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Article ; Online: Detection and quantification of Babesia species intraerythrocytic parasites by flow cytometry.

Vanderboom, Patrick M / Misra, Anisha / Rodino, Kyle G / Eberly, Allison R / Greenwood, Jason D / Morris, Heather E / Norrie, Felicity C / Fernholz, Emily C / Pritt, Bobbi S / Norgan, Andrew P

American journal of clinical pathology

2023 Volume 161, Issue 5, Page(s) 451–462

Abstract: Objectives: Recent work has demonstrated that automated fluorescence flow cytometry (FLC) is a potential alternative for the detection and quantification of Plasmodium parasites. The objective of this study was to apply this novel FLC method to detect ... ...

Abstract	Objectives: Recent work has demonstrated that automated fluorescence flow cytometry (FLC) is a potential alternative for the detection and quantification of Plasmodium parasites. The objective of this study was to apply this novel FLC method to detect and quantify Babesia parasites in venous blood and compare results to light microscopy and polymerase chain reaction methods. Methods: An automated hematology/malaria analyzer (XN-31; Sysmex) was used to detect and quantify B microti-infected red blood cells from residual venous blood samples (n = 250: Babesia positive, n = 170; Babesia negative, n = 80). As no instrument software currently exists for Babesia, qualitative and quantitative machine learning (ML) algorithms were developed to facilitate analysis. Results: Performance of the ML models was verified against the XN-31 software using P falciparum-infected samples. When applied to Babesia-infected samples, the qualitative ML model demonstrated an area under the curve (AUC) of 0.956 (sensitivity, 95.9%; specificity, 83.3%) relative to polymerase chain reaction. For valid scattergrams, the qualitive model achieved an AUC of 1.0 (sensitivity and specificity, 100%), while the quantitative model demonstrated an AUC of 0.986 (sensitivity, 94.4%; specificity, 100%). Conclusions: This investigation demonstrates that Babesia parasites can be detected and quantified directly from venous blood using FLC. Although promising, opportunities remain to improve the general applicability of the method.
MeSH term(s)	Flow Cytometry/methods ; Humans ; Babesiosis/diagnosis ; Babesiosis/blood ; Erythrocytes/parasitology ; Babesia/isolation & purification ; Babesia/genetics ; Machine Learning ; Polymerase Chain Reaction/methods ; Sensitivity and Specificity
Language	English
Publishing date	2023-12-19
Publishing country	England
Document type	Journal Article
ZDB-ID	2944-0
ISSN	1943-7722 ; 0002-9173
ISSN (online)	1943-7722
ISSN	0002-9173
DOI	10.1093/ajcp/aqad168
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Article ; Online: A size-exclusion-based approach for purifying extracellular vesicles from human plasma.

Vanderboom, Patrick M / Dasari, Surendra / Ruegsegger, Gregory N / Pataky, Mark W / Lucien, Fabrice / Heppelmann, Carrie Jo / Lanza, Ian R / Nair, K Sreekumaran

Cell reports methods

2021 Volume 1, Issue 3

Abstract: Extracellular vesicles (EVs) are released into blood from multiple organs and carry molecular cargo that facilitates inter-organ communication and an integrated response to physiological and pathological stimuli. Interrogation of the protein cargo of EVs ...

Abstract	Extracellular vesicles (EVs) are released into blood from multiple organs and carry molecular cargo that facilitates inter-organ communication and an integrated response to physiological and pathological stimuli. Interrogation of the protein cargo of EVs is currently limited by the absence of optimal and reproducible approaches for purifying plasma EVs that are suitable for downstream proteomic analyses. We describe a size-exclusion chromatography (SEC)-based method to purify EVs from platelet-poor plasma (PPP) for proteomics profiling via high-resolution mass spectrometry (SEC-MS). The SEC-MS method identifies more proteins with higher precision than several conventional EV isolation approaches. We apply the SEC-MS method to identify the unique proteomic signatures of EVs released from platelets, adipocytes, muscle cells, and hepatocytes, with the goal of identifying tissue-specific EV markers. Furthermore, we apply the SEC-MS approach to evaluate the effects of a single bout of exercise on EV proteomic cargo in human plasma.
MeSH term(s)	Humans ; Proteomics/methods ; Proteins/analysis ; Extracellular Vesicles/chemistry ; Chromatography, Gel ; Mass Spectrometry/methods
Chemical Substances	Proteins
Language	English
Publishing date	2021-07-26
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ISSN	2667-2375
ISSN (online)	2667-2375
DOI	10.1016/j.crmeth.2021.100055
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Article ; Online: DIA-Based Proteome Profiling of Nasopharyngeal Swabs from COVID-19 Patients.

Mun, Dong-Gi / Vanderboom, Patrick M / Madugundu, Anil K / Garapati, Kishore / Chavan, Sandip / Peterson, Jane A / Saraswat, Mayank / Pandey, Akhilesh

Journal of proteome research

2021 Volume 20, Issue 8, Page(s) 4165–4175

Abstract: Since the recent outbreak of COVID-19, there have been intense efforts to understand viral pathogenesis and host immune response to combat SARS-CoV-2. It has become evident that different host alterations can be identified in SARS-CoV-2 infection based ... ...

Abstract	Since the recent outbreak of COVID-19, there have been intense efforts to understand viral pathogenesis and host immune response to combat SARS-CoV-2. It has become evident that different host alterations can be identified in SARS-CoV-2 infection based on whether infected cells, animal models or clinical samples are studied. Although nasopharyngeal swabs are routinely collected for SARS-CoV-2 detection by RT-PCR testing, host alterations in the nasopharynx at the proteomic level have not been systematically investigated. Thus, we sought to characterize the host response through global proteome profiling of nasopharyngeal swab specimens. A mass spectrometer combining trapped ion mobility spectrometry (TIMS) and high-resolution QTOF mass spectrometer with parallel accumulation-serial fragmentation (PASEF) was deployed for unbiased proteome profiling. First, deep proteome profiling of pooled nasopharyngeal swab samples was performed in the PASEF enabled DDA mode, which identified 7723 proteins that were then used to generate a spectral library. This approach provided peptide level evidence of five missing proteins for which MS/MS spectrum and mobilograms were validated with synthetic peptides. Subsequently, quantitative proteomic profiling was carried out for 90 individual nasopharyngeal swab samples (45 positive and 45 negative) in DIA combined with PASEF, termed as diaPASEF mode, which resulted in a total of 5023 protein identifications. Of these, 577 proteins were found to be upregulated in SARS-CoV-2 positive samples. Functional analysis of these upregulated proteins revealed alterations in several biological processes including innate immune response, viral protein assembly, and exocytosis. To the best of our knowledge, this study is the first to deploy diaPASEF for quantitative proteomic profiling of clinical samples and shows the feasibility of adopting such an approach to understand mechanisms and pathways altered in diseases.
MeSH term(s)	COVID-19 ; Humans ; Nasopharynx ; Proteome ; Proteomics ; SARS-CoV-2 ; Specimen Handling ; Tandem Mass Spectrometry
Chemical Substances	Proteome
Language	English
Publishing date	2021-07-22
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2078618-9
ISSN	1535-3907 ; 1535-3893
ISSN (online)	1535-3907
ISSN	1535-3893
DOI	10.1021/acs.jproteome.1c00506
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Article: DIA-Based Proteome Profiling of Nasopharyngeal Swabs from COVID-19 Patients

Mun, Dong-Gi / Vanderboom, Patrick M. / Madugundu, Anil K. / Garapati, Kishore / Chavan, Sandip / Peterson, Jane A. / Saraswat, Mayank / Pandey, Akhilesh

Journal of proteome research. 2021 July 22, v. 20, no. 8

2021

Abstract	Since the recent outbreak of COVID-19, there have been intense efforts to understand viral pathogenesis and host immune response to combat SARS-CoV-2. It has become evident that different host alterations can be identified in SARS-CoV-2 infection based on whether infected cells, animal models or clinical samples are studied. Although nasopharyngeal swabs are routinely collected for SARS-CoV-2 detection by RT-PCR testing, host alterations in the nasopharynx at the proteomic level have not been systematically investigated. Thus, we sought to characterize the host response through global proteome profiling of nasopharyngeal swab specimens. A mass spectrometer combining trapped ion mobility spectrometry (TIMS) and high-resolution QTOF mass spectrometer with parallel accumulation-serial fragmentation (PASEF) was deployed for unbiased proteome profiling. First, deep proteome profiling of pooled nasopharyngeal swab samples was performed in the PASEF enabled DDA mode, which identified 7723 proteins that were then used to generate a spectral library. This approach provided peptide level evidence of five missing proteins for which MS/MS spectrum and mobilograms were validated with synthetic peptides. Subsequently, quantitative proteomic profiling was carried out for 90 individual nasopharyngeal swab samples (45 positive and 45 negative) in DIA combined with PASEF, termed as diaPASEF mode, which resulted in a total of 5023 protein identifications. Of these, 577 proteins were found to be upregulated in SARS-CoV-2 positive samples. Functional analysis of these upregulated proteins revealed alterations in several biological processes including innate immune response, viral protein assembly, and exocytosis. To the best of our knowledge, this study is the first to deploy diaPASEF for quantitative proteomic profiling of clinical samples and shows the feasibility of adopting such an approach to understand mechanisms and pathways altered in diseases.
Keywords	COVID-19 infection ; Severe acute respiratory syndrome coronavirus 2 ; animals ; exocytosis ; immune response ; innate immunity ; nasopharynx ; pathogenesis ; proteome ; proteomics ; research ; spectrometers ; synthetic peptides
Language	English
Dates of publication	2021-0722
Size	p. 4165-4175.
Publishing place	American Chemical Society
Document type	Article
ZDB-ID	2078618-9
ISSN	1535-3907 ; 1535-3893
ISSN (online)	1535-3907
ISSN	1535-3893
DOI	10.1021/acs.jproteome.1c00506
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Article: Correction: A SISCAPA-based approach for detection of SARS-CoV-2 viral antigens from clinical samples.

Mangalaparthi, Kiran K / Chavan, Sandip / Madugundu, Anil K / Renuse, Santosh / Vanderboom, Patrick M / Maus, Anthony D / Kemp, Jennifer / Kipp, Benjamin R / Grebe, Stefan K / Singh, Ravinder J / Pandey, Akhilesh

Clinical proteomics

2022 Volume 19, Issue 1, Page(s) 11

Language	English
Publishing date	2022-05-04
Publishing country	England
Document type	Published Erratum
ZDB-ID	2205154-5
ISSN	1542-6416
ISSN	1542-6416
DOI	10.1186/s12014-022-09355-z
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Article: 13

Renuse, Santosh / Benson, Linda M / Vanderboom, Patrick M / Ruchi, F N U / Yadav, Yogesh R / Johnson, Kenneth L / Brown, Benjamin C / Peterson, Jane A / Basu, Rita / McCormick, Daniel J / Pandey, Akhilesh / Basu, Ananda

Clinical proteomics

2022 Volume 19, Issue 1, Page(s) 16

Abstract: Background: Glucagon serves as an important regulatory hormone for regulating blood glucose concentration with tight feedback control exerted by insulin and glucose. There are critical gaps in our understanding of glucagon kinetics, pancreatic α cell ... ...

Abstract	Background: Glucagon serves as an important regulatory hormone for regulating blood glucose concentration with tight feedback control exerted by insulin and glucose. There are critical gaps in our understanding of glucagon kinetics, pancreatic α cell function and intra-islet feedback network that are disrupted in type 1 diabetes. This is important for translational research applications of evolving dual-hormone (insulin + glucagon) closed-loop artificial pancreas algorithms and their usage in type 1 diabetes. Thus, it is important to accurately measure glucagon kinetics in vivo and to develop robust models of glucose-insulin-glucagon interplay that could inform next generation of artificial pancreas algorithms. Methods: Here, we describe the administration of novel Results: The limit of quantitation was found to be 1.56 pg/ml using stable isotope-labeled glucagon as an internal standard. Intra and inter-assay variability was < 6% and < 16%, respectively, for FF glucagon while it was < 5% and < 23%, respectively, for FFLA glucagon. Further, we carried out a novel isotope dilution technique using glucagon tracers for studying glucagon kinetics in type 1 diabetes. Conclusions: The methods described in this study for simultaneous detection and quantitation of glucagon tracers have clinical utility for investigating glucagon kinetics in vivo in humans.
Language	English
Publishing date	2022-05-19
Publishing country	England
Document type	Journal Article
ZDB-ID	2205154-5
ISSN	1542-6416
ISSN	1542-6416
DOI	10.1186/s12014-022-09344-2
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Article ; Online: Machine Learning-Based Fragment Selection Improves the Performance of Qualitative PRM Assays.

Vanderboom, Patrick M / Renuse, Santosh / Maus, Anthony D / Madugundu, Anil K / Kemp, Jennifer V / Gurtner, Kari M / Singh, Ravinder J / Grebe, Stefan K / Pandey, Akhilesh / Dasari, Surendra

Journal of proteome research

2022 Volume 21, Issue 8, Page(s) 2045–2054

Abstract: Targeted mass spectrometry-based platforms have become a valuable tool for the sensitive and specific detection of protein biomarkers in clinical and research settings. Traditionally, developing a targeted assay for peptide quantification has involved ... ...

Abstract	Targeted mass spectrometry-based platforms have become a valuable tool for the sensitive and specific detection of protein biomarkers in clinical and research settings. Traditionally, developing a targeted assay for peptide quantification has involved manually preselecting several fragment ions and establishing a limit of detection (LOD) and a lower limit of quantitation (LLOQ) for confident detection of the target. Established thresholds such as LOD and LLOQ, however, inherently sacrifice sensitivity to afford specificity. Here, we demonstrate that machine learning can be applied to qualitative PRM assays to discriminate positive from negative samples more effectively than a traditional approach utilizing conventional methods. To demonstrate the utility of this method, we trained an ensemble machine learning model using 282 SARS-CoV-2 positive and 994 SARS-CoV-2 negative nasopharyngeal swabs (NP swab) analyzed using a targeted PRM method. This model was then validated using an independent set of 200 positive and 150 negative samples and achieved a sensitivity of 92% relative to results obtained by RT-PCR, which was superior to a traditional approach that resulted in 86.5% sensitivity when analyzing the same data. These results demonstrate that machine learning can be applied to qualitative PRM assays and results in superior performance relative to traditional methods.
MeSH term(s)	COVID-19 ; COVID-19 Testing ; Humans ; Machine Learning ; Mass Spectrometry/methods ; SARS-CoV-2 ; Sensitivity and Specificity
Language	English
Publishing date	2022-07-18
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2078618-9
ISSN	1535-3907 ; 1535-3893
ISSN (online)	1535-3907
ISSN	1535-3893
DOI	10.1021/acs.jproteome.2c00156
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Article: Machine Learning-Based Fragment Selection Improves the Performance of Qualitative PRM Assays

Vanderboom, Patrick M. / Renuse, Santosh / Maus, Anthony D. / Madugundu, Anil K. / Kemp, Jennifer V. / Gurtner, Kari M. / Singh, Ravinder J. / Grebe, Stefan K. / Pandey, Akhilesh / Dasari, Surendra

Journal of proteome research. 2022 July 18, v. 21, no. 8

2022

Abstract	Targeted mass spectrometry-based platforms have become a valuable tool for the sensitive and specific detection of protein biomarkers in clinical and research settings. Traditionally, developing a targeted assay for peptide quantification has involved manually preselecting several fragment ions and establishing a limit of detection (LOD) and a lower limit of quantitation (LLOQ) for confident detection of the target. Established thresholds such as LOD and LLOQ, however, inherently sacrifice sensitivity to afford specificity. Here, we demonstrate that machine learning can be applied to qualitative PRM assays to discriminate positive from negative samples more effectively than a traditional approach utilizing conventional methods. To demonstrate the utility of this method, we trained an ensemble machine learning model using 282 SARS-CoV-2 positive and 994 SARS-CoV-2 negative nasopharyngeal swabs (NP swab) analyzed using a targeted PRM method. This model was then validated using an independent set of 200 positive and 150 negative samples and achieved a sensitivity of 92% relative to results obtained by RT-PCR, which was superior to a traditional approach that resulted in 86.5% sensitivity when analyzing the same data. These results demonstrate that machine learning can be applied to qualitative PRM assays and results in superior performance relative to traditional methods.
Keywords	Severe acute respiratory syndrome coronavirus 2 ; biomarkers ; detection limit ; mass spectrometry ; models ; peptides ; proteome ; research
Language	English
Dates of publication	2022-0718
Size	p. 2045-2054.
Publishing place	American Chemical Society
Document type	Article
ZDB-ID	2078618-9
ISSN	1535-3907 ; 1535-3893
ISSN (online)	1535-3907
ISSN	1535-3893
DOI	10.1021/acs.jproteome.2c00156
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Article: A Comparative Proteomic Analysis of Extracellular Vesicles Associated With Lipotoxicity.

Nakao, Yasuhiko / Fukushima, Masanori / Mauer, Amy S / Liao, Chieh-Yu / Ferris, Anya / Dasgupta, Debanjali / Heppelmann, Carrie Jo / Vanderboom, Patrick M / Saraswat, Mayank / Pandey, Akhilesh / Nair, K Sreekumaran / Allen, Alina M / Nakao, Kazuhiko / Malhi, Harmeet

Frontiers in cell and developmental biology

2021 Volume 9, Page(s) 735001

Abstract: Extracellular vesicles (EVs) are emerging mediators of intercellular communication in nonalcoholic steatohepatitis (NASH). Palmitate, a lipotoxic saturated fatty acid, activates hepatocellular endoplasmic reticulum stress, which has been demonstrated to ... ...

Abstract	Extracellular vesicles (EVs) are emerging mediators of intercellular communication in nonalcoholic steatohepatitis (NASH). Palmitate, a lipotoxic saturated fatty acid, activates hepatocellular endoplasmic reticulum stress, which has been demonstrated to be important in NASH pathogenesis, including in the release of EVs. We have previously demonstrated that the release of palmitate-stimulated EVs is dependent on the
Language	English
Publishing date	2021-11-04
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2737824-X
ISSN	2296-634X
ISSN	2296-634X
DOI	10.3389/fcell.2021.735001
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Article ; Online: Proteomic Signature of Host Response to SARS-CoV-2 Infection in the Nasopharynx.

Vanderboom, Patrick M / Mun, Dong-Gi / Madugundu, Anil K / Mangalaparthi, Kiran K / Saraswat, Mayank / Garapati, Kishore / Chakraborty, Rana / Ebihara, Hideki / Sun, Jie / Pandey, Akhilesh

Molecular & cellular proteomics : MCP

2021 Volume 20, Page(s) 100134

Abstract: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, has become a global health pandemic. COVID-19 severity ranges from an asymptomatic infection to a severe multiorgan disease. Although ... ...

Abstract	Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, has become a global health pandemic. COVID-19 severity ranges from an asymptomatic infection to a severe multiorgan disease. Although the inflammatory response has been implicated in the pathogenesis of COVID-19, the exact nature of dysregulation in signaling pathways has not yet been elucidated, underscoring the need for further molecular characterization of SARS-CoV-2 infection in humans. Here, we characterize the host response directly at the point of viral entry through analysis of nasopharyngeal swabs. Multiplexed high-resolution MS-based proteomic analysis of confirmed COVID-19 cases and negative controls identified 7582 proteins and revealed significant upregulation of interferon-mediated antiviral signaling in addition to multiple other proteins that are not encoded by interferon-stimulated genes or well characterized during viral infections. Downregulation of several proteasomal subunits, E3 ubiquitin ligases, and components of protein synthesis machinery was significant upon SARS-CoV-2 infection. Targeted proteomics to measure abundance levels of MX1, ISG15, STAT1, RIG-I, and CXCL10 detected proteomic signatures of interferon-mediated antiviral signaling that differentiated COVID-19-positive from COVID-19-negative cases. Phosphoproteomic analysis revealed increased phosphorylation of several proteins with known antiviral properties as well as several proteins involved in ciliary function (CEP131 and CFAP57) that have not previously been implicated in the context of coronavirus infections. In addition, decreased phosphorylation levels of AKT and PKC, which have been shown to play varying roles in different viral infections, were observed in infected individuals relative to controls. These data provide novel insights that add depth to our understanding of SARS-CoV-2 infection in the upper airway and establish a proteomic signature for this viral infection.
MeSH term(s)	COVID-19/immunology ; COVID-19/metabolism ; COVID-19/virology ; Chromatography, Liquid ; Epithelial Cells/metabolism ; Epithelial Cells/virology ; Host-Pathogen Interactions/physiology ; Humans ; Interferons/immunology ; Interferons/metabolism ; Nasopharynx/virology ; Phosphoproteins/analysis ; Phosphoproteins/metabolism ; Proteasome Endopeptidase Complex/metabolism ; Protein Kinase C/metabolism ; Proteome/analysis ; Proteome/metabolism ; Proto-Oncogene Proteins c-akt/metabolism ; Receptors, Opioid/metabolism ; Signal Transduction ; Tandem Mass Spectrometry ; Ubiquitin/metabolism
Chemical Substances	Phosphoproteins ; Proteome ; Receptors, Opioid ; Ubiquitin ; methionine-enkephalin receptor ; Interferons (9008-11-1) ; Proto-Oncogene Proteins c-akt (EC 2.7.11.1) ; Protein Kinase C (EC 2.7.11.13) ; Proteasome Endopeptidase Complex (EC 3.4.25.1)
Language	English
Publishing date	2021-08-14
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2075924-1
ISSN	1535-9484 ; 1535-9476
ISSN (online)	1535-9484
ISSN	1535-9476
DOI	10.1016/j.mcpro.2021.100134
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