Molecular diagnostics of infectious diseases: state of the technology

Detection of extended-spectrum β-lactamase-producing bacteria isolated directly from urine by infrared spectroscopy and machine learning

Resistant bacteria have become one of the leading health threats in the last decades. Extended-spectrum β-lactamase (ESBL) producing bacteria, including Escherichia (E.) coli and Klebsiella (K.) pneumoniae (the most frequent ones), are a significant class out of all resistant infecting bacteria. Due to the widespread and ongoing development of ESBL-producing (ESBL⁺) resistant bacteria, many routinely used antibiotics are no longer effective against them. However, an early and reliable ESBL⁺ bacteria detection method will improve the efficiency of treatment and limit their spread. In this work, we investigated the capability of infrared (IR) spectroscopy based machine learning tools [principal component analysis (PCA) and Random Forest (RF) classifier] for the rapid detection of ESBL⁺ bacteria isolated directly from patients' urine. For that, we examined 1881 E. coli samples (416 ESBL⁺ and 1465 ESBL^-) and 609 K. pneumoniae samples (237 ESBL⁺ and 372 ESBL^-). All samples were isolated directly from the urine of midstream patients. This study revealed that within 40 min of receiving the patient urine it is possible to determine the infecting bacterium as E. coli or K. pneumoniae with 95% success rate while it was possible to determine the ESBL⁺E. coli and ESBL⁺K. pneumoniae with 83% and 78% accuracy rates, respectively.

Fast identification and susceptibility determination of E. coli isolated directly from patients' urine using infrared-spectroscopy and machine learning

For effective treatment, it is crucial to identify the infecting bacterium at the species level and to determine its antimicrobial susceptibility. This is especially true now, when numerous bacteria have developed multidrug resistance to most commonly used antibiotics. Currently used methods need ∼ 48 h to identify a bacterium and determine its susceptibility to specific antibiotics. This study reports the potential of using infrared spectroscopy with machine learning algorithms to identify E. coli isolated directly from patients' urine while simultaneously determining its susceptibility to antibiotics within ∼ 40 min after receiving the patient's urine sample. For this goal, 1,765 E. coli isolates purified directly from urine samples were collected from patients with urinary tract infections (UTIs). After collection, the samples were tested by infrared microscopy and analyzed by machine learning. We achieved success rates of ∼ 96% in isolate level identification and ∼ 84% in susceptibility determination.

Using Infrared Spectroscopy and Multivariate Analysis to Detect Antibiotics' Resistant Escherichia coli Bacteria

Bacterial pathogens are one of the primary causes of human morbidity worldwide. Historically, antibiotics have been highly effective against most bacterial pathogens; however, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global health-care problem. Early and rapid determination of bacterial susceptibility to antibiotics has become essential in many clinical settings and, sometimes, can save lives. Currently classical procedures require at least 48 h for determining bacterial susceptibility, which can constitute a life-threatening delay for effective treatment. Infrared (IR) microscopy is a rapid and inexpensive technique, which has been used successfully for the detection and identification of various biological samples; nonetheless, its true potential in routine clinical diagnosis has not yet been established. In this study, we evaluated the potential of this technique for rapid identification of bacterial susceptibility to specific antibiotics based on the IR spectra of the bacteria. IR spectroscopy was conducted on bacterial colonies, obtained after 24 h culture from patients' samples. An IR microscope was utilized, and a computational classification method was developed to analyze the IR spectra by novel pattern-recognition and statistical tools, to determine E. coli susceptibility within a few minutes to different antibiotics, gentamicin, ceftazidime, nitrofurantoin, nalidixic acid, ofloxacin. Our results show that it was possible to classify the tested bacteria into sensitive and resistant types, with success rates as high as 85% for a number of examined antibiotics. These promising results open the potential of this technique for faster determination of bacterial susceptibility to certain antibiotics.

Detection of antibiotic resistant Escherichia Coli bacteria using infrared microscopy and advanced multivariate analysis

DeterminingE. colibacteria susceptibility by analyzing their FTIR spectra using multivariate analysis.

Conformational features of benzo-homologated yDNA duplexes by molecular dynamics simulation

yDNA is a base-modified nucleic acid duplex containing size-expanded nucleobases. Base-modified nucleic acids could expand the genetic alphabet and thereby enhance the functional potential of DNA. Unrestrained 100 ns MD simulations were performed in explicit solvent on the yDNA NMR sequence [5'(yA T yA yA T yA T T yA T)₂ ] and two modeled yDNA duplexes, [5'(yC yC G yC yC G G yC G G)₂ ] and [(yT5' G yT A yC yG C yA yG T3')•(yA5' C T C yG C G yT A yC A3')]. The force field parameters for the yDNA bases were derived in consistent with the well-established AMBER force field. Our results show that DNA backbone can withstand the stretched size of the bases retaining the Watson-Crick base pairing in the duplexes. The duplexes retained their double helical structure throughout the simulations accommodating the strain due to expanded bases in the backbone torsion angles, sugar pucker and helical parameters. The effect of the benzo-expansion is clearly reflected in the extended C1'-C1' distances and enlarged groove widths. The size expanded base modification leads to reduction in base pair twist resulting in larger overlapping area between the stacked bases, enhancing inter and intra strand stacking interactions in yDNA in comparison with BDNA. This geometry could favour enhanced interactions with the groove binders and DNA binding proteins., 2016. © 2015 Wiley Periodicals, Inc. Biopolymers 105: 55-64, 2016.

Isothermal Recombinase Polymerase Amplification Assay Applied to the Detection of Group B Streptococci in Vaginal/Anal Samples

BACKGROUND

Group B streptococcal infections are the leading cause of sepsis and meningitis in newborns. A rapid and reliable method for the detection of this pathogen at the time of delivery is needed for the early treatment of neonates. Isothermal amplification techniques such as recombinase polymerase amplification have advantages relative to PCR in terms of the speed of reaction and simplicity.

METHODS

We studied the clinical performance of recombinase polymerase amplification for the screening of group B streptococci in vaginal/anal samples from 50 pregnant women. We also compared the limit of detection and the analytical specificity of this isothermal assay to real-time PCR (RT-PCR).

RESULTS

Compared to RT-PCR, the recombinase polymerase amplification assay showed a clinical sensitivity of 96% and a clinical specificity of 100%. The limit of detection was 98 genome copies and the analytical specificity was 100% for a panel of 15 bacterial and/or fungal strains naturally found in the vaginal/anal flora. Time-to-result for the recombinase polymerase amplification assay was <20 min compared to 45 min for the RT-PCR assay; a positive sample could be detected as early as 8 min.

CONCLUSIONS

We demonstrate the potential of isothermal recombinase polymerase amplification assay as a clinically useful molecular diagnostic tool that is simple and faster than PCR/RT-PCR. Recombinase polymerase amplification offers great potential for nucleic acid–based diagnostics at the point of care.

Application of mass spectrometry to molecular diagnostics of viral infections

Mass spectrometry (MS) has found numerous applications in life sciences. It has high accuracy, sensitivity and wide dynamic range in addition to medium- to high-throughput capabilities. These features make MS a superior platform for analysis of various biomolecules including proteins, lipids, nucleic acids and carbohydrates. Until recently, MS was applied for protein detection and characterization. During the last decade, however, MS has successfully been used for molecular diagnostics of microbial and viral infections with the most notable applications being identification of pathogens, genomic sequencing, mutation detection, DNA methylation analysis, tracking of transmissions, and characterization of genetic heterogeneity. These new developments vastly expand the MS application from experimental research to public health and clinical fields. Matching of molecular techniques with specific requirements of the major MS platforms has produced powerful technologies for molecular diagnostics, which will further benefit from coupling with computational tools for extracting clinical information from MS-derived data.

Liposome-enhanced lateral-flow assays for the sandwich-hybridization detection of RNA

Clinical and environmental analyses frequently necessitate rapid, simple, and inexpensive point-of-care or field tests. These semiquantitative tests may be later followed up by confirmatory laboratory-based assays, but can provide an initial scenario assessment important for resource mobilization and threat confinement. Lateral-flow assays (LFAs) and dip-stick assays, which are typically antibody-based and yield a visually detectable signal, provide an assay format suiting these applications extremely well. Signal generation is commonly obtained through the use of colloidal gold or latex beads, which yield a colored band either directly proportional or inversely proportional to the concentration of the analyte of interest. Here, dye-encapsulating liposomes as an alternative are discussed. The LFA biosensors described in this chapter rely on the sandwich-hybridization of a nucleic acid sequence-based amplified (NASBA) mRNA target between a membrane immobilized capture probe and a visible dye (sulforhodamine B)-encapsulating liposome conjugated reporter probe. Although the methodology of this chapter is focused on LFAs for the detection of RNA through sandwich hybridization, the information within can be readily adapted for sandwich and competitive immunoassays. Included are an introduction and application notes toward this end. These include notes ranging from the detection of nonamplified RNA and single-stranded DNA, conjugation protocols for antibodies and other proteins to liposomes, and universal assay formats.

Reproducible surface-enhanced Raman scattering spectra of bacteria on aggregated silver nanoparticles

Surface-enhanced Raman scattering (SERS) is proven to be a powerful technique for rapid identification and discrimination of microorganisms. However, due to the heterogeneous nature of the samples, the acquisition of reproducible spectra hinders the further development of the technique. In this study, we demonstrate the influence of the experimental conditions on SERS spectra. Then, we report a simple sample preparation method coupled with a light microscope attached to a Raman spectrometer to find a proper spot on the sample to acquire reproducible SERS spectra. This method utilizes the excited surface plasmons of the aggregated silver nanoparticles to visualize the spots on the sample. The samples are prepared using the concentrated silver colloidal solutions. The collection time for one spectrum is 10 s and each spectrum is a very good representative of the other spectra acquired from the same sample. The nature of the surface charge of the silver nanoparticles influences the spectral features by determining the strength of the interactions between nanoparticles and bacteria and the aggregation properties of the nanoparticles. Although increasing the colloid concentration in the sample resulted in reproducible spectra from arbitrary points on the sample, a great variation from sample to sample prepared with the different colloidal solution concentrations is observed.

FTIR spectroscopy in medical mycology: applications to the differentiation and typing of Candida

The incidence of fungal infections, in particular candidiasis and aspergillosis, has considerably increased during the last three decades. This is mainly due to advances in medical treatments and technologies. In high risk patients (e.g. in haematology or intensive care), the prognosis of invasive candidiasis is relatively poor. Therefore, a rapid and correct identification of the infectious agent is important for an efficient and prompt therapy. Most clinical laboratories rely on conventional identification methods that are based on morphological, physiological and nutritional characteristics. However, these have their limitations because they are time-consuming and not always very accurate. Moreover, molecular methods may be required to determine the genetic relationship between the infectious strains, for instance in Candida outbreaks. In addition, the latter methods require time, expensive consumables and highly trained staff to be performed adequately. In this study, we have applied the FTIR spectroscopic approach to different situations encountered in routine mycological diagnosis. We show the potentials of this phenotypic approach, used in parallel with routine identification methods, for the differentiation of 3 frequently encountered Candida species (C. albicans, C. glabrata and C. krusei) by using both suspensions and microcolonies. This approach, developed for an early discrimination, may help in the initial choice of antifungal treatment. Furthermore, we demonstrate the feasibility of the method for intraspecies comparison (typing) of 3 Candida species (C. albicans, C. glabrata and C. parapsilosis), particularly when an outbreak is suspected.

Rapid identification of Candida species by FT-IR microspectroscopy

Due to the continuous increase of human candidiasis and the great diversity of yeasts of the Candida genera, it is indispensable to identify this yeast as early as possible. Early identification enables an early diagnostic and patient-adapted anti-fungal therapy, thus reducing morbidity and mortality related to these infections. In view of this, we have in this study investigated microcolonies using a method based on Fourier transform-infrared microspectroscopy (FTIRM) for a rapid and early identification of the most frequent Candida species encountered in human pathology. FTIR spectroscopy is a whole-cell "fingerprinting" method by which microorganisms can be identified. By exploiting the huge discriminating capacity of this technique, we identified 6 species (Candida albicans, Candida glabrata, Candida parapsilosis, Candida tropicalis, Candida krusei, and Candida kefyr) from a collection of 57 clinical strains of Candida, isolated from hospitalised patients. Data obtained on 10- to 18-h-old microcolonies were compared to cultures of 24 h. Our results clearly show the efficiency and the robustness of FTIR (micro)spectroscopy in identifying species with a classification rate of 100% for both microcolonies and 24-h cultures. FTIR microspectroscopy is thus a promising clinical approach, because compared to conventional and molecular techniques, it is time and money saving, has great identification and discriminating potentials, and is amenable to an automated high-throughput routine system.

Prospective study of the performance of vibrational spectroscopies for rapid identification of bacterial and fungal pathogens recovered from blood cultures

Rapid identification of microbial pathogens reduces infection-related morbidity and mortality of hospitalized patients. Raman spectra and Fourier transform infrared (IR) spectra constitute highly specific spectroscopic fingerprints of microorganisms by which they can be identified. Little biomass is required, so that spectra of microcolonies can be obtained. A prospective clinical study was carried out in which the causative pathogens of bloodstream infections in hospitalized patients were identified. Reference libraries of Raman and IR spectra of bacterial and yeast pathogens highly prevalent in bloodstream infections were created. They were used to develop identification models based on linear discriminant analysis and artificial neural networks. These models were tested by carrying out vibrational spectroscopic identification in parallel with routine diagnostic phenotypic identification. Whereas routine identification has a typical turnaround time of 1 to 2 days, Raman and IR spectra of microcolonies were collected 6 to 8 h after microbial growth was detected by an automated blood culture system. One hundred fifteen samples were analyzed by Raman spectroscopy, of which 109 contained bacteria and 6 contained yeasts. One hundred twenty-one samples were analyzed by IR spectroscopy. Of these, 114 yielded bacteria and 7 were positive for yeasts. High identification accuracy was achieved in both the Raman (92.2%, 106 of 115) and IR (98.3%, 119 of 121) studies. Vibrational spectroscopic techniques enable simple, rapid, and accurate microbial identification. These advantages can be easily transferred to other applications in diagnostic microbiology, e.g., to accelerate identification of fastidious microorganisms.

Integration of molecular diagnostics with therapeutics: implications for drug discovery and patient care

The Introduction of targeted therapeutics into clinical practice has created major opportunities for further development of the molecular diagnostics industry. Emerging genomic and proteomic technologies and information are now resulting in the molecular subclassification of disease as the basis for diagnosis, prognosis and therapeutic selection. The ultimate goals of personalized medicine are to take advantage of a molecular understanding of disease, both to optimize drug development and direct preventive resources and therapeutic agents at the right population of people while they are still well. Single nucleotide polymorphisms identification and genotyping have uncovered predisposition markers from cancer and heart disease as well in the prediction of both drug efficacy and toxicity. Pharmacogenomic and pharmacodynamic assays are being developed to enhance the speed and decrease the cost of drug development, as well as reduce side effects and increase response rates in a variety of diseases. The traditional trial and error practice of medicine is progressively eroding in favor of more precise marker-assisted diagnosis and safer and more effective molecularly guided treatment of disease. For the diagnostics industry this represents an unprecedented opportunity for integration, increased value and commercial opportunities for molecularly-derived tests.

Integrating diagnostics and therapeutics: revolutionizing drug discovery and patient care

Over the next five years it is widely anticipated that the molecular diagnostics industry will continue to grow at double-digit pace to meet increasing demand for personalized medicine. A wide variety of drugs in late preclinical and early clinical development is now being targeted to disease-specific gene and protein defects that will require co-approval of diagnostic and therapeutic products by regulatory agencies. For clinical laboratories and pathologists, this integration of diagnostics and therapeutics represents a major new opportunity to emerge as leaders of the new medicine, guiding the selection, dosage, route of administration and multi-drug combinations, and producing increased efficacy and reduced toxicity of pharmaceutical products.