Rapid discrimination of klebsiella pneumoniae carbapenemase 2 – producing and non-producing klebsiella pneumoniae strains using near-infrared spectroscopy (NIRS) and multivariate analysis

Near-infrared spectroscopy as a feasible method for the differentiation of Neisseria gonorrhoeae from Neisseria commensals and antimicrobial resistant from susceptible gonococcal strains

Rapid and cost-effective diagnosis of Neisseria gonorrhoeae (NG) are important measures for the control and management of gonococcal infection. Current diagnostic tools such as nucleic acid amplification tests and bacterial culture are not feasible in many resource-poor settings, and so syndromic patient management is commonplace. Alternative cost-effective diagnostic tools are therefore needed. Here, we sought to explore the utility and feasibility of Near Infrared Spectroscopy (NIRS) to (1) identify and differentiate NG from Neisseria commensals and (2) to differentiate fully susceptible NG from resistant NG. NIRS correctly classified NG from Neisseria commensals (R²= 0.89; SECV 0.164) and to a lesser capacity, susceptible NG from resistant (R² = 0.60; SECV 0.32). To the best our knowledge, this is the first proof of concept study in the field. Further evaluations are now warranted to enhance capacity and accuracy of this diagnostic approach.

Near-infrared spectroscopy of blood plasma with chemometrics towards HIV discrimination during pregnancy

Prevention of mother-to-child transmission programs have been one of the hallmarks of success in the fight against HIV/AIDS. In Brazil, access to antiretroviral therapy (ART) during pregnancy has increased, leading to a reduction in new infections among children. Currently, lifelong ART is available to all pregnant, however yet challenges remain in eliminating mother-to-child transmission. In this paper, we focus on the role of near-infrared (NIR) spectroscopy to analyse blood plasma samples of pregnant women with HIV infection to differentiate pregnant women without HIV infection. Seventy-seven samples (39 HIV-infected patient and 38 healthy control samples) were analysed. Multivariate classification of resultant NIR spectra facilitated diagnostic segregation of both sample categories in a fast and non-destructive fashion, generating good accuracy, sensitivity and specificity. This method is simple and low-cost, and can be easily adapted to point-of-care screening, which can be essential to monitor pregnancy risks in remote locations or in the developing world. Therefore, it opens a new perspective to investigate vertical transmission (VT). The approach described here, can be useful for the identification and exploration of VT under various pathophysiological conditions of maternal HIV. These findings demonstrate, for the first time, the potential of NIR spectroscopy combined with multivariate analysis as a screening tool for fast and low-cost HIV detection.

Potential of FTIR-Spectroscopy for Drugs Screening against Helicobacter pylori

Helicobacter pylori colonizes the human stomach of half of the world's population. The infection if not treated, persists through life, leading to chronic gastric inflammation, that may progress to severe diseases as peptic ulcer, gastric adenocarcinoma, and mucosa-associated lymphoid tissue lymphoma. The first line of treatment, based on 7 to 21 days of two antibiotics associated with a proton pump inhibitor, is, however, already failing most due to patient non-compliance that leads to antibiotic resistance. It is, therefore, urgent to screen for new and more efficient antimicrobials against this bacterium. In this work, Fourier Transform Infrared (FTIR) spectroscopy was evaluated to screen new drugs against H. pylori, in rapid (between 1 to 6 h), and high-throughput mode and based on a microliter volume processes in relation to the agar dilution method. The reference H. pylori strains 26,695 and J99, were evaluated against a peptide-based antimicrobial and the clinical antibiotic clarithromycin, respectively. After optimization of the assay conditions, as the composition of the incubation mixture, the time of incubation, and spectral pre-processing, it was possible to reproducibly observe the effect of the drug on the bacterial molecular fingerprint as pointed by the spectra principal component analysis. The spectra, obtained from both reference strains, after its incubation with drugs concentrations lower than the MIC, presented peak ratios statistically different (p < 0.05) in relation to the bacteria incubated with drugs concentrations equal or higher to the MIC. It was possible to develop a partial least square regression model, enabling to predict from spectra of both bacteria strains, the drug concentration on the assay, with a high correlation coefficient between predicted and experimental data (0.91) and root square error of 40% of the minimum inhibitory concentration. All this points to the high potential of the technique for drug screening against this fastidious growth bacterium.

Occurrence of wooden breast and white striping in Brazilian slaughtering plants and use of near-infrared spectroscopy and multivariate analysis to identify affected chicken breasts

White Striping (WS) and Wooden Breast (WB) are emerging poultry myopathies that occur worldwide, affecting the quality of meat. The aim of this study was to evaluate the occurrence of N, WS, WB, and WS/WB (myopathies combined) in chicken breast from Brazilian commercial plant, comparing (1) inspection based on visual aspect and palpation of Pectoralis major muscle, and (2) identification of these myopathies by near-infrared Spectroscopy (NIRS). Chickens slaughtered at Brazilian commercial plant at four age ranges (4 to 5, 6 to 7, 8 to 9, and 65 weeks) were inspected. Spectral information was acquired using a portable NIR spectrometer, and classification models were performed using and Successive Projection Algorithm-Linear Discriminant Analysis (SPA-LDA) and Soft Independent Modeling of Class Analogy (SIMCA) to distinguish normal and affected muscles. Results showed that occurrence of myopathies was aggravated by age of slaughter, as chicken slaughtered at 4 to 5 and 65 weeks exhibited 13.6 and 95% of myopathies, respectively. Birds slaughtered at 65 weeks showed no occurrence of WB, isolated or combined with WS. It was not possible to differentiate the WB and WS/WB classes; therefore, those samples were grouped (WB+WS/WB). SPA-LDA model showed greater accuracy (92 to 93%) in identifying Normal (N), WS, and WB+WS/WB groups, compared to SIMCA (89 to 91%). It can be concluded that the level of occurrence of myopathies in meat is directly related to the age of slaughter. This study demonstrated that NIRS combined with SPA-LDA model could be used as a tool to detect myopathies in chicken breast. This technique has potential for application in industrial processing lines as an alternative to the traditional methods of identification. PRACTICAL APPLICATION: This study shows that NIRS combined with chemometric techniques can be used to identify chicken breast myopathies in a wide range of ages at slaughter. In addition to being able to discriminate chicken muscles into subclasses, namely, Normal, WS, and WB/WB+WS, this technique has potential for application in industrial processing lines as it is a portable and nondestructive method. This procedure is emphasized as an alternative to the conventional method of identification based on palpation and visual assessment of muscle.

Near-Infrared Spectroscopy Evaluations for the Differentiation of Carbapenem-Resistant from Susceptible Enterobacteriaceae Strains

Antimicrobial Resistance (AMR) caused by Carbapenem-Resistant Enterobacteriaceae (CRE) is a global threat. Accurate identification of these bacterial species with associated AMR is critical for their management. While highly accurate methods to detect CRE are available, they are costly, timely and require expert skills, making their application infeasible in low-resource settings. Here, we investigated the potential of Near-Infrared Spectroscopy (NIRS) for a range of applications: (i) the detection and differentiation of isolates of two pathogenic Enterobacteriaceae species, Klebsiella pneumoniae and Escherichia coli, and (ii) the differentiation of carbapenem resistant and susceptible K. pneumoniae. NIRS has successfully differentiated between K. pneumoniae and E. coli isolates with a predictive accuracy of 89.04% (95% CI; 88.7–89.4%). K. pneumoniae isolates harbouring carbapenem-resistance determinants were differentiated from susceptible K. pneumoniae strains with an accuracy of 85% (95% CI; 84.2–86.1%). To our knowledge, this is the largest proof of concept demonstration for the utility and feasibility of NIRS to rapidly differentiate between K. pneumoniae and E. coli as well as carbapenem-resistant K. pneumoniae from susceptible strains.

Prevalence of Resistance to β-Lactam Antibiotics and bla Genes Among Commensal Haemophilus parainfluenzae Isolates from Respiratory Microbiota in Poland

(1) Background: Beta-lactams are the most frequently used antimicrobials, and are the first-line drugs in many infectious diseases, e.g., pneumonia, otitis media. Due to this fact, various bacteria have developed resistance to this group of drugs. (2) Methods: Eighty-seven Haemophilus parainfluenzae isolates were obtained from adults 18–70 years old in eastern Poland. The presence of 10 bla genes and 2 substitutions in ftsI reported as the most frequent in H. parainfluenzae were analyzed. (3) Results: Among 57 beta-lactam-resistant isolates, 63.2% encoded bla genes; bla_TEM-1 predominated (54.4%), followed by bla_OXA (19.3%), bla_DHA (12.3%), bla_SHV (10.5%), bla_GES (7.0%), bla_CMY (5.3%), bla_VEB (1.8%) and bla_ROB-1 (1.8%). Lys-526 was the most common substitution in ftsI gene. The resistance genotypes were as follows: gBLNAS (17.5%), low-gBLNAR I (1.8%), low-gBLNAR II (1.8%), gBLNAR II (15.8%), gBLPAS (15.8%), gBLPAR (19.3%), gBLPBS I (8.8%) and gBLPBS II (1.8%); (4) Conclusions: This has been the first study to report on the high diversity of bla genes in H. parainfluenzae isolates in Poland. High sensitivity and specificity of benzylpenicillin test, as well as PCR of bla genes were shown, indicating that these methods may be useful as tools for the rapid screening of beta-lactamase prevalence and resistance to beta-lactams among H. parainfluenzae isolated from respiratory microbiota.

Advances in chemometric control of commercial diesel adulteration by kerosene using IR spectroscopy

Adulteration is a recurrent issue found in fuel screening. Commercial diesel contamination by kerosene is highly difficult to be detected via physicochemical methods applied in market. Although the contamination may affect diesel quality and storage stability, there is a lack of efficient methodologies for this evaluation. This paper assessed the use of IR spectroscopies (MIR and NIR) coupled with partial least squares (PLS) regression, support vector machine regression (SVR), and multivariate curve resolution with alternating least squares (MCR-ALS) calibration models for quantifying and identifying the presence of kerosene adulterant in commercial diesel. Moreover, principal component analysis (PCA), successive projections algorithm (SPA), and genetic algorithm (GA) tools coupled to linear discriminant analysis were used to observe the degradation behavior of 60 samples of pure and kerosene-added diesel fuel in different concentrations over 60 days of storage. Physicochemical properties of commercial diesel with 15% kerosene remained within conformity with Brazilian screening specifications; in addition, specified tests were not able to identify changes in the blends' performance over time. By using multivariate classification, the samples of pure and contaminated fuel were accurately classified by aging level into two well-defined groups, and some spectral features related to fuel degradation products were detected. PLS and SVR were accurate to quantify kerosene in the 2.5-40% (v/v) range, reaching RMSEC < 2.59% and RMSEP < 5.56%, with high correlation between real and predicted concentrations. MCR-ALS with correlation constraint was able to identify and recover the spectral profile of commercial diesel and kerosene adulterant from the IR spectra of contaminated blends.

Near-infrared spectroscopy (NIRS) as a tool to monitor exhaust air from poultry operations

Intensive poultry operation systems emit a considerable volume of inorganic and organic matter in the surrounding environment. Monitoring cleaning properties of exhaust air cleaning systems and to detect small but significant changes in emission characteristics during a fattening cycle is important for both emission and fattening process control. In the present study, we evaluated the potential of near-infrared spectroscopy (NIRS) combined with chemometric techniques as a monitoring tool of exhaust air from poultry operation systems. To generate a high-quality data set for evaluation, the exhaust air of two poultry houses was sampled by applying state-of-the-art filter sampling protocols. The two stables were identical except for one crucial difference, the presence or absence of an exhaust air cleaning system. In total, twenty-one exhaust air samples were collected at the two sites to monitor spectral differences caused by the cleaning device, and to follow changes in exhaust air characteristics during a fattening period. The total dust load was analyzed by gravimetric determination and included as a response variable in multivariate data analysis. The filter samples were directly measured with NIR spectroscopy. Principal component analysis (PCA), linear discriminant analysis (LDA), and factor analysis (FA) were effective in classifying the NIR exhaust air spectra according to fattening day and origin. The results indicate that the dust load and the composition of exhaust air (inorganic or organic matter) substantially influence the NIR spectral patterns. In conclusion, NIR spectroscopy as a tool is a promising and very rapid way to detect differences between exhaust air samples based on still not clearly defined circumstances triggered during a fattening period and the availability of an exhaust air cleaning system.

Spectrophotometric techniques for the characterization of strains involved in the blue pigmentation of food: Preliminary results

Near infrared spectroscopy (NIRs) and ultraviolet visible spectroscopy (UV-vis) have been investigated as rapid techniques to characterize foodborne bacteria through the analysis of the spectra of whole cells or microbial suspensions. The use of spectra collected from broth cultures could be used as a fingerprint for strain classification using a combined polyphasic approach. The aim of this study was to evaluate the feasibility of NIRs and UV-vis for the characterization of blue strains belonging to the Pseudomonas fluorescens group. The bacteria were isolated from different food matrices, including some spoiled samples (blue discoloration). Eightyone strains previously identified at the species level were grown in Minimal Bacterial Medium broth under standard conditions at 22°C. Two biological replicates were centrifuged in order to separate the bacterial cells from the extracellular products. Six aliquots per strain were analyzed on a small ring cup in transflectance mode (680-2500 nm, gap 2 nm). A subset of 39 strains was evaluated by UV-vis to determine changes in the spectral characteristics at 48 and 72 hours. Several chemometric approaches were tested to assess the performance of NIRs and UVvis. According to the variable importance in projection (VIP), the 1892-2020 nm spectral region showed the highest level of discrimination between blue strains and others. Additional information was provided in the 680-886 and 1454-1768 nm regions (aromatic C-H bonds) and in the 2036-2134 nm region (fatty acids). Changes in UV-vis spectral data (at 48 and 72 hours) appear to indicate the presence of phenazine and catecholic compounds in extracellular products.

Spectroscopy with computational analysis in virological studies: A decade (2006-2016)

This review presents a retrospective of the studies carried out in the last 10 years (2006–2016) using spectroscopic methods as a research tool in the field of virology. Spectroscopic analyses are sensitive to variations in the biochemical composition of the sample, are non-destructive, fast and require the least sample preparation, making spectroscopic techniques tools of great interest in biological studies. Herein important chemometric algorithms that have been used in virological studies are also evidenced as a good alternative for analyzing the spectra, discrimination and classification of samples. Techniques that have not yet been used in the field of virology are also suggested. This methodology emerges as a new and promising field of research, and may be used in the near future as diagnosis tools for detecting diseases caused by viruses.

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A retrospective study of 2006–2016 using spectroscopic methods as a research tool in the field of virology.

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Chemometric algorithms used in virological studies were evidenced.

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This review emerges as a new and promising field of research in virology.

ATR-FTIR spectroscopy coupled with multivariate analysis techniques for the identification of DENV-3 in different concentrations in blood and serum: a new approach

In most cases of virus infections the viral load is directly related to the intensity of the disease.