Rapid classification of heavy metal-exposed freshwater bacteria by infrared spectroscopy coupled with chemometrics using supervised method

Gurbanov, Rafig; Gözen, Ayşe Gül; Severcan, Feride

doi:10.1016/j.saa.2017.08.038

Cited by 41 publications

(12 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similar results were obtained in studies performed by Holmes et al (2002), involving metabolomic analysis to distinguish between classes expected to show metabolic or genetic differences, for example, controls versus dosed, healthy versus diseased, male versus female, based on their biofluid, or tissue 1 H NMR spectra 31 . Studies performed previously showed the success of infrared spectroscopy associated to SIMCA methods in terms of microbiological classification, as well as suitable discrimination of deletion strains from the wild‐type laboratory strain 32–34 . The SIMCA algorithm showed to be more appropriate for this study, since it is suitable to work with a reduced number of samples per class, and there is no restriction in terms of the number of the measurement variables, which is considered as a significant feature.…”

Section: Resultssupporting

confidence: 84%

Comparison of partial least squares‐discriminant analysis and soft independent modeling of class analogy methods for classification of Saccharomyces cerevisiae cells based on mid‐infrared spectroscopy

Sampaio

Calado

2021

Journal of Chemometrics

View full text Add to dashboard Cite

Saccharomyces cerevisiae is a widely studied and highly utilized eukaryotic organism, ideally suited to high throughput metabolic analysis, being a powerful model for understanding basic cell biology. This study compares the models developed by two supervised methods, such as the partial least squares‐discriminant analysis (PLS‐DA) and soft independent modeling of class analogy (SIMCA), using mid‐infrared (MIR) spectra registered during the growth of S. cerevisiae in bioreactor. The spectra were analyzed using the principal component analysis (PCA), with resolution in five different classes, which were well defined in terms of their biochemical parameters. The SIMCA model showed a significant fitting, 99%, validation, 98%, and prediction parameters, 97%, comparatively with PLS‐DA model. Regarding accuracy, sensitivity, and specificity parameters, a value between 83% and 100% was achieved for both methods, but the SIMCA method showed significant specificity and sensitivity values, 98%–100%, representing a suitable classification tool of yeast cells. According to these results, the MIR spectra associated with chemometric tools can be considered a valued strategy for a classification and detailed analysis for an accurate control, allowing to predict the evolution of the corrected process in advance, avoiding losses of time and costs associated with new fermentations, identifying a significant number of samples in any biotechnological process.

show abstract

Section: Resultssupporting

confidence: 84%

Comparison of partial least squares‐discriminant analysis and soft independent modeling of class analogy methods for classification of Saccharomyces cerevisiae cells based on mid‐infrared spectroscopy

Sampaio

Calado

2021

Journal of Chemometrics

View full text Add to dashboard Cite

show abstract

“…10 µL of sample, corresponding to 5 × 10 5 cells in PBS, was placed on a diamond/ZnSe crystal plate (PerkinElmer) and dried with a mild nitrogen flux for 2 min. Purging samples with non-invasive N 2 was applied in order to remove the overlapping free water bands from the samples (while keeping the bound water in the system), a common procedure in ATR-FTIR studies 84 . PBS, which was used during the sample preparation step, was scanned under identical experimental conditions as the samples.…”

Section: Methodsmentioning

confidence: 99%

Low dose dimethyl sulfoxide driven gross molecular changes have the potential to interfere with various cellular processes

Tunçer

Gurbanov

Sheraj

et al. 2018

Sci Rep

Self Cite

View full text Add to dashboard Cite

Dimethyl sulfoxide (DMSO) is a small molecule with polar, aprotic and amphiphilic properties. It serves as a solvent for many polar and nonpolar molecules and continues to be one of the most used solvents (vehicle) in medical applications and scientific research. To better understand the cellular effects of DMSO within the concentration range commonly used as a vehicle (0.1–1.5%, v/v) for cellular treatments, we applied Attenuated Total Reflectance (ATR) Fourier Transform Infrared (FT-IR) spectroscopy to DMSO treated and untreated epithelial colon cancer cells. Both unsupervised (Principal Component Analysis-PCA) and supervised (Linear Discriminant Analysis-LDA) pattern recognition/modelling algorithms applied to the IR data revealed total segregation and prominent differences between DMSO treated and untreated cells at whole, lipid and nucleic acid regions. Several of these data were supported by other independent techniques. Further IR data analyses of macromolecular profile indicated comprehensive alterations especially in proteins and nucleic acids. Protein secondary structure analysis showed predominance of β-sheet over α-helix in DMSO treated cells. We also observed for the first time, a reduction in nucleic acid level upon DMSO treatment accompanied by the formation of Z-DNA. Molecular docking and binding free energy studies indicated a stabilization of Z-DNA in the presence of DMSO. This alternate DNA form may be related with the specific actions of DMSO on gene expression, differentiation, and epigenetic alterations. Using analytical tools combined with molecular and cellular biology techniques, our data indicate that even at very low concentrations, DMSO induces a number of changes in all macromolecules, which may affect experimental outcomes where DMSO is used as a solvent.

show abstract

“…KNN has no requirement for the data distribution and is robust to noisy training data, and hence, it is suitable for analysing small training sets [33]. SIMCA focuses more on the similarities among samples within a class and is thus widely used for OCC models [34]. SVM is another fitting approach that can be applied to datasets with a limited number of training samples [35].…”

Section: Multivariate Analysis: Determination Of Boundaries For Milk mentioning

confidence: 99%

Prevalence of Milk Fraud in the Chinese Market and its Relationship with Fraud Vulnerabilities in the Chain

Yang

Zhang

Hettinga

et al. 2020

Foods

View full text Add to dashboard Cite

This study aimed to assess the prevalence of ultra-high-temperature (UHT) processed milk samples suspected of being adulterated on the Chinese market and, subsequently, relate their geographical origin to the earlier determined fraud vulnerability. A total of 52 UHT milk samples purchased from the Chinese market were measured to detect possible anomalies. The milk compositional features were determined by standardized Fourier transform-infrared spectroscopy, and the detection limits for common milk adulterations were investigated. The results showed that twelve of the analysed milk samples (23%) were suspected of having quality or fraud-related issues, while one sample of these was highly suspected of being adulterated (diluted with water). Proportionally, more suspected samples were determined among milks produced in the Central-Northern and Eastern areas of China than in those from the North-Western and North-Eastern areas, while those from the South were in between. Combining the earlier collected results on fraud vulnerability in the Chinese milk chains, it appears that increased fraud prevalence relates to poorer business relationships and lack of adequate managerial controls. Since very few opportunities and motivations differ consistently across high and low-prevalence areas, primarily the improvement of control measures can help to mitigate food fraud in the Chinese milk supply chains.

show abstract

Rapid classification of heavy metal-exposed freshwater bacteria by infrared spectroscopy coupled with chemometrics using supervised method

Cited by 41 publications

References 43 publications

Comparison of partial least squares‐discriminant analysis and soft independent modeling of class analogy methods for classification of Saccharomyces cerevisiae cells based on mid‐infrared spectroscopy

Comparison of partial least squares‐discriminant analysis and soft independent modeling of class analogy methods for classification of Saccharomyces cerevisiae cells based on mid‐infrared spectroscopy

Low dose dimethyl sulfoxide driven gross molecular changes have the potential to interfere with various cellular processes

Prevalence of Milk Fraud in the Chinese Market and its Relationship with Fraud Vulnerabilities in the Chain

Contact Info

Product

Resources

About