Biomolecular profiles of Arctic sea-ice diatoms highlight the role of under-ice light in cellular energy allocation.

Arctic sea-ice diatoms fuel polar marine food webs as they emerge from winter darkness into spring. Through their photosynthetic activity they manufacture the nutrients and energy that underpin secondary production. Sea-ice diatom abundance and biomolecular composition vary in space and time. With climate change causing short-term extremes and long-term shifts in environmental conditions, understanding how and in what way diatoms adjust biomolecular stores with environmental perturbation is important to gain insight into future ecosystem energy production and nutrient transfer. Using synchrotron-based Fourier transform infrared microspectroscopy, we examined the biomolecular composition of five dominant sea-ice diatom taxa from landfast ice communities covering a range of under-ice light conditions during spring, in Svalbard, Norway. In all five taxa, we saw a doubling of lipid and fatty acid content when light transmitted to the ice-water interface was >5% but <15% (85%-95% attenuation through snow and ice). We determined a threshold around 15% light transmittance after which biomolecular synthesis plateaued, likely because of photoinhibitory effects, except for Navicula spp., which continued to accumulate lipids. Increasing under-ice light availability led to increased energy allocation towards carbohydrates, but this was secondary to lipid synthesis, whereas protein content remained stable. It is predicted that under-ice light availability will change in the Arctic, increasing because of sea-ice thinning and potentially decreasing with higher snowfall. Our findings show that the nutritional content of sea-ice diatoms is taxon-specific and linked to these changes, highlighting potential implications for future energy and nutrient supply for the polar marine food web.

Identification of Glucose-6 Phosphate Dehydrogenase Deficient Patients Using Attenuated Total Reflection Fourier Transform Infrared Spectroscopy Using Partial Least Squares Discriminant Analysis in Aqueous Blood Samples.

Glucose-6 phosphate dehydrogenase (G6PD) deficiency is an X-linked blood disease that affects 400 million people globally and is especially prevalent in malaria-endemic regions. A significant portion of carriers are asymptomatic and undiagnosed posing complications in the eradication of malaria as it restricts the types of drugs used for malaria treatment. A simple and accurate diagnosis of the deficiency is vital in the eradication of malaria. In this study, we investigate the potential of attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR) as a diagnostic technique for G6PD deficiency. Venous blood samples were collected in lithium heparin anticoagulant tubes from G6PD partial and fully deficient volunteers, n = 17, and normal volunteers, n = 59, in Khon Kaen, Thailand. Spectra of aqueous and dry samples were acquired of whole blood, plasma, and red blood cells, and modeled using partial least squares discriminant analysis (PLS-DA). PLS-DA modeling resulted in a sensitivity of 0.800 and specificity of 0.800 correctly classifying fully deficient participants as well as a majority of partially deficient females who are often misdiagnosed as normal by current screening methods. The viability of utilizing aqueous samples has always been hindered by the variability of hydration in the sample, but by employing multicurve curve resolution-alternating least squares to subtract water from each sample we are able to produce high-quality spectra with minimized water contributions. The approach shows proof of principle that ATR FT-IR combined with multivariate data analysis could become a frontline screening tool for G6PD deficiency by improving tailored drug treatments and ultimately saving lives.

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.

Disposable Coverslip for Rapid Throughput Screening of Malaria Using Attenuated Total Reflection Spectroscopy.

Malaria is considered to be one of the most catastrophic health issues in the whole world. Vibrational spectroscopy is a rapid, robust, label-free, inexpensive, highly sensitive, nonperturbative, and nondestructive technique with high diagnostic potential for the early detection of disease agents. In particular, the fingerprinting capability of attenuated total reflection spectroscopy is promising as a point-of-care diagnostic tool in resource-limited areas. However, improvements are required to expedite the measurements of biofluids, including the drying procedure and subsequent cleaning of the internal reflection element to enable high throughput successive measurements. As an alternative, we propose using an inexpensive coverslip to reduce the sample preparation time by enabling multiple samples to be collectively dried together under the same temperature and conditions. In conjunction with partial least squares regression, attenuated total reflection spectroscopy was able to detect and quantify the parasitemia with root mean square error of cross-validation and R2 values of 0.177 and 0.985, respectively. Here, we characterize an inexpensive, disposable coverslip for the high throughput screening of malaria parasitic infections and thus demonstrate an alternative approach to direct deposition of the sample onto the internal reflection element.

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.

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.

Infrared Spectroscopy of Blood.

The magnitude of infectious diseases in the twenty-first century created an urgent need for point-of-care diagnostics. Critical shortages in reagents and testing kits have had a large impact on the ability to test patients with a suspected parasitic, bacteria, fungal, and viral infections. New point-of-care tests need to be highly sensitive, specific, and easy to use and provide results in rapid time. Infrared spectroscopy, coupled to multivariate and machine learning algorithms, has the potential to meet this unmet demand requiring minimal sample preparation to detect both pathogenic infectious agents and chronic disease markers in blood. This focal point article will highlight the application of Fourier transform infrared spectroscopy to detect disease markers in blood focusing principally on parasites, bacteria, viruses, cancer markers, and important analytes indicative of disease. Methodologies and state-of-the-art approaches will be reported and potential confounding variables in blood analysis identified. The article provides an up to date review of the literature on blood diagnosis using infrared spectroscopy highlighting the recent advances in this burgeoning field.

Atomic Force Microscopy Combined with Infrared Spectroscopy as a Tool to Probe Single Bacterium Chemistry.

Atomic Force Microscopy-Infrared Spectroscopy (AFM-IR) is a novel combinatory technique, enabling simultaneous characterization of physical properties and chemical composition of sample with nanoscale resolution. By combining AFM with IR, the spatial resolution limitation of conventional IR is overcome, enabling a resolution of 20-100 nm to be achieved. This opens the door for a broad array of new applications of IR toward probing samples smaller than several micrometers, previously unachievable by means of conventional IR microscopy. AFM-IR is eminently suited for bacterial research, providing both spectral and spatial information at the single cell and intracellular level. The increasing global health concerns and unfavorable future prediction regarding bacterial infections, and especially, rapid development of antimicrobial resistance, has created an urgent need for a research tool capable of phenotypic probing at the single cell and subcellular level. AFM-IR offers the potential to address this need, by enabling detail characterization of chemical composition of a single bacterium. Here, we provide a complete protocol for sample preparation and data acquisition of single spectra and mapping modality, for the application of AFM-IR toward bacterial studies.

Publisher Correction: Classification of aggressive and classic mantle cell lymphomas using synchrotron Fourier Transform Infrared microspectroscopy.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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.

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.

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.

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.

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.

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.