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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

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.
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: Pro-inflammatory β cell small extracellular vesicles induce β cell failure through activation of the CXCL10/CXCR3 axis in diabetes.

Javeed, Naureen / Her, Tracy K / Brown, Matthew R / Vanderboom, Patrick / Rakshit, Kuntol / Egan, Aoife M / Vella, Adrian / Lanza, Ian / Matveyenko, Aleksey V

Cell reports

2021 Volume 36, Issue 8, Page(s) 109613

Abstract: Coordinated communication among pancreatic islet cells is necessary for maintenance of glucose homeostasis. In diabetes, chronic exposure to pro-inflammatory cytokines has been shown to perturb β cell communication and function. Compelling evidence has ... ...

Abstract	Coordinated communication among pancreatic islet cells is necessary for maintenance of glucose homeostasis. In diabetes, chronic exposure to pro-inflammatory cytokines has been shown to perturb β cell communication and function. Compelling evidence has implicated extracellular vesicles (EVs) in modulating physiological and pathological responses to β cell stress. We report that pro-inflammatory β cell small EVs (cytokine-exposed EVs [cytoEVs]) induce β cell dysfunction, promote a pro-inflammatory islet transcriptome, and enhance recruitment of CD8
MeSH term(s)	Animals ; CD8-Positive T-Lymphocytes/immunology ; CD8-Positive T-Lymphocytes/metabolism ; Chemokine CXCL10/metabolism ; Diabetes Mellitus/pathology ; Extracellular Vesicles/metabolism ; Insulin-Secreting Cells/metabolism ; Macrophages/metabolism ; Male ; Mice, Inbred C57BL ; Receptors, CXCR3/metabolism ; Mice
Chemical Substances	Chemokine CXCL10 ; Cxcl10 protein, mouse ; Cxcr3 protein, mouse ; Receptors, CXCR3
Language	English
Publishing date	2021-08-24
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2649101-1
ISSN	2211-1247 ; 2211-1247
ISSN (online)	2211-1247
ISSN	2211-1247
DOI	10.1016/j.celrep.2021.109613
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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 ; 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 ; 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: 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
Database	NAL-Catalogue (AGRICOLA)

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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: GADD45A is a mediator of mitochondrial loss, atrophy, and weakness in skeletal muscle.

JCI insight

2023 Volume 8, Issue 22

Abstract: Aging and many illnesses and injuries impair skeletal muscle mass and function, but the molecular mechanisms are not well understood. To better understand the mechanisms, we generated and studied transgenic mice with skeletal muscle-specific expression ... ...

Abstract	Aging and many illnesses and injuries impair skeletal muscle mass and function, but the molecular mechanisms are not well understood. To better understand the mechanisms, we generated and studied transgenic mice with skeletal muscle-specific expression of growth arrest and DNA damage inducible α (GADD45A), a signaling protein whose expression in skeletal muscle rises during aging and a wide range of illnesses and injuries. We found that GADD45A induced several cellular changes that are characteristic of skeletal muscle atrophy, including a reduction in skeletal muscle mitochondria and oxidative capacity, selective atrophy of glycolytic muscle fibers, and paradoxical expression of oxidative myosin heavy chains despite mitochondrial loss. These cellular changes were at least partly mediated by MAP kinase kinase kinase 4, a protein kinase that is directly activated by GADD45A. By inducing these changes, GADD45A decreased the mass of muscles that are enriched in glycolytic fibers, and it impaired strength, specific force, and endurance exercise capacity. Furthermore, as predicted by data from mouse models, we found that GADD45A expression in skeletal muscle was associated with muscle weakness in humans. Collectively, these findings identify GADD45A as a mediator of mitochondrial loss, atrophy, and weakness in mouse skeletal muscle and a potential target for muscle weakness in humans.
MeSH term(s)	Animals ; Humans ; Mice ; Aging ; Cell Cycle Proteins/genetics ; Cell Cycle Proteins/metabolism ; Mitochondria, Muscle/metabolism ; Muscle Weakness/metabolism ; Muscle, Skeletal/metabolism ; Muscular Atrophy/pathology
Chemical Substances	Cell Cycle Proteins ; GADD45A protein, human
Language	English
Publishing date	2023-11-22
Publishing country	United States
Document type	Journal Article
ISSN	2379-3708
ISSN (online)	2379-3708
DOI	10.1172/jci.insight.171772
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