1
|
Masucci EM, Hauschild JE, Gisler HM, Lester EM, Balss KM. Raman spectroscopy as an alternative rapid microbial bioburden test method for continuous, automated detection of contamination in biopharmaceutical drug substance manufacturing. J Appl Microbiol 2024; 135:lxae188. [PMID: 39054049 DOI: 10.1093/jambio/lxae188] [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: 05/30/2024] [Revised: 07/10/2024] [Accepted: 07/23/2024] [Indexed: 07/27/2024]
Abstract
AIMS To investigate an in-line Raman method capable of detecting accidental microbial contamination in pharmaceutical vessels, such as bioreactors producing monoclonal antibodies via cell culture. METHODS AND RESULTS The Raman method consists of a multivariate model built from Raman spectra collected in-line during reduced-scale bioreactor batches producing a monoclonal antibody, as well as a reduced-scale process with intentional spiking of representative compendial method microorganisms (n = 4). The orthogonal partial least squares regression discriminant analysis model (OPLS-DA) area under the curve (AUC), specificity and sensitivity were 0.96, 0.99, and 0.95, respectively. Furthermore, the model successfully detected contamination in an accidentally contaminated manufacturing-scale batch. In all cases, the time to detection (TTD) for Raman was superior compared to offline, traditional microbiological culturing. CONCLUSIONS The Raman OPLS-DA method met acceptance criteria for equivalent decision making to be considered a viable alternative to the compendial method for in-process bioburden testing. The in-line method is automated, non-destructive, and provides a continuous assessment of bioburden compared to an offline compendial method, which is manual, results in loss of product, and in practice is only collected once daily and requires 3-5 days for enumeration.
Collapse
Affiliation(s)
- Erin M Masucci
- Emerging Technologies, Manufacturing Science and Technology Janssen Pharmaceuticals Inc., Welsh and McKean Roads, Spring House, PA 19477, USA
| | - James E Hauschild
- Microbiological Quality and Sterility Assurance Johnson & Johnson Services, Inc., Raritan, NJ 08869, USA
| | - Helena M Gisler
- Emerging Technologies, Manufacturing Science and Technology Janssen Pharmaceuticals Inc., Welsh and McKean Roads, Spring House, PA 19477, USA
| | - Erin M Lester
- Emerging Technologies, Manufacturing Science and Technology Janssen Pharmaceuticals Inc., Welsh and McKean Roads, Spring House, PA 19477, USA
| | - Karin M Balss
- Emerging Technologies, Manufacturing Science and Technology Janssen Pharmaceuticals Inc., Welsh and McKean Roads, Spring House, PA 19477, USA
| |
Collapse
|
2
|
Dahal N, Peak C, Ehrett C, Osterberg J, Cao M, Divan R, Wang P. Microwave Flow Cytometric Detection and Differentiation of Escherichia coli. SENSORS (BASEL, SWITZERLAND) 2024; 24:2870. [PMID: 38732977 PMCID: PMC11086155 DOI: 10.3390/s24092870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 04/24/2024] [Accepted: 04/26/2024] [Indexed: 05/13/2024]
Abstract
Label-free measurement and analysis of single bacterial cells are essential for food safety monitoring and microbial disease diagnosis. We report a microwave flow cytometric sensor with a microstrip sensing device with reduced channel height for bacterial cell measurement. Escherichia coli B and Escherichia coli K-12 were measured with the sensor at frequencies between 500 MHz and 8 GHz. The results show microwave properties of E. coli cells are frequency-dependent. A LightGBM model was developed to classify cell types at a high accuracy of 0.96 at 1 GHz. Thus, the sensor provides a promising label-free method to rapidly detect and differentiate bacterial cells. Nevertheless, the method needs to be further developed by comprehensively measuring different types of cells and demonstrating accurate cell classification with improved machine-learning techniques.
Collapse
Affiliation(s)
- Neelima Dahal
- Holcombe Department of Electrical and Computer Engineering, Clemson University, Clemson, SC 29634, USA; (N.D.); (J.O.)
| | - Caroline Peak
- Department of Bioengineering, Clemson University, Clemson, SC 29634, USA;
| | - Carl Ehrett
- Watt Family Innovation Center, Clemson University, Clemson, SC 29634, USA;
| | - Jeffrey Osterberg
- Holcombe Department of Electrical and Computer Engineering, Clemson University, Clemson, SC 29634, USA; (N.D.); (J.O.)
| | - Min Cao
- Department of Biological Sciences, Clemson University, Clemson, SC 29634, USA;
| | - Ralu Divan
- Argonne National Laboratory, Chicago, IL 60439, USA;
| | - Pingshan Wang
- Holcombe Department of Electrical and Computer Engineering, Clemson University, Clemson, SC 29634, USA; (N.D.); (J.O.)
| |
Collapse
|
3
|
Frempong SB, Salbreiter M, Mostafapour S, Pistiki A, Bocklitz TW, Rösch P, Popp J. Illuminating the Tiny World: A Navigation Guide for Proper Raman Studies on Microorganisms. Molecules 2024; 29:1077. [PMID: 38474589 DOI: 10.3390/molecules29051077] [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: 12/19/2023] [Revised: 02/13/2024] [Accepted: 02/18/2024] [Indexed: 03/14/2024] Open
Abstract
Raman spectroscopy is an emerging method for the identification of bacteria. Nevertheless, a lot of different parameters need to be considered to establish a reliable database capable of identifying real-world samples such as medical or environmental probes. In this review, the establishment of such reliable databases with the proper design in microbiological Raman studies is demonstrated, shining a light into all the parts that require attention. Aspects such as the strain selection, sample preparation and isolation requirements, the phenotypic influence, measurement strategies, as well as the statistical approaches for discrimination of bacteria, are presented. Furthermore, the influence of these aspects on spectra quality, result accuracy, and read-out are discussed. The aim of this review is to serve as a guide for the design of microbiological Raman studies that can support the establishment of this method in different fields.
Collapse
Affiliation(s)
- Sandra Baaba Frempong
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
| | - Markus Salbreiter
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
| | - Sara Mostafapour
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Aikaterini Pistiki
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance-Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany
| | - Thomas W Bocklitz
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance-Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany
| | - Petra Rösch
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
| | - Jürgen Popp
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance-Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany
- Cluster of Excellence Balance of the Microverse, Friedrich Schiller University Jena, 07743 Jena, Germany
| |
Collapse
|
4
|
Kalpana S, Lin WY, Wang YC, Fu Y, Lakshmi A, Wang HY. Antibiotic Resistance Diagnosis in ESKAPE Pathogens-A Review on Proteomic Perspective. Diagnostics (Basel) 2023; 13:1014. [PMID: 36980322 PMCID: PMC10047325 DOI: 10.3390/diagnostics13061014] [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: 02/07/2023] [Revised: 02/26/2023] [Accepted: 02/28/2023] [Indexed: 03/11/2023] Open
Abstract
Antibiotic resistance has emerged as an imminent pandemic. Rapid diagnostic assays distinguish bacterial infections from other diseases and aid antimicrobial stewardship, therapy optimization, and epidemiological surveillance. Traditional methods typically have longer turn-around times for definitive results. On the other hand, proteomic studies have progressed constantly and improved both in qualitative and quantitative analysis. With a wide range of data sets made available in the public domain, the ability to interpret the data has considerably reduced the error rates. This review gives an insight on state-of-the-art proteomic techniques in diagnosing antibiotic resistance in ESKAPE pathogens with a future outlook for evading the "imminent pandemic".
Collapse
Affiliation(s)
- Sriram Kalpana
- Department of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan 333423, Taiwan
| | | | - Yu-Chiang Wang
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Yiwen Fu
- Department of Medicine, Kaiser Permanente Santa Clara Medical Center, Santa Clara, CA 95051, USA
| | - Amrutha Lakshmi
- Department of Biochemistry, University of Madras, Guindy Campus, Chennai 600025, India
| | - Hsin-Yao Wang
- Department of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan 333423, Taiwan
| |
Collapse
|
5
|
Dina NE, Tahir MA, Bajwa SZ, Amin I, Valev VK, Zhang L. SERS-based antibiotic susceptibility testing: Towards point-of-care clinical diagnosis. Biosens Bioelectron 2023; 219:114843. [PMID: 36327563 DOI: 10.1016/j.bios.2022.114843] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 08/09/2022] [Accepted: 10/19/2022] [Indexed: 11/06/2022]
Abstract
Emerging antibiotic resistant bacteria constitute one of the biggest threats to public health. Surface-enhanced Raman scattering (SERS) is highly promising for detecting such bacteria and for antibiotic susceptibility testing (AST). SERS is fast, non-destructive (can probe living cells) and it is technologically flexible (readily integrated with robotics and machine learning algorithms). However, in order to integrate into efficient point-of-care (PoC) devices and to effectively replace the current culture-based methods, it needs to overcome the challenges of reliability, cost and complexity. Recently, significant progress has been made with the emergence of both new questions and new promising directions of research and technological development. This article brings together insights from several representative SERS-based AST studies and approaches oriented towards clinical PoC biosensing. It aims to serve as a reference source that can guide progress towards PoC routines for identifying antibiotic resistant pathogens. In turn, such identification would help to trace the origin of sporadic infections, in order to prevent outbreaks and to design effective medical treatment and preventive procedures.
Collapse
Affiliation(s)
- Nicoleta Elena Dina
- Department of Molecular and Biomolecular Department, National Institute for Research and Development of Isotopic and Molecular Technologies, 400293, Cluj-Napoca, Romania.
| | - Muhammad Ali Tahir
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai, 200433, People's Republic of China
| | - Sadia Z Bajwa
- National Institute for Biotechnology and Genetic Engineering (NIBGE), P.O. Box No. 577, Jhang Road, 38000, Faisalabad, Pakistan
| | - Imran Amin
- National Institute for Biotechnology and Genetic Engineering (NIBGE), P.O. Box No. 577, Jhang Road, 38000, Faisalabad, Pakistan
| | - Ventsislav K Valev
- Centre for Photonics and Photonic Materials, Department of Physics, University of Bath, Bath, BA2 7AY, United Kingdom; Centre for Therapeutic Innovation, University of Bath, Bath, United Kingdom; Centre for Nanoscience and Nanotechnology, University of Bath, Bath, United Kingdom.
| | - Liwu Zhang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai, 200433, People's Republic of China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai, 200092, People's Republic of China.
| |
Collapse
|
6
|
Comparison of Different Label-Free Raman Spectroscopy Approaches for the Discrimination of Clinical MRSA and MSSA Isolates. Microbiol Spectr 2022; 10:e0076322. [PMID: 36005817 PMCID: PMC9603629 DOI: 10.1128/spectrum.00763-22] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Methicillin-resistant Staphylococcus aureus (MRSA) is classified as one of the priority pathogens that threaten human health. Resistance detection with conventional microbiological methods takes several days, forcing physicians to administer empirical antimicrobial treatment that is not always appropriate. A need exists for a rapid, accurate, and cost-effective method that allows targeted antimicrobial therapy in limited time. In this pilot study, we investigate the efficacy of three different label-free Raman spectroscopic approaches to differentiate methicillin-resistant and -susceptible clinical isolates of S. aureus (MSSA). Single-cell analysis using 532 nm excitation was shown to be the most suitable approach since it captures information on the overall biochemical composition of the bacteria, predicting 87.5% of the strains correctly. UV resonance Raman microspectroscopy provided a balanced accuracy of 62.5% and was not sensitive enough in discriminating MRSA from MSSA. Excitation of 785 nm directly on the petri dish provided a balanced accuracy of 87.5%. However, the difference between the strains was derived from the dominant staphyloxanthin bands in the MRSA, a cell component not associated with the presence of methicillin resistance. This is the first step toward the development of label-free Raman spectroscopy for the discrimination of MRSA and MSSA using single-cell analysis with 532 nm excitation. IMPORTANCE Label-free Raman spectra capture the high chemical complexity of bacterial cells. Many different Raman approaches have been developed using different excitation wavelength and cell analysis methods. This study highlights the major importance of selecting the most suitable Raman approach, capable of providing spectral features that can be associated with the cell mechanism under investigation. It is shown that the approach of choice for differentiating MRSA from MSSA should be single-cell analysis with 532 nm excitation since it captures the difference in the overall biochemical composition. These results should be taken into consideration in future studies aiming for the development of label-free Raman spectroscopy as a clinical analytical tool for antimicrobial resistance determination.
Collapse
|
7
|
Hussain M, Zou J, Zhang H, Zhang R, Chen Z, Tang Y. Recent Progress in Spectroscopic Methods for the Detection of Foodborne Pathogenic Bacteria. BIOSENSORS 2022; 12:bios12100869. [PMID: 36291007 PMCID: PMC9599795 DOI: 10.3390/bios12100869] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Revised: 10/07/2022] [Accepted: 10/09/2022] [Indexed: 05/06/2023]
Abstract
Detection of foodborne pathogens at an early stage is very important to control food quality and improve medical response. Rapid detection of foodborne pathogens with high sensitivity and specificity is becoming an urgent requirement in health safety, medical diagnostics, environmental safety, and controlling food quality. Despite the existing bacterial detection methods being reliable and widely used, these methods are time-consuming, expensive, and cumbersome. Therefore, researchers are trying to find new methods by integrating spectroscopy techniques with artificial intelligence and advanced materials. Within this progress report, advances in the detection of foodborne pathogens using spectroscopy techniques are discussed. This paper presents an overview of the progress and application of spectroscopy techniques for the detection of foodborne pathogens, particularly new trends in the past few years, including surface-enhanced Raman spectroscopy, surface plasmon resonance, fluorescence spectroscopy, multiangle laser light scattering, and imaging analysis. In addition, the applications of artificial intelligence, microfluidics, smartphone-based techniques, and advanced materials related to spectroscopy for the detection of bacterial pathogens are discussed. Finally, we conclude and discuss possible research prospects in aspects of spectroscopy techniques for the identification and classification of pathogens.
Collapse
Affiliation(s)
- Mubashir Hussain
- School of Materials and Chemical Engineering, Hunan Institute of Engineering, Xiangtan 411104, China
- Postdoctoral Innovation Practice, Shenzhen Polytechnic, Liuxian Avenue, Nanshan District, Shenzhen 518055, China
| | - Jun Zou
- School of Materials and Chemical Engineering, Hunan Institute of Engineering, Xiangtan 411104, China
- Correspondence: (Z.J.); (T.Y.)
| | - He Zhang
- School of Materials and Chemical Engineering, Hunan Institute of Engineering, Xiangtan 411104, China
| | - Ru Zhang
- School of Materials and Chemical Engineering, Hunan Institute of Engineering, Xiangtan 411104, China
| | - Zhu Chen
- Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou 412007, China
| | - Yongjun Tang
- Postdoctoral Innovation Practice, Shenzhen Polytechnic, Liuxian Avenue, Nanshan District, Shenzhen 518055, China
- Correspondence: (Z.J.); (T.Y.)
| |
Collapse
|
8
|
Nakar A, Wagenhaus A, Rösch P, Popp J. Raman spectroscopy for the differentiation of Enterobacteriaceae: a comparison of two methods. Analyst 2022; 147:3938-3946. [DOI: 10.1039/d2an00822j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
A comprehensive dataset of bacteria of the family Enterobacteriaceae was collected and measured with Raman spectroscopy. Fiber-probe based Raman spectroscopy enabled classification with 100% accuracy and remained robust with a validation dataset.
Collapse
Affiliation(s)
- Amir Nakar
- Leibniz Institute of Photonic Technology Jena – Member of the research alliance “Leibniz Health Technologies”, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Germany
- Research Campus Infectognostics, Jena, Germany
| | - Annette Wagenhaus
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Germany
| | - Petra Rösch
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Germany
- Research Campus Infectognostics, Jena, Germany
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology Jena – Member of the research alliance “Leibniz Health Technologies”, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Germany
- Research Campus Infectognostics, Jena, Germany
| |
Collapse
|