, and in light of the overlapping substrate specificity of aminopeptidases, they seem to be insufficient [8], [27], [28]. The application of substrates must be tightly controlled to assess the possible cross-reactivity of similar enzymes; however, the single-substrate method also has favorable features that allow the study of only the active form of the enzymes present in a sample. Other assays do not always account for the influence of these possibilities, such as overlapping substrate specificity, enzyme regulation by activators or natural inhibitors, or even protein maturation that occurs in live cells. Aminopeptidase activity in the kidneys may be an early marker of pathological states such as renal cancer or renal dysfunction and has been previously examined by several groups [8], [15], [29], [30], [31]. In these studies, the whole kidney cell content or urine in physiological and pathological conditions was assayed using different methods. Some methods measured the mRNA expression, but most methods identified the enzymes directly from the lysates. The common feature of aminopeptidase activity detection methods was the application of single substrates connected to some type of tag for the final identification of individual enzymes [6], [18]. The main enzyme identified by almost every group was APN, a widely expressed protease with high proteolytic activity [8], [11], [12], [13]. The second identified enzyme of this class is APA (aspartyl-aminopeptidase, glutamyl-aminopeptidase); however, not all groups measured the activity of this enzyme [15], [16], [17]. Several other aminopeptidases have been identified in kidneys using single-substrate studies, including LAP, APB (an arginyl aminopeptidase), IRAP (a leucyl-cystinyl aminopeptidase), puromycin-sensitive aminopeptidase (a cytosolic alanyl aminopeptidase) and pyroglutamyl aminopeptidase [8], [16], [19]. In this work, we presented a new approach for measuring the aminopeptidase activity in tissues. Our method is based on a fluorogenic substrate library that monitors the overall hydrolysis performed by aminopeptidases. Substrate usage ensures that only the active form of an enzyme is assayed; moreover, the enzyme activity is monitored under physiologically relevant conditions. Our library is a multipurpose tool that can interact with enzymes according to the considerable differences in their structures. The inclusion of both natural and unnatural amino acids was previously reported to be useful for distinguishing between even very closely related enzymes [5], [23], [32], [33]. Comparing the substrate specificity of individual enzymes shows their distinct activity against both natural and unnatural amino acids. Some aminopeptidases demonstrated broad tolerance for structures that accommodated the S1 pocket, whereas others recognized only a few structures with similar chemical characteristics; the latter finding indicates the S1 pocket of the enzyme has a strictly defined shape. APN is an example of an enzyme that recognizes a wide range of substrates. APN recognized substrates such as alanine, leucine, methionine, arginine or unnatural amino acids that are used as activity indicators for other aminopeptidases [8], [22], [27], [28]. Despite some similarities for different enzymes in recognizing our library, the application of a substantial number of substrates allows us to separate the structures of unnatural amino acids that are recognized by a single enzyme. Moreover, the obtained profiles can be used to compare activities when using the best substrates and are a type of biochemical fingerprint for each aminopeptidase.