Visible microspectrophotometry coupled with machine learning to discriminate the erythrocytic life cycle stages of P. falciparum malaria parasites in functional single cells.

Malaria was regarded as the most devastating infectious disease of the 21st century until the COVID-19 pandemic. Asexual blood staged parasites (ABS) play a unique role in ensuring the parasite's survival and pathogenesis. Hitherto, there have been no spectroscopic reports discriminating the life cycle stages of the ABS parasite under physiological conditions. The identification and quantification of the stages in the erythrocytic life cycle is important in monitoring the progression and recovery from the disease. In this study, we explored visible microspectrophotometry coupled to machine learning to discriminate functional ABS parasites at the single cell level. Principal Component Analysis (PCA) showed an excellent discrimination between the different stages of the ABS parasites. Support Vector Machine Analysis provided a 100% prediction for both schizonts and trophozoites, while a 92% and 98% accuracy was achieved for predicting control and ring staged infected RBCs, respectively. This work shows proof of principle for discriminating the life cycle stages of parasites in functional erythrocytes using visible microscopy and thus eliminating the drying and fixative steps that are associated with other optical-based spectroscopic techniques.

Fourier-Transform Infra-Red Microspectroscopy Can Accurately Diagnose Colitis and Assess Severity of Inflammation.

The diagnosis and management of inflammatory bowel disease relies on histological assessment, which is costly, subjective, and lacks utility for point-of-care diagnosis. Fourier-transform infra-red spectroscopy provides rapid, non-destructive, reproducible, and automatable label-free biochemical imaging of tissue for diagnostic purposes. This study characterises colitis using spectroscopy, discriminates colitis from healthy tissue, and classifies inflammation severity. Hyperspectral images were obtained from fixed intestinal sections of a murine colitis model treated with cell therapy to improve inflammation. Multivariate analyses and classification modelling were performed using supervised and unsupervised machine-learning algorithms. Quantitative analysis of severe colitis showed increased protein, collagen, and nucleic acids, but reduced glycogen when compared with normal tissue. A partial least squares discriminant analysis model, including spectra from all intestinal layers, classified normal colon and severe colitis with a sensitivity of 91.4% and a specificity of 93.3%. Colitis severity was classified by a stacked ensemble model yielding an average area under the receiver operating characteristic curve of 0.95, 0.88, 0.79, and 0.85 for controls, mild, moderate, and severe colitis, respectively. Infra-red spectroscopy can detect unique biochemical features of intestinal inflammation and accurately classify normal and inflamed tissue and quantify the severity of inflammation. This is a promising alternative to histological assessment.

A Near-Infrared "Matchbox Size" Spectrometer to Detect and Quantify Malaria Parasitemia.

New point-of-care diagnostic approaches for malaria that are sensitive to low parasitemia, easy to use in a field setting, and affordable are urgently required to meet the World Health Organization's objective of reducing malaria cases and related life losses by 90% globally on or before 2030. In this study, an inexpensive "matchbox size" near-infrared (NIR) spectrophotometer was used for the first time to detect and quantify malaria infection in vitro from isolated dried red blood cells using a fingerpick volume of blood. This the first study to apply a miniaturized NIR device to diagnose a parasitic infection and identify marker bands indicative of malaria infection in the NIR region. An NIR device has many advantages including wavelength accuracy and repeatability, speed, resolution, and a greatly improved signal-to-noise ratio compared to existing spectroscopic options. Using multivariate data analysis, we discriminated control red blood cells from infected cells and established the limit of detection of the technique. Principal component analysis displayed a good separation between the infected and uninfected RBCs, while partial least-squares regression analysis yielded a robust parasitemia prediction with root-mean-square error of prediction values of 0.446 and 0.001% for the higher and lower parasitemia models, respectively. The R2 values of the higher and lower parasitemia models were 0.947 and 0.931, respectively. Finally, an estimated parasitemia detection limit of 0.00001% and a qunatification limit of 0.001% was achieved; to ascertain the true efficacy of the technique for point-of-care screening, clinical studies using large patient numbers are required, which is the subject of future studies.

Ultraviolet/Visible and Near-Infrared Dual Spectroscopic Method for Detection and Quantification of Low-Level Malaria Parasitemia in Whole Blood.

The scourge of malaria infection continues to strike hardest against pregnant women and children in Africa and South East Asia. For global elimination, testing methods that are ultrasensitive to low-level ring-staged parasitemia are urgently required. In this study, we used a novel approach for diagnosis of malaria infection by combining both electronic ultraviolet-visible (UV/vis) spectroscopy and near infrared (NIR) spectroscopy to detect and quantify low-level (1-0.000001%) ring-staged malaria-infected whole blood under physiological conditions uisng Multiclass classification using logistic regression, which showed that the best results were achieved using the extended wavelength range, providing an accuracy of 100% for most parasitemia classes. Likewise, partial least-squares regression (PLS-R) analysis showed a higher quantification sensitivity (R2 = 0.898) for the extended spectral region compared to UV/vis and NIR (R2 = 0.806 and 0.556, respectively). For quantifying different-stage blood parasites, the extended wavelength range was able to detect and quantify all thePlasmodium falciparum accurately compared to testing each spectral component separately. These results demonstrate the potential of a combined UV/vis-NIR spectroscopy to accurately diagnose malaria-infected patients without the need for elaborate sample preparation associated with the existing mid-IR approaches.

Correction: Synchrotron macro ATR-FTIR microspectroscopy for high-resolution chemical mapping of single cells.

Correction for 'Synchrotron macro ATR-FTIR microspectroscopy for high-resolution chemical mapping of single cells' by Jitraporn Vongsvivut et al., Analyst, 2019, 144, 3226-3238, DOI: 10.1039/C8AN01543K.

Infrared Based Saliva Screening Test for COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in an unprecedented need for diagnostic testing that is critical in controlling the spread of COVID-19. We propose a portable infrared spectrometer with purpose-built transflection accessory for rapid point-of-care detection of COVID-19 markers in saliva. Initially, purified virion particles were characterized with Raman spectroscopy, synchrotron infrared (IR) and AFM-IR. A data set comprising 171 transflection infrared spectra from 29 subjects testing positive for SARS-CoV-2 by RT-qPCR and 28 testing negative, was modeled using Monte Carlo Double Cross Validation with 50 randomized test and model sets. The testing sensitivity was 93 % (27/29) with a specificity of 82 % (23/28) that included positive samples on the limit of detection for RT-qPCR. Herein, we demonstrate a proof-of-concept high throughput infrared COVID-19 test that is rapid, inexpensive, portable and utilizes sample self-collection thus minimizing the risk to healthcare workers and ideally suited to mass screening.

Quantification and Identification of Microproteinuria Using Ultrafiltration and ATR-FTIR Spectroscopy.

The presence of low amounts of specific proteins in urine can be an indicator of diagnosis and prognosis of several diseases including renal failure and cancer. Hence, there is an urgent need for Point-of-care (PoC) methods, which can quantify microproteinuria levels (30-300 ppm) and identify the major proteins associated with the microproteinuria. In this study, we coupled ultracentrifugation with attenuated total reflectance-Fourier transform infrared (ATR-FTIR) to identify and quantify proteins in urine at low parts per million levels. The process involves the preconcentration of proteins from 500 µL of urine using an ultrafiltration device. After several washings, the isolated proteins are dried onto the ATR crystal forming a thin film. Imaging studies showed that the absorbance of the protein bands was linear with the amount of mass deposited on the crystal. The methodology was first evaluated with artificial urine spiked with 30-300 ppm of albumin. The calibration showed acceptable linearity (R2 = 0.97) and a limit of detection of 6.7 ppm. Linear relationships were also observed from urine of healthy subjects spiked with microproteinuria concentrations of albumin, immunoglobulin, and hemoglobin, giving a prediction error of the spiked concentration of 23 ppm. When multiple proteins were spiked into the real urine, multivariate analysis was able to decompose the data set into the different proteins, but the multicomponent evaluation was challenging for proteins at low levels. Although the introduction of a preprocessing step reduces the PoC capability of the method, it largely increases its performance, showing great potential as a tool for the diagnosis and prognosis of several illnesses affecting urine proteic composition.

Rapid Approach for Detection of Antibiotic Resistance in Bacteria Using Vibrational Spectroscopy.

Here, we applied vibrational spectroscopy to investigate the drug response following incubation of S. aureus with oxacillin. The main focus of this work was to identify the chemical changes caused by oxacillin over time and to determine the feasibility of the spectroscopic approach to detect antimicrobial resistance. The oxacillin-induced changes in the chemical composition of susceptible bacteria, preceding (and leading to) the inhibition of growth, included an increase in the relative content of nucleic acids, alteration in the α-helical/ß-sheet protein ratio, structural changes in carbohydrates (observed via changes in the band at 1035 cm-1), and significant thickening of the cell wall. These observations enabled a dose-dependent discrimination between susceptible bacteria incubated with and without oxacillin after 120 min. In methicillin resistant strains, no spectral differences were observed between cells, regardless of drug exposure. These results pave the way for a new, rapid spectroscopic approach to detect drug resistance in pathogens, based on their early positive/negative drug response.

Vibrational Spectroscopic Based Approach for Diagnosing Babesia bovis Infection.

Babesia bovis parasites present a serious and significant health concern for the beef and dairy industries in many parts of the world. Difficulties associated with the current diagnostic techniques include the following: they are prone to human error (microscopy) or expensive and time-consuming (polymerase chain reaction) to perform. Little is known about the biochemical changes in blood that are associated with Babesia infections. The discovery of new biomarkers will lead to improved diagnostic outcomes for the cattle industry. Vibrational spectroscopic technologies can record a chemical snapshot of the entire organism and the surrounding cell thereby providing a phenotype of the organism and the host infected cell. Here, we demonstrate the applicability of vibrational spectroscopic imaging techniques including Atomic Force Microscopy Infrared (AFM-IR) and confocal Raman microscopy to discover new biomarkers for B. bovis infections. Furthermore, we applied Attenuated Total Reflection Fourier Transform Infrared (ATR-FTIR) to detect B. bovis in red blood cells (RBCs). Based on changes in the IR spectral bands, with ATR-FTIR in combination with Partial Least Squares-Discriminant Analysis we were able to discriminate infected samples from controls with a sensitivity and specificity of 92.0% and 91.7%, respectively, in less than 2 min, excluding sample extraction and preparation. The proposed method utilized a lysis approach to remove hemoglobin from the suspension of infected and uninfected cells, which significantly increased the sensitivity and specificity compared to measurements performed on intact infected red blood cells (intact infected RBC, 77.3% and 79.2%). This work represents a holistic spectroscopic study from the level of the single infected RBC using AFM-IR and confocal Raman to the detection of the parasite in a cell population using ATR-FTIR for a babesiosis diagnostic.

Parasites under the Spotlight: Applications of Vibrational Spectroscopy to Malaria Research.

New technologies to diagnose malaria at high sensitivity and specificity are urgently needed in the developing world where the disease continues to pose a huge burden on society. Infrared and Raman spectroscopy-based diagnostic methods have a number of advantages compared with other diagnostic tests currently on the market. These include high sensitivity and specificity for detecting low levels of parasitemia along with ease of use and portability. Here, we review the application of vibrational spectroscopic techniques for monitoring and detecting malaria infection. We discuss the role of vibrational (infrared and Raman) spectroscopy in understanding the processes of parasite biology and its application to the study of interactions with antimalarial drugs. The distinct molecular phenotype that characterizes malaria infection and the high sensitivity enabling detection of low parasite densities provides a genuine opportunity for vibrational spectroscopy to become a front-line tool in the elimination of this deadly disease and provide molecular insights into the chemistry of this unique organism.

Vibrational Spectroscopy as a Sensitive Probe for the Chemistry of Intra-Phase Bacterial Growth.

Bacterial growth in batch cultures occurs in four phases (lag, exponential/log, stationary and death phase) that differ distinctly in number of different bacteria, biochemistry and physiology. Knowledge regarding the growth phase and its kinetics is essential for bacterial research, especially in taxonomic identification and monitoring drug interactions. However, the conventional methods by which to assess microbial growth are based only on cell counting or optical density, without any insight into the biochemistry of cells or processes. Both Raman and Fourier transform infrared (FTIR) spectroscopy have shown potential to determine the chemical changes occurring between different bacterial growth phases. Here, we extend the application of spectroscopy and for the first time combine both Raman and FTIR microscopy in a multimodal approach to detect changes in the chemical compositions of bacteria within the same phase (intra-phase). We found a number of spectral markers associated with nucleic acids (IR: 964, 1082, 1215 cm-1; RS: 785, 1483 cm-1), carbohydrates (IR: 1035 cm-1; RS: 1047 cm-1) and proteins (1394 cm-1, amide II) reflecting not only inter-, but also intra-phase changes in bacterial chemistry. Principal component analysis performed simultaneously on FTIR and Raman spectra enabled a clear-cut, time-dependent discrimination between intra-lag phase bacteria probed every 30 min. This demonstrates the unique capability of multimodal vibrational spectroscopy to probe the chemistry of bacterial growth even at the intra-phase level, which is particularly important for the lag phase, where low bacterial numbers limit conventional analytical approaches.

Influence of the Sample Preparation Method in Discriminating Candida spp. Using ATR-FTIR Spectroscopy.

Several studies have investigated the capacity of ATR-FTIR spectroscopy for fungal species discrimination. However, preparation methods vary among studies. This study aims to ascertain the effect of sample preparation on the discriminatory capacity of ATR-FTIR spectroscopy. Candida species were streaked to obtain colonies and spectra were collected from each preparation type, which included: (a) untreated colonies being directly transferred to the ATR crystal, (b) following washing and (c) following 24-h fixation in formalin. Spectra were pre-processed and principal component analysis (PCA) and K-means cluster analysis (KMC) were performed. Results showed that there was a clear discrimination between preparation types. Groups of spectra from untreated and washed isolates clustered separately due to intense protein, DNA and polysaccharide bands, whilst fixed spectra clustered separately due to intense polysaccharide bands. This signified that sample preparation had influenced the chemical composition of samples. Nevertheless, across preparation types, significant species discrimination was observed, and the polysaccharide (1200-900 cm-1) region was a common critical marker for species discrimination. However, different discriminatory marker bands were observed across preparation methods. Thus, sample preparation appears to influence the chemical composition of Candida samples; however, does not seem to significantly impact the species discrimination potential for ATR-FTIR spectroscopy.

Attenuated total reflection: Fourier transform infrared spectroscopy for detection of heterogeneous vancomycin-intermediate Staphylococcus aureus.

Staphylococcus aureus strains resistant to the last line antibiotic, vancomycin, have been of clinical concern. These include heterogeneous vancomycin-intermediate S. aureus (hVISA) and VISA. The hVISA phenotype cannot be detected by routine laboratory methods. Characterization of hVISA/VISA by new technologies is necessary to differentiate them rapidly from the vancomycin-susceptible isolates (VSSA). In this study, we developed a model for discrimination of hVISA from VSSA by using attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy combined with multivariate data analysis, displaying a phenotypic signature of the bacteria. ATR-FTIR spectra were acquired from a total of 59 clinical methicillin-resistant S. aureus (MRSA) isolates comprising 28 hVISA and 31 VSSA strains. Principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) were used to analyze 351 spectra of 39 isolates and develop a discrimination model for identifying hVISA and VSSA. The classification model, which was used for blind testing of 90 spectra from each of 10 hVISA, and 10 VSSA isolates, provided 100% sensitivity and specificity. The modeling revealed that the major discrimination between hVISA and VSSA phenotypes involved bands related to cell wall content (1087 and 1057 cm-1). This study showed that ATR-FTIR technique may be an alternative method for rapid detection of low-level vancomycin-resistant S. aureus.

Detection of Antimicrobial Resistance-Related Changes in Biochemical Composition of Staphylococcus aureus by Means of Atomic Force Microscopy-Infrared Spectroscopy.

The development of antimicrobial resistance (AMR) resulting from widespread antibiotic usage is occurring at an alarming pace, much faster than our understanding of the mechanisms behind resistance. Knowledge about resistance-related phenotypic and genotypic changes is critical for the development of new drugs. Here, we identify changes in the chemical composition of Staphylococcus aureus associated with the development of resistance to last resort drugs, vancomycin and daptomycin, using a novel, single cell, nanoscale technique, atomic force microscopy-infrared spectroscopy (AFM-IR), combined with chemometric analysis. We utilized paired clinical isolates, with the parent (susceptible) strain isolated prior to treatment and the daughter (resistant) strain obtained from the same patient after drug admission and clinical failure. We observed an increase in the amount of nonintracellular carbohydrates, indicating thickening or changes in the packing of the cell wall, as well as changes in the phospholipid content in relation to vancomycin resistance and daptomycin nonsusceptibility, respectively.

Infrared spectroscopy coupled to cloud-based data management as a tool to diagnose malaria: a pilot study in a malaria-endemic country.

BACKGROUND: Widespread elimination of malaria requires an ultra-sensitive detection method that can detect low parasitaemia levels seen in asymptomatic carriers who act as reservoirs for further transmission of the disease, but is inexpensive and easy to deploy in the field in low income settings. It was hypothesized that a new method of malaria detection based on infrared spectroscopy, shown in the laboratory to have similar sensitivity to PCR based detection, could prove effective in detecting malaria in a field setting using cheap portable units with data management systems allowing them to be used by users inexpert in spectroscopy. This study was designed to determine whether the methodology developed in the laboratory could be translated to the field to diagnose the presence of Plasmodium in the blood of patients presenting at hospital with symptoms of malaria, as a precursor to trials testing the sensitivity of to detect asymptomatic carriers. METHODS: The field study tested 318 patients presenting with suspected malaria at four regional clinics in Thailand. Two portable infrared spectrometers were employed, operated from a laptop computer or a mobile telephone with in-built software that guided the user through the simple measurement steps. Diagnostic modelling and validation testing using linear and machine learning approaches was performed against the gold standard qPCR. Sample spectra from 318 patients were used for building calibration models (112 positive and 110 negative samples according to PCR testing) and independent validation testing (39 positive and 57 negatives samples by PCR). RESULTS: The machine learning classification (support vector machines; SVM) performed with 92% sensitivity (3 false negatives) and 97% specificity (2 false positives). The Area Under the Receiver Operation Curve (AUROC) for the SVM classification was 0.98. These results may be better than as stated as one of the spectroscopy false positives was infected by a Plasmodium species other than Plasmodium falciparum or Plasmodium vivax, not detected by the PCR primers employed. CONCLUSIONS: In conclusion, it was demonstrated that ATR-FTIR spectroscopy could be used as an efficient and reliable malaria diagnostic tool and has the potential to be developed for use at point of care under tropical field conditions with spectra able to be analysed via a Cloud-based system, and the diagnostic results returned to the user's mobile telephone or computer. The combination of accessibility to mass screening, high sensitivity and selectivity, low logistics requirements and portability, makes this new approach a potentially outstanding tool in the context of malaria elimination programmes. The next step in the experimental programme now underway is to reduce the sample requirements to fingerprick volumes.

Synchrotron macro ATR-FTIR microspectroscopy for high-resolution chemical mapping of single cells.

Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy has been used widely for probing the molecular properties of materials. Coupling a synchrotron infrared (IR) beam to an ATR element using a high numerical aperture (NA) microscope objective enhances the spatial resolution, relative to transmission or transflectance microspectroscopy, by a factor proportional to the refractive index (n) of the ATR element. This work presents the development of the synchrotron macro ATR-FTIR microspectroscopy at Australian Synchrotron Infrared Microspectroscopy (IRM) Beamline, and demonstrates that high quality FTIR chemical maps of single cells and tissues can be achieved at an enhanced spatial resolution. The so-called "hybrid" macro ATR-FTIR device was developed by modifying the cantilever arm of a standard Bruker macro ATR-FTIR unit to accept germanium (Ge) ATR elements with different facet sizes (i.e. 1 mm, 250 µm and 100 µm in diameter) suitable for different types of sample surfaces. We demonstrated the capability of the technique for high-resolution single cell analysis of malaria-infected red blood cells, individual neurons in a brain tissue and cellular structures of a Eucalyptus leaf. The ability to measure a range of samples from soft membranes to hard cell wall structures demonstrates the potential of the technique for high-resolution chemical mapping across a broad range of applications in biology, medicine and environmental science.

Simultaneous ATR-FTIR Based Determination of Malaria Parasitemia, Glucose and Urea in Whole Blood Dried onto a Glass Slide.

New diagnostic tools that can detect malaria parasites in conjunction with other diagnostic parameters are urgently required. In this study, Attenuated Total Reflection Fourier transform infrared (ATR-FTIR) spectroscopy in combination with Partial Least Square Discriminant Analysis (PLS-DA) and Partial Least Square Regression (PLS-R) have been applied as a point-of-care test for identifying malaria parasites, blood glucose, and urea levels in whole blood samples from thick blood films on glass slides. The specificity for the PLS-DA was found to be 98% for parasitemia levels >0.5%, but a rather low sensitivity of 70% was achieved because of the small number of negative samples in the model. In PLS-R the Root Mean Square Error of Cross Validation (RMSECV) for parasite concentration (0-5%) was 0.58%. Similarly, for glucose (0-400 mg/dL) and urea (0-250 mg/dL) spiked samples, relative RMSECVs were 16% and 17%, respectively. The method reported here is the first example of multianalyte/disease diagnosis using ATR-FTIR spectroscopy, which in this case, enabled the simultaneous quantification of glucose and urea analytes along with malaria parasitemia quantification using one spectrum obtained from a single drop of blood on a glass microscope slide.

The effect of common anticoagulants in detection and quantification of malaria parasitemia in human red blood cells by ATR-FTIR spectroscopy.

Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR) has the potential to become a new diagnostic tool for malaria and other diseases. For point-of-care testing, the use of ATR-FTIR in malaria diagnosis enables the analysis of blood in the aqueous state, which represents an enormous advantage by minimising the sample preparation by removing the need for cell fixation. Here we report the quantification of malaria parasitemia in human RBCs in their normal physiological aqueous state. A potential confounding variable for spectroscopic measurements performed on blood are the various anticoagulants that are required to prevent clotting. Accordingly, we tested the effects of 3 common anticoagulants; Sodium Citrate (SC), Potassium Ethylenediaminetetraacetic Acid (EDTA) and lithium heparin on plasma and whole blood in the aqueous and dry phase. Principal Component Analysis (PCA) revealed the model was heavily influenced by the anticoagulants in the case of dry samples, however, in aqueous whole blood samples, the effect was less pronounced as the water in the sample presumably diluted the amount of anticoagulant in contact with the ATR crystal. The possible influence of the anticoagulant effect on the ability to quantify parasitemia levels was tested using Partial Least Squares Regression Analysis (PLS-R). There was no influence of anticoagulants on quantification in the 0-1% range, however attempts to quantify at lower levels (0-0.1%) was best achieved with heparin compared to the other two anticoagulants. The results demonstrate ability to diagnose malaria using ATR-FTIR spectroscopy using wet RBC samples as well as underscoring the desirability to perform wet measurements as these minimise the possible confounding influence of anticoagulants used in blood collection.

High resolution FTIR imaging provides automated discrimination and detection of single malaria parasite infected erythrocytes on glass.

New highly sensitive tools for malaria diagnostics are urgently needed to enable the detection of infection in asymptomatic carriers and patients with low parasitemia. In pursuit of a highly sensitive diagnostic tool that can identify parasite infections at the single cell level, we have been exploring Fourier transform infrared (FTIR) microscopy using a Focal Plane Array (FPA) imaging detector. Here we report for the first time the application of a new optic configuration developed by Agilent that incorporates 25× condenser and objective Cassegrain optics with a high numerical aperture (NA = 0.81) along with additional high magnification optics within the microscope to provide 0.66 micron pixel resolution (total IR system magnification of 61×) to diagnose malaria parasites at the single cell level on a conventional glass microscope slide. The high quality images clearly resolve the parasite's digestive vacuole demonstrating sub-cellular resolution using this approach. Moreover, we have developed an algorithm that first detects the cells in the infrared image, and secondly extracts the average spectrum. The average spectrum is then run through a model based on Partial Least Squares-Discriminant Analysis (PLS-DA), which diagnoses unequivocally the infected from normal cells. The high quality images, and the fact this measurement can be achieved without a synchrotron source on a conventional glass slide, shows promise as a potential gold standard for malaria detection at the single cell level.