High-content screening image dataset and quantitative image analysis of Salmonella infected human cells

Abstract Objectives Salmonella bacteria can induce the unfolded protein response, a cellular stress response to misfolding proteins within the endoplasmic reticulum. Salmonella can exploit the host unfolded protein response leading to enhanced bacterial replication which was in part mediated by the...
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Autor*in:	Antony N. Antoniou [verfasserIn] Simon J. Powis [verfasserIn] Janos Kriston-Vizi [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Salmonella Unfolded protein response Endoplasmic reticulum High-content screening Image-based screening Phenotypic screening

Übergeordnetes Werk:	In: BMC Research Notes - BMC, 2008, 12(2019), 1, Seite 4
Übergeordnetes Werk:	volume:12 ; year:2019 ; number:1 ; pages:4

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1186/s13104-019-4844-5

Katalog-ID:	DOAJ054856310

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520			\|a Abstract Objectives Salmonella bacteria can induce the unfolded protein response, a cellular stress response to misfolding proteins within the endoplasmic reticulum. Salmonella can exploit the host unfolded protein response leading to enhanced bacterial replication which was in part mediated by the induction and/or enhanced endo-reticular membrane synthesis. We therefore wanted to establish a quantitative confocal imaging assay to measure endo-reticular membrane expansion following Salmonella infections of host cells. Data description High-content screening confocal fluorescence microscopic image set of Salmonella infected HeLa cells is presented. The images were collected with a PerkinElmer Opera LX high-content screening system in seven 96-well plates, 50 field-of-views and DAPI, endoplasmic reticulum tracker channels and Salmonella mCherry protein in each well. Totally 93,300 confocal fluorescence microscopic images were published in this dataset. An ImageJ high-content image analysis workflow was used to extract features. Cells were classified as infected and non-infected, the mean intensity of endoplasmic reticulum tracker under Salmonella bacteria was calculated. Statistical analysis was performed by an R script, quantifying infected and non-infected cells for wild-type and ΔsifA mutant cells. The dataset can be further used by researchers working with big data of endoplasmic reticulum fluorescence microscopic images, Salmonella bacterial infection images and human cancer cells.
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allfields	10.1186/s13104-019-4844-5 doi (DE-627)DOAJ054856310 (DE-599)DOAJ119285ecfc40459b9cbc684cb9c6edcb DE-627 ger DE-627 rakwb eng QH301-705.5 Q1-390 Antony N. Antoniou verfasserin aut High-content screening image dataset and quantitative image analysis of Salmonella infected human cells 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Objectives Salmonella bacteria can induce the unfolded protein response, a cellular stress response to misfolding proteins within the endoplasmic reticulum. Salmonella can exploit the host unfolded protein response leading to enhanced bacterial replication which was in part mediated by the induction and/or enhanced endo-reticular membrane synthesis. We therefore wanted to establish a quantitative confocal imaging assay to measure endo-reticular membrane expansion following Salmonella infections of host cells. Data description High-content screening confocal fluorescence microscopic image set of Salmonella infected HeLa cells is presented. The images were collected with a PerkinElmer Opera LX high-content screening system in seven 96-well plates, 50 field-of-views and DAPI, endoplasmic reticulum tracker channels and Salmonella mCherry protein in each well. Totally 93,300 confocal fluorescence microscopic images were published in this dataset. An ImageJ high-content image analysis workflow was used to extract features. Cells were classified as infected and non-infected, the mean intensity of endoplasmic reticulum tracker under Salmonella bacteria was calculated. Statistical analysis was performed by an R script, quantifying infected and non-infected cells for wild-type and ΔsifA mutant cells. The dataset can be further used by researchers working with big data of endoplasmic reticulum fluorescence microscopic images, Salmonella bacterial infection images and human cancer cells. Salmonella Unfolded protein response Endoplasmic reticulum High-content screening Image-based screening Phenotypic screening Medicine R Biology (General) Science (General) Simon J. Powis verfasserin aut Janos Kriston-Vizi verfasserin aut In BMC Research Notes BMC, 2008 12(2019), 1, Seite 4 (DE-627)559431805 (DE-600)2413336-X 17560500 nnns volume:12 year:2019 number:1 pages:4 https://doi.org/10.1186/s13104-019-4844-5 kostenfrei https://doaj.org/article/119285ecfc40459b9cbc684cb9c6edcb kostenfrei https://doi.org/10.1186/s13104-019-4844-5 kostenfrei https://doaj.org/toc/1756-0500 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2019 1 4
spelling	10.1186/s13104-019-4844-5 doi (DE-627)DOAJ054856310 (DE-599)DOAJ119285ecfc40459b9cbc684cb9c6edcb DE-627 ger DE-627 rakwb eng QH301-705.5 Q1-390 Antony N. Antoniou verfasserin aut High-content screening image dataset and quantitative image analysis of Salmonella infected human cells 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Objectives Salmonella bacteria can induce the unfolded protein response, a cellular stress response to misfolding proteins within the endoplasmic reticulum. Salmonella can exploit the host unfolded protein response leading to enhanced bacterial replication which was in part mediated by the induction and/or enhanced endo-reticular membrane synthesis. We therefore wanted to establish a quantitative confocal imaging assay to measure endo-reticular membrane expansion following Salmonella infections of host cells. Data description High-content screening confocal fluorescence microscopic image set of Salmonella infected HeLa cells is presented. The images were collected with a PerkinElmer Opera LX high-content screening system in seven 96-well plates, 50 field-of-views and DAPI, endoplasmic reticulum tracker channels and Salmonella mCherry protein in each well. Totally 93,300 confocal fluorescence microscopic images were published in this dataset. An ImageJ high-content image analysis workflow was used to extract features. Cells were classified as infected and non-infected, the mean intensity of endoplasmic reticulum tracker under Salmonella bacteria was calculated. Statistical analysis was performed by an R script, quantifying infected and non-infected cells for wild-type and ΔsifA mutant cells. The dataset can be further used by researchers working with big data of endoplasmic reticulum fluorescence microscopic images, Salmonella bacterial infection images and human cancer cells. Salmonella Unfolded protein response Endoplasmic reticulum High-content screening Image-based screening Phenotypic screening Medicine R Biology (General) Science (General) Simon J. Powis verfasserin aut Janos Kriston-Vizi verfasserin aut In BMC Research Notes BMC, 2008 12(2019), 1, Seite 4 (DE-627)559431805 (DE-600)2413336-X 17560500 nnns volume:12 year:2019 number:1 pages:4 https://doi.org/10.1186/s13104-019-4844-5 kostenfrei https://doaj.org/article/119285ecfc40459b9cbc684cb9c6edcb kostenfrei https://doi.org/10.1186/s13104-019-4844-5 kostenfrei https://doaj.org/toc/1756-0500 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2019 1 4
allfields_unstemmed	10.1186/s13104-019-4844-5 doi (DE-627)DOAJ054856310 (DE-599)DOAJ119285ecfc40459b9cbc684cb9c6edcb DE-627 ger DE-627 rakwb eng QH301-705.5 Q1-390 Antony N. Antoniou verfasserin aut High-content screening image dataset and quantitative image analysis of Salmonella infected human cells 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Objectives Salmonella bacteria can induce the unfolded protein response, a cellular stress response to misfolding proteins within the endoplasmic reticulum. Salmonella can exploit the host unfolded protein response leading to enhanced bacterial replication which was in part mediated by the induction and/or enhanced endo-reticular membrane synthesis. We therefore wanted to establish a quantitative confocal imaging assay to measure endo-reticular membrane expansion following Salmonella infections of host cells. Data description High-content screening confocal fluorescence microscopic image set of Salmonella infected HeLa cells is presented. The images were collected with a PerkinElmer Opera LX high-content screening system in seven 96-well plates, 50 field-of-views and DAPI, endoplasmic reticulum tracker channels and Salmonella mCherry protein in each well. Totally 93,300 confocal fluorescence microscopic images were published in this dataset. An ImageJ high-content image analysis workflow was used to extract features. Cells were classified as infected and non-infected, the mean intensity of endoplasmic reticulum tracker under Salmonella bacteria was calculated. Statistical analysis was performed by an R script, quantifying infected and non-infected cells for wild-type and ΔsifA mutant cells. The dataset can be further used by researchers working with big data of endoplasmic reticulum fluorescence microscopic images, Salmonella bacterial infection images and human cancer cells. Salmonella Unfolded protein response Endoplasmic reticulum High-content screening Image-based screening Phenotypic screening Medicine R Biology (General) Science (General) Simon J. Powis verfasserin aut Janos Kriston-Vizi verfasserin aut In BMC Research Notes BMC, 2008 12(2019), 1, Seite 4 (DE-627)559431805 (DE-600)2413336-X 17560500 nnns volume:12 year:2019 number:1 pages:4 https://doi.org/10.1186/s13104-019-4844-5 kostenfrei https://doaj.org/article/119285ecfc40459b9cbc684cb9c6edcb kostenfrei https://doi.org/10.1186/s13104-019-4844-5 kostenfrei https://doaj.org/toc/1756-0500 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2019 1 4
allfieldsGer	10.1186/s13104-019-4844-5 doi (DE-627)DOAJ054856310 (DE-599)DOAJ119285ecfc40459b9cbc684cb9c6edcb DE-627 ger DE-627 rakwb eng QH301-705.5 Q1-390 Antony N. Antoniou verfasserin aut High-content screening image dataset and quantitative image analysis of Salmonella infected human cells 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Objectives Salmonella bacteria can induce the unfolded protein response, a cellular stress response to misfolding proteins within the endoplasmic reticulum. Salmonella can exploit the host unfolded protein response leading to enhanced bacterial replication which was in part mediated by the induction and/or enhanced endo-reticular membrane synthesis. We therefore wanted to establish a quantitative confocal imaging assay to measure endo-reticular membrane expansion following Salmonella infections of host cells. Data description High-content screening confocal fluorescence microscopic image set of Salmonella infected HeLa cells is presented. The images were collected with a PerkinElmer Opera LX high-content screening system in seven 96-well plates, 50 field-of-views and DAPI, endoplasmic reticulum tracker channels and Salmonella mCherry protein in each well. Totally 93,300 confocal fluorescence microscopic images were published in this dataset. An ImageJ high-content image analysis workflow was used to extract features. Cells were classified as infected and non-infected, the mean intensity of endoplasmic reticulum tracker under Salmonella bacteria was calculated. Statistical analysis was performed by an R script, quantifying infected and non-infected cells for wild-type and ΔsifA mutant cells. The dataset can be further used by researchers working with big data of endoplasmic reticulum fluorescence microscopic images, Salmonella bacterial infection images and human cancer cells. Salmonella Unfolded protein response Endoplasmic reticulum High-content screening Image-based screening Phenotypic screening Medicine R Biology (General) Science (General) Simon J. Powis verfasserin aut Janos Kriston-Vizi verfasserin aut In BMC Research Notes BMC, 2008 12(2019), 1, Seite 4 (DE-627)559431805 (DE-600)2413336-X 17560500 nnns volume:12 year:2019 number:1 pages:4 https://doi.org/10.1186/s13104-019-4844-5 kostenfrei https://doaj.org/article/119285ecfc40459b9cbc684cb9c6edcb kostenfrei https://doi.org/10.1186/s13104-019-4844-5 kostenfrei https://doaj.org/toc/1756-0500 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2019 1 4
allfieldsSound	10.1186/s13104-019-4844-5 doi (DE-627)DOAJ054856310 (DE-599)DOAJ119285ecfc40459b9cbc684cb9c6edcb DE-627 ger DE-627 rakwb eng QH301-705.5 Q1-390 Antony N. Antoniou verfasserin aut High-content screening image dataset and quantitative image analysis of Salmonella infected human cells 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Objectives Salmonella bacteria can induce the unfolded protein response, a cellular stress response to misfolding proteins within the endoplasmic reticulum. Salmonella can exploit the host unfolded protein response leading to enhanced bacterial replication which was in part mediated by the induction and/or enhanced endo-reticular membrane synthesis. We therefore wanted to establish a quantitative confocal imaging assay to measure endo-reticular membrane expansion following Salmonella infections of host cells. Data description High-content screening confocal fluorescence microscopic image set of Salmonella infected HeLa cells is presented. The images were collected with a PerkinElmer Opera LX high-content screening system in seven 96-well plates, 50 field-of-views and DAPI, endoplasmic reticulum tracker channels and Salmonella mCherry protein in each well. Totally 93,300 confocal fluorescence microscopic images were published in this dataset. An ImageJ high-content image analysis workflow was used to extract features. Cells were classified as infected and non-infected, the mean intensity of endoplasmic reticulum tracker under Salmonella bacteria was calculated. Statistical analysis was performed by an R script, quantifying infected and non-infected cells for wild-type and ΔsifA mutant cells. The dataset can be further used by researchers working with big data of endoplasmic reticulum fluorescence microscopic images, Salmonella bacterial infection images and human cancer cells. Salmonella Unfolded protein response Endoplasmic reticulum High-content screening Image-based screening Phenotypic screening Medicine R Biology (General) Science (General) Simon J. Powis verfasserin aut Janos Kriston-Vizi verfasserin aut In BMC Research Notes BMC, 2008 12(2019), 1, Seite 4 (DE-627)559431805 (DE-600)2413336-X 17560500 nnns volume:12 year:2019 number:1 pages:4 https://doi.org/10.1186/s13104-019-4844-5 kostenfrei https://doaj.org/article/119285ecfc40459b9cbc684cb9c6edcb kostenfrei https://doi.org/10.1186/s13104-019-4844-5 kostenfrei https://doaj.org/toc/1756-0500 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2019 1 4
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authorswithroles_txt_mv	Antony N. Antoniou @@aut@@ Simon J. Powis @@aut@@ Janos Kriston-Vizi @@aut@@
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callnumber-first	Q - Science
author	Antony N. Antoniou
spellingShingle	Antony N. Antoniou misc QH301-705.5 misc Q1-390 misc Salmonella misc Unfolded protein response misc Endoplasmic reticulum misc High-content screening misc Image-based screening misc Phenotypic screening misc Medicine misc R misc Biology (General) misc Science (General) High-content screening image dataset and quantitative image analysis of Salmonella infected human cells
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topic_title	QH301-705.5 Q1-390 High-content screening image dataset and quantitative image analysis of Salmonella infected human cells Salmonella Unfolded protein response Endoplasmic reticulum High-content screening Image-based screening Phenotypic screening
topic	misc QH301-705.5 misc Q1-390 misc Salmonella misc Unfolded protein response misc Endoplasmic reticulum misc High-content screening misc Image-based screening misc Phenotypic screening misc Medicine misc R misc Biology (General) misc Science (General)
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title	High-content screening image dataset and quantitative image analysis of Salmonella infected human cells
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title_full	High-content screening image dataset and quantitative image analysis of Salmonella infected human cells
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title_sort	high-content screening image dataset and quantitative image analysis of salmonella infected human cells
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title_auth	High-content screening image dataset and quantitative image analysis of Salmonella infected human cells
abstract	Abstract Objectives Salmonella bacteria can induce the unfolded protein response, a cellular stress response to misfolding proteins within the endoplasmic reticulum. Salmonella can exploit the host unfolded protein response leading to enhanced bacterial replication which was in part mediated by the induction and/or enhanced endo-reticular membrane synthesis. We therefore wanted to establish a quantitative confocal imaging assay to measure endo-reticular membrane expansion following Salmonella infections of host cells. Data description High-content screening confocal fluorescence microscopic image set of Salmonella infected HeLa cells is presented. The images were collected with a PerkinElmer Opera LX high-content screening system in seven 96-well plates, 50 field-of-views and DAPI, endoplasmic reticulum tracker channels and Salmonella mCherry protein in each well. Totally 93,300 confocal fluorescence microscopic images were published in this dataset. An ImageJ high-content image analysis workflow was used to extract features. Cells were classified as infected and non-infected, the mean intensity of endoplasmic reticulum tracker under Salmonella bacteria was calculated. Statistical analysis was performed by an R script, quantifying infected and non-infected cells for wild-type and ΔsifA mutant cells. The dataset can be further used by researchers working with big data of endoplasmic reticulum fluorescence microscopic images, Salmonella bacterial infection images and human cancer cells.
abstractGer	Abstract Objectives Salmonella bacteria can induce the unfolded protein response, a cellular stress response to misfolding proteins within the endoplasmic reticulum. Salmonella can exploit the host unfolded protein response leading to enhanced bacterial replication which was in part mediated by the induction and/or enhanced endo-reticular membrane synthesis. We therefore wanted to establish a quantitative confocal imaging assay to measure endo-reticular membrane expansion following Salmonella infections of host cells. Data description High-content screening confocal fluorescence microscopic image set of Salmonella infected HeLa cells is presented. The images were collected with a PerkinElmer Opera LX high-content screening system in seven 96-well plates, 50 field-of-views and DAPI, endoplasmic reticulum tracker channels and Salmonella mCherry protein in each well. Totally 93,300 confocal fluorescence microscopic images were published in this dataset. An ImageJ high-content image analysis workflow was used to extract features. Cells were classified as infected and non-infected, the mean intensity of endoplasmic reticulum tracker under Salmonella bacteria was calculated. Statistical analysis was performed by an R script, quantifying infected and non-infected cells for wild-type and ΔsifA mutant cells. The dataset can be further used by researchers working with big data of endoplasmic reticulum fluorescence microscopic images, Salmonella bacterial infection images and human cancer cells.
abstract_unstemmed	Abstract Objectives Salmonella bacteria can induce the unfolded protein response, a cellular stress response to misfolding proteins within the endoplasmic reticulum. Salmonella can exploit the host unfolded protein response leading to enhanced bacterial replication which was in part mediated by the induction and/or enhanced endo-reticular membrane synthesis. We therefore wanted to establish a quantitative confocal imaging assay to measure endo-reticular membrane expansion following Salmonella infections of host cells. Data description High-content screening confocal fluorescence microscopic image set of Salmonella infected HeLa cells is presented. The images were collected with a PerkinElmer Opera LX high-content screening system in seven 96-well plates, 50 field-of-views and DAPI, endoplasmic reticulum tracker channels and Salmonella mCherry protein in each well. Totally 93,300 confocal fluorescence microscopic images were published in this dataset. An ImageJ high-content image analysis workflow was used to extract features. Cells were classified as infected and non-infected, the mean intensity of endoplasmic reticulum tracker under Salmonella bacteria was calculated. Statistical analysis was performed by an R script, quantifying infected and non-infected cells for wild-type and ΔsifA mutant cells. The dataset can be further used by researchers working with big data of endoplasmic reticulum fluorescence microscopic images, Salmonella bacterial infection images and human cancer cells.
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title_short	High-content screening image dataset and quantitative image analysis of Salmonella infected human cells
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High-content screening image dataset and quantitative image analysis of Salmonella infected human cells

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