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Soleimani S, Bruce-Tagoe TA, Ullah N, Rippy MG, Spratt HG, Danquah MK. Development and characterization of a portable electrochemical aptasensor for IsdA protein and Staphylococcus aureus detection. Anal Bioanal Chem 2024; 416:4619-4634. [PMID: 38916796 DOI: 10.1007/s00216-024-05410-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Accepted: 06/14/2024] [Indexed: 06/26/2024]
Abstract
Staphylococcus aureus (S. aureus) is recognized as one of the most common causes of gastroenteritis worldwide. This pathogen is a major foodborne pathogen that can cause many different types of various infections, from minor skin infections to lethal blood infectious diseases. Iron-regulated surface determinant protein A (IsdA) is an important protein on the S. aureus surface. It is responsible for iron scavenging via interaction with hemoglobin, haptoglobin, and hemoglobin-haptoglobin complexes. This study develops a portable aptasensor for IsdA and S. aureus detection using aptamer-modified gold nanoparticles (AuNPs) integrated into screen-printed carbon electrodes (SPCEs). The electrode system was made of three parts, including a carbon counter electrode, an AuNPs/carbon working electrode, and a silver reference electrode. The aptamer by Au-S bonding was conjugated on the electrode surface to create the aptasensor platform. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were utilized to investigate the binding interactions between the aptasensor and the IsdA protein. CV studies showed a linear correlation between varying S. aureus concentrations within the range of 101 to 106 CFU/mL, resulting in a limit of detection (LOD) of 0.2 CFU/mL. The results demonstrated strong reproducibility, selectivity, and sensitivity of the aptasensor for enhanced detection of IsdA, along with about 93% performance stability after 30 days. The capability of the aptasensor to directly detect S. aureus via the IsdA surface protein binding was further investigated in a food matrix. Overall, the aptasensor device showed the potential for rapid detection of S. aureus, serving as a robust approach to developing real-time aptasensors to identify an extensive range of targets of foodborne pathogens and beyond.
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Affiliation(s)
- Shokoufeh Soleimani
- Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, TN, 37996, USA
| | - Tracy Ann Bruce-Tagoe
- Department of Chemical and Biomolecular Engineering, University of Tennessee, Knoxville, TN, 37996, USA
| | - Najeeb Ullah
- Department of Chemical and Biomolecular Engineering, University of Tennessee, Knoxville, TN, 37996, USA
| | - Meredith G Rippy
- Department of Biology, Geology, and Environmental Science, University of Tennessee, Chattanooga, TN, 37403, USA
| | - Henry G Spratt
- Department of Biology, Geology, and Environmental Science, University of Tennessee, Chattanooga, TN, 37403, USA
| | - Michael K Danquah
- Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, TN, 37996, USA.
- Department of Chemical and Biomolecular Engineering, University of Tennessee, Knoxville, TN, 37996, USA.
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2
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Strunk T, Molloy EJ, Mishra A, Bhutta ZA. Neonatal bacterial sepsis. Lancet 2024; 404:277-293. [PMID: 38944044 DOI: 10.1016/s0140-6736(24)00495-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 02/06/2024] [Accepted: 03/07/2024] [Indexed: 07/01/2024]
Abstract
Neonatal sepsis remains one of the key challenges of neonatal medicine, and together with preterm birth, causes almost 50% of all deaths globally for children younger than 5 years. Compared with advances achieved for other serious neonatal and early childhood conditions globally, progress in reducing neonatal sepsis has been much slower, especially in low-resource settings that have the highest burden of neonatal sepsis morbidity and mortality. By contrast to sepsis in older patients, there is no universally accepted neonatal sepsis definition. This poses substantial challenges in clinical practice, research, and health-care management, and has direct practical implications, such as diagnostic inconsistency, heterogeneous data collection and surveillance, and inappropriate treatment, health-resource allocation, and education. As the clinical manifestation of neonatal sepsis is frequently non-specific and the current diagnostic standard blood culture has performance limitations, new improved diagnostic techniques are required to guide appropriate and warranted antimicrobial treatment. Although antimicrobial therapy and supportive care continue as principal components of neonatal sepsis therapy, refining basic neonatal care to prevent sepsis through education and quality improvement initiatives remains paramount.
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Affiliation(s)
- Tobias Strunk
- Neonatal Directorate, King Edward Memorial Hospital, Child and Adolescent Health Service, Perth, WA, Australia; Wesfarmers Centre for Vaccines and Infectious Diseases, Telethon Kids Institute, University of Western Australia, Perth, WA, Australia.
| | - Eleanor J Molloy
- Discipline of Paediatrics, Trinity College, University of Dublin and Trinity Research in Childhood Centre, Dublin, Ireland; Children's Health Hospital at Tallaght, Tallaght University Hospital, Dublin, Ireland; Trinity Translational Medicine Institute, St James Hospital, Dublin, Ireland; Neonatology, Children's Health Hospital at Crumlin, Dublin, Ireland; Paediatrics, Coombe Women's and Infant's University Hospital, Dublin, Ireland
| | - Archita Mishra
- Wesfarmers Centre for Vaccines and Infectious Diseases, Telethon Kids Institute, University of Western Australia, Perth, WA, Australia
| | - Zulfiqar A Bhutta
- Centre for Global Child Health, Hospital for Sick Children, Toronto, ON, Canada; Institute for Global Health and Development, The Aga Khan University South-Central Asia, Karachi, Pakistan
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3
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Alves G, Ogurtsov AY, Porterfield H, Maity T, Jenkins LM, Sacks DB, Yu YK. Multiplexing the Identification of Microorganisms via Tandem Mass Tag Labeling Augmented by Interference Removal through a Novel Modification of the Expectation Maximization Algorithm. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:1138-1155. [PMID: 38740383 PMCID: PMC11157548 DOI: 10.1021/jasms.3c00445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 04/12/2024] [Accepted: 04/17/2024] [Indexed: 05/16/2024]
Abstract
Having fast, accurate, and broad spectrum methods for the identification of microorganisms is of paramount importance to public health, research, and safety. Bottom-up mass spectrometer-based proteomics has emerged as an effective tool for the accurate identification of microorganisms from microbial isolates. However, one major hurdle that limits the deployment of this tool for routine clinical diagnosis, and other areas of research such as culturomics, is the instrument time required for the mass spectrometer to analyze a single sample, which can take ∼1 h per sample, when using mass spectrometers that are presently used in most institutes. To address this issue, in this study, we employed, for the first time, tandem mass tags (TMTs) in multiplex identifications of microorganisms from multiple TMT-labeled samples in one MS/MS experiment. A difficulty encountered when using TMT labeling is the presence of interference in the measured intensities of TMT reporter ions. To correct for interference, we employed in the proposed method a modified version of the expectation maximization (EM) algorithm that redistributes the signal from ion interference back to the correct TMT-labeled samples. We have evaluated the sensitivity and specificity of the proposed method using 94 MS/MS experiments (covering a broad range of protein concentration ratios across TMT-labeled channels and experimental parameters), containing a total of 1931 true positive TMT-labeled channels and 317 true negative TMT-labeled channels. The results of the evaluation show that the proposed method has an identification sensitivity of 93-97% and a specificity of 100% at the species level. Furthermore, as a proof of concept, using an in-house-generated data set composed of some of the most common urinary tract pathogens, we demonstrated that by using the proposed method the mass spectrometer time required per sample, using a 1 h LC-MS/MS run, can be reduced to 10 and 6 min when samples are labeled with TMT-6 and TMT-10, respectively. The proposed method can also be used along with Orbitrap mass spectrometers that have faster MS/MS acquisition rates, like the recently released Orbitrap Astral mass spectrometer, to further reduce the mass spectrometer time required per sample.
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Affiliation(s)
- Gelio Alves
- National
Center for Biotechnology Information, National Library of Medicine,
National Institutes of Health, Bethesda, Maryland 20894, United States
| | - Aleksey Y. Ogurtsov
- National
Center for Biotechnology Information, National Library of Medicine,
National Institutes of Health, Bethesda, Maryland 20894, United States
| | - Harry Porterfield
- Department
of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - Tapan Maity
- Laboratory
of Cell Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - Lisa M. Jenkins
- Laboratory
of Cell Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - David B. Sacks
- Department
of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - Yi-Kuo Yu
- National
Center for Biotechnology Information, National Library of Medicine,
National Institutes of Health, Bethesda, Maryland 20894, United States
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4
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Tao Y, Liu Q, Cheng N. Sea hedgehog-inspired surface-enhanced Raman scattering biosensor probe for ultrasensitive determination of Staphylococcus aureus in food supplements. Biosens Bioelectron 2024; 252:116146. [PMID: 38417286 DOI: 10.1016/j.bios.2024.116146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 02/16/2024] [Accepted: 02/19/2024] [Indexed: 03/01/2024]
Abstract
Staphylococcus aureus contamination in food supplements poses substantial challenges to public health and large-scale production but the sensitive detection in a timely manner remains a bottleneck. Drawing inspiration from the sea hedgehog, gold nanostars (AuNSs) were leveraged to design an ultrasensitive surface-enhanced Raman scattering (SERS) biosensor for the determination of Staphylococcus aureus in food supplements. Besides the surface enhancement furnished by the AuNSs, Raman reporter molecules and specific aptamers sequentially self-assembled onto these AuNSs to construct the "three-in-one" SERS biosensor probe for label-based quantitation of Staphylococcus aureus. Following incubation with contaminated health product samples, the gold nanostars@Raman reporter-aptamer specifically recognize and assemble around Staphylococcus aureus cells, forming a distinctive sea hedgehog structure. This unique configuration results in an amplified Raman signal at 1338 cm-1 and an enhancement factor of up to 6.71 × 107. The entire quantitative detection process can be completed within 30 min, boasting an exceptional limit of detection as low as 1.0 CFU mL-1. The method exhibits a broad working range for the determination of Staphylococcus aureus, with concentrations spanning 2.15 CFU mL-1 to 2.15 × 105 CFU mL-1. Furthermore, it demonstrates outstanding precision, with relative standard deviation values consistently below 5.0%. As a showcase to validate the practicality of the SERS method, we conducted tests on determining Staphylococcus aureus in a herbal food supplement, i.e., Ginkgo Biloba extract (GBE); the results align closely with those obtained through the conventional lysogeny broth agar plate method, pointing to the potential applicability in real-world scenarios.
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Affiliation(s)
- Yi Tao
- College of Pharmaceutical Science, Zhejiang University of Technology, Hangzhou, Zhejiang, 310032, China.
| | - Qing Liu
- College of Pharmaceutical Science, Zhejiang University of Technology, Hangzhou, Zhejiang, 310032, China
| | - Ningtao Cheng
- School of Public Health, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310058, China.
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Jones KL, Cunha F, Casaro S, Galvão KN. Optimization and Testing of a Commercial Viability PCR Protocol to Detect Escherichia coli in Whole Blood. Microorganisms 2024; 12:765. [PMID: 38674709 PMCID: PMC11052410 DOI: 10.3390/microorganisms12040765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 04/04/2024] [Accepted: 04/08/2024] [Indexed: 04/28/2024] Open
Abstract
Bacteremia, specifically if progressed to sepsis, poses a time-sensitive threat to human and animal health. Escherichia coli is a main causative agent of sepsis in humans. The objective was to evaluate a propidium monoazide (PMA)-based viability PCR (vPCR) protocol to detect and quantify live E. coli from whole blood. We optimized the protocol by adding a eukaryotic-specific lysis step prior to PMA exposure, then used spiking experiments to determine the lower limit of detection (LOD) and linear range of quantification. We also compared the vPCR quantification method to standard colony count of spiked inoculum. Lastly, we calculated percent viability in spiked samples containing 50% live cells or 0% live cells. The LOD was 102 CFU/mL for samples containing live cells only and samples with mixed live and heat-killed cells. The linear range of quantification was 102 CFU/mL to 108 CFU/mL (R2 of 0.997) in samples containing only live cells and 103 CFU/mL to 108 CFU/mL (R2 of 0.998) in samples containing live plus heat-killed cells. A Bland-Altman analysis showed that vPCR quantification overestimates compared to standard plate count of the spiked inoculum, with an average bias of 1.85 Log10 CFU/mL across the linear range when only live cells were present in the sample and 1.98 Log10 CFU/mL when live plus heat-killed cells were present. Lastly, percent viability calculations showed an average 89.5% viable cells for samples containing 50% live cells and an average 19.3% for samples containing 0% live cells. In summary, this optimized protocol can detect and quantify viable E. coli in blood in the presence of heat-killed cells. Additionally, the data presented here provide the groundwork for further development of vPCR to detect and quantify live bacteria in blood in clinical settings.
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Affiliation(s)
| | | | | | - Klibs N. Galvão
- Department of Large Animal Clinical Sciences, University of Florida College of Veterinary Medicine, Gainesville, FL 32608, USA
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6
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Ogurtsov A, Alves G, Rubio A, Joyce B, Andersson B, Karlsson R, Moore ER, Yu YK. MiCId GUI: The Graphical User Interface for MiCId, a Fast Microorganism Classification and Identification Workflow with Accurate Statistics and High Recall. J Comput Biol 2024; 31:175-178. [PMID: 38301204 PMCID: PMC10874827 DOI: 10.1089/cmb.2023.0149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2024] Open
Abstract
Although many user-friendly workflows exist for identifications of peptides and proteins in mass-spectrometry-based proteomics, there is a need of easy to use, fast, and accurate workflows for identifications of microorganisms, antimicrobial resistant proteins, and biomass estimation. Identification of microorganisms is a computationally demanding task that requires querying thousands of MS/MS spectra in a database containing thousands to tens of thousands of microorganisms. Existing software can't handle such a task in a time efficient manner, taking hours to process a single MS/MS experiment. Another paramount factor to consider is the necessity of accurate statistical significance to properly control the proportion of false discoveries among the identified microorganisms, and antimicrobial-resistant proteins, and to provide robust biomass estimation. Recently, we have developed Microorganism Classification and Identification (MiCId) workflow that assigns accurate statistical significance to identified microorganisms, antimicrobial-resistant proteins, and biomass estimation. MiCId's workflow is also computationally efficient, taking about 6-17 minutes to process a tandem mass-spectrometry (MS/MS) experiment using computer resources that are available in most laptop and desktop computers, making it a portable workflow. To make data analysis accessible to a broader range of users, beyond users familiar with the Linux environment, we have developed a graphical user interface (GUI) for MiCId's workflow. The GUI brings to users all the functionality of MiCId's workflow in a friendly interface along with tools for data analysis, visualization, and to export results.
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Affiliation(s)
- Aleksey Ogurtsov
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA
| | - Gelio Alves
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA
| | - Alex Rubio
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA
| | - Brendan Joyce
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA
| | - Björn Andersson
- Bioinformatics Core Facility, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Roger Karlsson
- Department of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Nanoxis Consulting AB, Gothenburg, Sweden
| | - Edward R.B. Moore
- Department of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Culture Collection University of Gothenburg, Sahlgrenska Academy, University of Gothenburg, Sweden
| | - Yi-Kuo Yu
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA
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7
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Bankvall M, Carda-Diéguez M, Mira A, Karlsson A, Hasséus B, Karlsson R, Robledo-Sierra J. Metataxonomic and metaproteomic profiling of the oral microbiome in oral lichen planus - a pilot study. J Oral Microbiol 2022; 15:2161726. [PMID: 36605405 PMCID: PMC9809343 DOI: 10.1080/20002297.2022.2161726] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
Background A growing body of evidence demonstrates a different bacterial composition in the oral cavity of patients with oral lichen planus (OLP). Patients and methods Buccal swab samples were collected from affected and non-affected sites of six patients with reticular OLP and the healthy oral mucosa of six control subjects. 16S rRNA gene MiSeq sequencing and mass spectrometry-based proteomics were utilised to identify the metataxonomic and metaproteomic profiles of the oral microbiome in both groups. Results From the metataxonomic analysis, the most abundant species in the three subgroups were Streptococcus oralis and Pseudomonas aeruginosa, accounting for up to 70% of the total population. Principal Coordinates Analysis showed differential clustering of samples from the healthy and OLP groups. ANCOM-BC compositional analysis revealed multiple species (including P. aeruginosa and several species of Veillonella, Prevotella, Streptococcus and Neisseria) significantly over-represented in the control group and several (including Granulicatella elegans, Gemella haemolysans and G. parahaemolysans) in patients with OLP. The metaproteomic data were generally congruent and revealed that several Gemella haemolysans-belonging peptidases and other proteins with inflammatory and virulence potential were present in OLP lesions. Conclusion Our data suggest that several bacterial species are associated with OLP. Future studies with larger cohorts should be conducted to determine their role in the aetiology of OLP and evaluate their potential as disease biomarkers.
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Affiliation(s)
- Maria Bankvall
- Department of Dental Medicine, Karolinska Institute, Huddinge, Sweden
| | - Miguel Carda-Diéguez
- Department of Health and Genomics, Center for Advanced Research in Public Health, FISABIO Foundation, Valencia, Spain
| | - Alex Mira
- Department of Health and Genomics, Center for Advanced Research in Public Health, FISABIO Foundation, Valencia, Spain,School of Health and Welfare, Jönköping University, Jönköping, Sweden
| | | | - Bengt Hasséus
- Department of Oral Medicine and Pathology, Institute of Odontology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Roger Karlsson
- Clinical microbiology, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Jairo Robledo-Sierra
- Nanoxis Consulting AB, Gothenburg, Sweden,Faculty of Dentistry, CES University, Medellin, Colombia,CONTACT Jairo Robledo-Sierra Faculty of Dentistry, CES University, Medellin, Colombia
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8
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Alves G, Ogurtsov A, Karlsson R, Jaén-Luchoro D, Piñeiro-Iglesias B, Salvà-Serra F, Andersson B, Moore ERB, Yu YK. Identification of Antibiotic Resistance Proteins via MiCId's Augmented Workflow. A Mass Spectrometry-Based Proteomics Approach. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2022; 33:917-931. [PMID: 35500907 PMCID: PMC9164240 DOI: 10.1021/jasms.1c00347] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 02/17/2022] [Accepted: 02/18/2022] [Indexed: 06/01/2023]
Abstract
Fast and accurate identifications of pathogenic bacteria along with their associated antibiotic resistance proteins are of paramount importance for patient treatments and public health. To meet this goal from the mass spectrometry aspect, we have augmented the previously published Microorganism Classification and Identification (MiCId) workflow for this capability. To evaluate the performance of this augmented workflow, we have used MS/MS datafiles from samples of 10 antibiotic resistance bacterial strains belonging to three different species: Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa. The evaluation shows that MiCId's workflow has a sensitivity value around 85% (with a lower bound at about 72%) and a precision greater than 95% in identifying antibiotic resistance proteins. In addition to having high sensitivity and precision, MiCId's workflow is fast and portable, making it a valuable tool for rapid identifications of bacteria as well as detection of their antibiotic resistance proteins. It performs microorganismal identifications, protein identifications, sample biomass estimates, and antibiotic resistance protein identifications in 6-17 min per MS/MS sample using computing resources that are available in most desktop and laptop computers. We have also demonstrated other use of MiCId's workflow. Using MS/MS data sets from samples of two bacterial clonal isolates, one being antibiotic-sensitive while the other being multidrug-resistant, we applied MiCId's workflow to investigate possible mechanisms of antibiotic resistance in these pathogenic bacteria; the results showed that MiCId's conclusions agree with the published study. The new version of MiCId (v.07.01.2021) is freely available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.
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Affiliation(s)
- Gelio Alves
- National
Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, United States
| | - Aleksey Ogurtsov
- National
Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, United States
| | - Roger Karlsson
- Department
of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, 40530 Gothenburg, Sweden
- Department
of Clinical Microbiology, Sahlgrenska University
Hospital, 40234 Gothenburg, Sweden
- Center
for Antibiotic Resistance Research (CARe), University of Gothenburg, 40016 Gothenburg, Sweden
- Nanoxis
Consulting AB, 40234 Gothenburg, Sweden
| | - Daniel Jaén-Luchoro
- Department
of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, 40530 Gothenburg, Sweden
- Center
for Antibiotic Resistance Research (CARe), University of Gothenburg, 40016 Gothenburg, Sweden
- Culture Collection
University of Gothenburg (CCUG), Sahlgrenska
Academy of the University of Gothenburg, 40234 Gothenburg, Sweden
| | - Beatriz Piñeiro-Iglesias
- Department
of Clinical Microbiology, Sahlgrenska University
Hospital, 40234 Gothenburg, Sweden
- Center
for Antibiotic Resistance Research (CARe), University of Gothenburg, 40016 Gothenburg, Sweden
| | - Francisco Salvà-Serra
- Department
of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, 40530 Gothenburg, Sweden
- Department
of Clinical Microbiology, Sahlgrenska University
Hospital, 40234 Gothenburg, Sweden
- Center
for Antibiotic Resistance Research (CARe), University of Gothenburg, 40016 Gothenburg, Sweden
- Culture Collection
University of Gothenburg (CCUG), Sahlgrenska
Academy of the University of Gothenburg, 40234 Gothenburg, Sweden
- Microbiology,
Department of Biology, University of the
Balearic Islands, 07122 Palma de Mallorca, Spain
| | - Björn Andersson
- Bioinformatics
Core Facility at Sahlgrenska Academy, University
of Gothenburg, Box 413, 40530 Gothenburg, Sweden
| | - Edward R. B. Moore
- Department
of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, 40530 Gothenburg, Sweden
- Department
of Clinical Microbiology, Sahlgrenska University
Hospital, 40234 Gothenburg, Sweden
- Center
for Antibiotic Resistance Research (CARe), University of Gothenburg, 40016 Gothenburg, Sweden
- Culture Collection
University of Gothenburg (CCUG), Sahlgrenska
Academy of the University of Gothenburg, 40234 Gothenburg, Sweden
| | - Yi-Kuo Yu
- National
Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, United States
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