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      Global Proteomic Profiling of Piscirickettsia salmonis and Salmon Macrophage-Like Cells during Intracellular Infection

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          Abstract

          Piscirickettsia salmonis is an intracellular bacterial fish pathogen that causes piscirickettsiosis, a disease with numerous negative impacts in the Chilean salmon farming industry. Although transcriptomic studies of P. salmonis and its host have been performed, dual host–pathogen proteomic approaches during infection are still missing. Considering that gene expression does not always correspond with observed phenotype, and bacteriological culture studies inadequately reflect infection conditions, to improve the existing knowledge for the pathogenicity of P. salmonis, we present here a global proteomic profiling of Salmon salar macrophage-like cell cultures infected with P. salmonis LF-89. The proteomic analyses identified several P. salmonis proteins from two temporally different stages of macrophages infection, some of them related to key functions for bacterial survival in other intracellular pathogens. Metabolic differences were observed in early-stage infection bacteria, compared to late-stage infections. Virulence factors related to membrane, lipopolysaccharide (LPS) and surface component modifications, cell motility, toxins, and secretion systems also varied between the infection stages. Pilus proteins, beta-hemolysin, and the type VI secretion system (T6SS) were characteristic of the early-infection stage, while fimbria, upregulation of 10 toxins or effector proteins, and the Dot/Icm type IV secretion system (T4SS) were representative of the late-infection stage bacteria. Previously described virulence-related genes in P. salmonis plasmids were identified by proteomic assays during infection in SHK-1 cells, accompanied by an increase of mobile-related elements. By comparing the infected and un-infected proteome of SHK-1 cells, we observed changes in cellular and redox homeostasis; innate immune response; microtubules and actin cytoskeleton organization and dynamics; alteration in phagosome components, iron transport, and metabolism; and amino acids, nucleoside, and nucleotide metabolism, together with an overall energy and ATP production alteration. Our global proteomic profiling and the current knowledge of the P. salmonis infection process allowed us to propose a model of the macrophage– P. salmonis interaction.

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          A new mathematical model for relative quantification in real-time RT-PCR.

          M. Pfaffl (2001)
          Use of the real-time polymerase chain reaction (PCR) to amplify cDNA products reverse transcribed from mRNA is on the way to becoming a routine tool in molecular biology to study low abundance gene expression. Real-time PCR is easy to perform, provides the necessary accuracy and produces reliable as well as rapid quantification results. But accurate quantification of nucleic acids requires a reproducible methodology and an adequate mathematical model for data analysis. This study enters into the particular topics of the relative quantification in real-time RT-PCR of a target gene transcript in comparison to a reference gene transcript. Therefore, a new mathematical model is presented. The relative expression ratio is calculated only from the real-time PCR efficiencies and the crossing point deviation of an unknown sample versus a control. This model needs no calibration curve. Control levels were included in the model to standardise each reaction run with respect to RNA integrity, sample loading and inter-PCR variations. High accuracy and reproducibility (<2.5% variation) were reached in LightCycler PCR using the established mathematical model.
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            Molecular mechanisms of cell death: recommendations of the Nomenclature Committee on Cell Death 2018

            Over the past decade, the Nomenclature Committee on Cell Death (NCCD) has formulated guidelines for the definition and interpretation of cell death from morphological, biochemical, and functional perspectives. Since the field continues to expand and novel mechanisms that orchestrate multiple cell death pathways are unveiled, we propose an updated classification of cell death subroutines focusing on mechanistic and essential (as opposed to correlative and dispensable) aspects of the process. As we provide molecularly oriented definitions of terms including intrinsic apoptosis, extrinsic apoptosis, mitochondrial permeability transition (MPT)-driven necrosis, necroptosis, ferroptosis, pyroptosis, parthanatos, entotic cell death, NETotic cell death, lysosome-dependent cell death, autophagy-dependent cell death, immunogenic cell death, cellular senescence, and mitotic catastrophe, we discuss the utility of neologisms that refer to highly specialized instances of these processes. The mission of the NCCD is to provide a widely accepted nomenclature on cell death in support of the continued development of the field.
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              Universal sample preparation method for proteome analysis.

              We describe a method, filter-aided sample preparation (FASP), which combines the advantages of in-gel and in-solution digestion for mass spectrometry-based proteomics. We completely solubilized the proteome in sodium dodecyl sulfate, which we then exchanged by urea on a standard filtration device. Peptides eluted after digestion on the filter were pure, allowing single-run analyses of organelles and an unprecedented depth of proteome coverage.
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                Author and article information

                Journal
                Microorganisms
                Microorganisms
                microorganisms
                Microorganisms
                MDPI
                2076-2607
                24 November 2020
                December 2020
                : 8
                : 12
                : 1845
                Affiliations
                [1 ]Laboratorio de Microbiología de Sistemas, Departamento de Biología, Facultad de Ciencias, Universidad de Chile, Santiago 7800003, Chile; javiera.o.s@ 123456gmail.com
                [2 ]Laboratorio de Bioinformática y Expresión Génica, Instituto de Nutrición y Tecnología de los Alimentos, Universidad de Chile, Santiago 7830490, Chile; vcambiaz@ 123456inta.uchile.cl
                [3 ]Fondap Center for Genome Regulation (Fondap 15090007), Universidad de Chile, Santiago 8370415, Chile; dtravisany@ 123456gmail.com (D.T.); amaass@ 123456dim.uchile.cl (A.M.)
                [4 ]Centro de Modelamiento Matemático (AFB170001) and Departamento de Ingeniería Matemática, Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile and UMI-CNRS 2807, Santiago 8370415, Chile
                Author notes
                [* ]Correspondence: fpchavez@ 123456uchile.cl
                Author information
                https://orcid.org/0000-0002-2545-176X
                https://orcid.org/0000-0002-7038-4527
                https://orcid.org/0000-0002-6838-208X
                Article
                microorganisms-08-01845
                10.3390/microorganisms8121845
                7760863
                33255149
                3a7fb33c-862b-407e-ba76-318bfc18cfd9
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 04 September 2020
                : 18 September 2020
                Categories
                Article

                fish pathogen,host–pathogen interaction,proteomics,infection assays,virulence factors

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