1H NMR spectroscopy in the diagnosis of Klebsiella pneumoniae-induced urinary tract infection

A cross-omics data analysis strategy for metabolite-microbe pair identification

Given the pivotal roles of metabolomics and microbiomics, numerous data mining approaches aim to uncover their intricate connections. However, the complex many-to-many associations between metabolome-microbiome profiles yield numerous statistically significant but biologically unvalidated candidates. To address these challenges, we introduce BiOFI, a strategic framework for identifying metabolome-microbiome correlation pairs (Bi-Omics). BiOFI employs a comprehensive scoring system, incorporating intergroup differences, effects on feature correlation networks, and organism abundance. Meanwhile, it establishes a built-in database of metabolite-microbe-KEGG functional pathway linking relationships. Furthermore, BiOFI can rank related feature pairs by combining importance scores and correlation strength. Validation on a dataset of cesarean-section infants confirms the strategy's validity and interpretability. The BiOFI R package is freely accessible at https://github.com/chentianlu/BiOFI.

The Role of Metabolomics and Microbiology in Urinary Tract Infection

One of the common illnesses that affect women's physical and mental health is urinary tract infection (UTI). The disappointing results of empirical anti-infective treatment and the lengthy time required for urine bacterial culture are two issues. Antibiotic misuse is common, especially in females who experience recurrent UTI (rUTI). This leads to a higher prevalence of antibiotic resistance in the microorganisms that cause the infection. Antibiotic therapy will face major challenges in the future, prompting clinicians to update their practices. New testing techniques are making the potential association between the urogenital microbiota and UTIs increasingly apparent. Monitoring changes in female urinary tract (UT) microbiota, as well as metabolites, may be useful in exploring newer preventive treatments for UTIs. This review focuses on advances in urogenital microbiology and organismal metabolites relevant to the identification and handling of UTIs in an attempt to provide novel methods for the identification and management of infections of the UT. Particular attention is paid to the microbiota and metabolites in the patient's urine in relation to their role in supporting host health.

Identification and Antibiotic-Susceptibility Profiling of Infectious Bacterial Agents: A Review of Current and Future Trends

Antimicrobial resistance is one of the most worrying threats to humankind with extremely high healthcare costs associated. The current technologies used in clinical microbiology to identify the bacterial agent and profile antimicrobial susceptibility are time-consuming and frequently expensive. As a result, physicians prescribe empirical antimicrobial therapies. This scenario is often the cause of therapeutic failures, causing higher mortality rates and healthcare costs, as well as the emergence and spread of antibiotic resistant bacteria. As such, new technologies for rapid identification of the pathogen and antimicrobial susceptibility testing are needed. This review summarizes the current technologies, and the promising emerging and future alternatives for the identification and profiling of antimicrobial resistance bacterial agents, which are expected to revolutionize the field of clinical diagnostics.

Identification of bacterial species by untargeted NMR spectroscopy of the exo-metabolome

Identification of bacterial species is a crucial bottleneck for clinical diagnosis of infectious diseases. Quick and reliable identification is a key factor to provide suitable antibiotherapies and avoid the development of multiple-drug resistance. We propose a novel nuclear magnetic resonance (NMR)-based metabolomics strategy for rapid discrimination and identification of several bacterial species that relies on untargeted metabolic profiling of supernatants from bacterial culture media. We show that six bacterial species (Gram negative: Escherichia coli, Pseudomonas aeruginosa, Proteus mirabilis; Gram positive: Enterococcus faecalis, Staphylococcus aureus, and Staphylococcus saprophyticus) can be well discriminated from multivariate statistical analysis, opening new prospects for NMR applications to microbial clinical diagnosis.

Serum procalcitonin levels in combination with (1)H NMR spectroscopy: A rapid indicator for differentiation of urosepsis

BACKGROUND

Urosepsis, a severe form of sepsis requires immediate medical attention for prognosis. It is clinically diagnosed by estimating serum procalcitonin (PCT) levels along with time taking urine and blood cultures. We explored NMR based profiling, deriving metabolites that could potentially aid diagnosis.

METHODS

The proton NMR of serum and urine samples of healthy control subjects (n=32) and urosepsis cases (n=35) based on PCT levels, were analyzed. Four clinically identified non-urosepsis cases with high PCT levels were also differentiated through principal component analysis (PCA) of the serum samples.

RESULTS

Quantification of serum and urine through Discriminant Function Analysis (DFA) afforded 93.7% and 91.7% correct classification respectively, along with identification of malonate and urea as potential biomarkers for the disease in both urine and serum samples. The partial least square discriminant analysis (PLS-DA) showed an R(2) value of 0.97 in both biofluids with Q(2)=0.87 and 0.85 for serum and urine respectively. The training set of serum samples provided precise prediction of the test set in a small cohort through random re-sampling method, while in urine samples, the predictions were inconclusive.

CONCLUSIONS

Our pilot study reveals that (1)H NMR of serum metabolic profiling in combination with PCT levels may provide a rapid method for differentiation of urosepsis.

Nuclear Magnetic Resonance (NMR) as a tool for the study of the metabolism of Rickettsia slovaca

Rickettsial infections are caused by intracellular bacteria. They do not grow in standard culture media so there are limitations in routine practice to study their metabolism. Nuclear Magnetic Resonance (NMR) spectroscopy is used for identification of metabolites in biological samples. Vero cells infected with Rickettsia slovaca as well as uninfected cells were monitored by (1)H NMR showing the presence of ethanol and lactic acid. As no differences were observed, labeled compounds were added into cultures. When D-[1-13C]glucose was monitored by (13)C NMR no differences among infected and uninfected cells were observed in metabolic profiles. Glucose was transformed into ethanol in all cultures. Monitored experiments carried out with [2-13C]glycine showed differences between infected and uninfected cell cultures spectra. Glycine was partially transformed into serine, but the amount of the serine formed was larger in those infected. Moreover, L-[2-13C]leucine, L-[1-13C]isoleucine and L-[15N]tyrosine were evaluated. No differences among infected and uninfected cells were observed in the metabolic profiles when tyrosine and leucine were monitored. The amino acid L-[1-13C]isoleucine exhibited different metabolism in presence of the R. slovaca, showing a promising behavior as biomarker. In this work we focused on finding one or more compounds that could be metabolized specifically by R. slovaca and could be used as an indicator of its activity.

Exploratory analysis of urinary tract infection using a GC-APCI-MS platform

This study shows the first application of GC-APCI-MS in a clinical setting specifically in the context of urinary tract infection.

Quantitative metabolomics of urine for rapid etiological diagnosis of urinary tract infection: evaluation of a microbial-mammalian co-metabolite as a diagnostic biomarker

BACKGROUND

We have previously reported a NMR-based urinalysis for the screening of urinary tract infection (UTI) with high accuracy and reproducibility. Urinary acetic acid per creatinine was found to be a diagnostic marker of bacterial UTI with an area-under-receiver operating characteristic (ROC) curve of 0.97. In addition, we identified trimethylamine (TMA) as a human-microbial marker of Escherichia coli (EC)-associated UTI. Here, we evaluate the clinical application of NMR-based urinalysis in aiding the etiological diagnosis of bacterial UTI.

METHODS

Proton NMR spectroscopy was acquired using a Bruker 600MHz spectroscopy for 88 urine samples from patients with bacterial UTI, confirmed by urine culture. The spectra were analyzed using orthogonal partial least squares-discriminant analysis (OPLS-DA). ROC curve analysis was performed after the quantitation of the urine metabolites.

RESULTS

The TMA/creatinine (mmol/mmol) level was determined to be a specific marker for EC-associated UTI. It has an area-under-ROC=0.85 (95% confidence interval: 0.75-0.91). For the etiological diagnosis, the cutoff for 97.0% specificity was at 0.0117mmol/mmol creatinine for EC-associated UTI with a sensitivity of 66.7%. The mean of TMA/creatinine of EC is 21-fold that of non-EC.

CONCLUSIONS

The co-metabolism of TMA by EC and human cells makes TMA an ideal urine biomarker for UTI. The presence of TMA in a freshly collected sample eliminates the possibility of contamination of urine by bacteria during the collection process resulting in a positive bacterial culture result. We envisage the NMR-based urinalysis of urinary TMA that can be a useful method for the etiological diagnosis of EC-associated UTI.

Nuclear magnetic resonance applied to antimicrobial drug susceptibility

There are many conventional microbiological methods in routine clinical practice to determine the sensitivity of common bacteria. The problem with these methods arises with bacteria that do not grow on habitual media (Rickettsia spp., Coxiella spp. and Anaplasma spp., among others) and for which there are no standardized techniques to determine their antimicrobial susceptibility. In addition, the techniques that are used for the culture of these fastidious bacteria show problems in both accuracy and reproducibility and, in some cases, the in vitro antimicrobial susceptibility of bacteria shows poor correlation with therapeutic outcome. Therefore, it becomes difficult to determine the antimicrobial drug susceptibility of some bacteria and, thus, to assess the therapeutic effect of drugs. The scientific breakthroughs that have taken place in recent years have allowed the use of new techniques that facilitate and improve microbiological study. This paper reviews the use of nuclear magnetic resonance spectroscopy as an alternative tool for determining antimicrobial drug susceptibility.

(1)H NMR-based metabolic profiling of urinary tract infection: combining multiple statistical models and clinical data

Urinary tract infection (UTI) encompasses a variety of clinical syndromes ranging from mild to life-threatening conditions. As such, it represents an interesting model for the development of an analytically based scoring system of disease severity and/or host response. Here we test the feasibility of this concept using (1)H NMR based metabolomics as the analytical platform. Using an exhaustively clinically characterized cohort and taking advantage of the multi-level study design, which opens possibilities for case-control and longitudinal modeling, we were able to identify molecular discriminators that characterize UTI patients. Among those discriminators a number (e.g. acetate, trimethylamine and others) showed association with the degree of bacterial contamination of urine, whereas others, such as, for instance, scyllo-inositol and para-aminohippuric acid, are more likely to be the markers of morbidity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-012-0411-y) contains supplementary material, which is available to authorized users.

Metabolomic investigations of human infections

Metabolomics has a special place among other 'omics' disciplines (genomics, transcriptomics and proteomics) as it describes the most dynamic level of biological regulation and, as such, provides the most direct reflection of the physiological status of an organism. Quick development of the analytical technologies in the first place - MS and NMR - has enabled the metabolomics analysis of such complex biological phenomena as host-pathogen interactions in the development of infection. In this review, an overview of the metabolomics studies of infectious diseases carried out on human material is provided. The relevant papers on the metabolomics of human infectious diseases are comprehensively summarized in a table, including, for example, information on the study design, number of subjects, employed technology and metabolic discriminator. Future considerations, such as importance of the time-resolved study designs and the embedment of metabolomics in large-scale epidemiological studies are discussed.

Metabolomics of urinary tract infection: a new uroscope in town

Urinary tract infection (UTI) is a potentially life-threatening infectious disease. For rapid directed therapy of UTIs, it is essential to determine the causative microorganism. To date, there is no single test that has been proven to reliably, rapidly and accurately identify the etiologic organism in UTI. The molecular methods for diagnosing the cause of UTI and prognostic development of clinically important metabolomic evaluations and their limitations for use in the diagnosis and monitoring of infections are discussed in this review article. The application of the emerging investigative device NMR spectroscopy as a surrogate method for the diagnosis of UTI is also addressed.

Broad identification of bacterial type in urinary tract infection using (1)h NMR spectroscopy

To address the shortcomings of urine culture for the rapid identification of urinary tract infection (UTI), we applied (1)H-nuclear magnetic resonance (NMR) spectroscopy as a surrogate method for fast screening of microorganisms. Study includes 682 urine samples from suspected UTI patients, 50 healthy volunteers, and commercially available standard strains of gram negative bacilli (GNB) (Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumonia, Enterobacter, Acinetobacter, Proteus mirabilis, Citrobacter frundii) and gram positive cocci (GPC) (Enterococcus faecalis, Streptococcus group B, Staphylococcus saprophyticus). Acetate, lactate, ethanol, succinate, creatinine, trimethylamine (TMA), citrate, trimethylamin-N-oxide, glycine, urea, and hippurate were measured by (1)H NMR spectroscopy. All urine specimens were evaluated with culture method. Multivariate discriminant function analysis (DFA) reveals that acetate, lactate, succinate, and formate were able to differentiate, with high accuracy (99.5%), healthy controls from UTI patients. This statistical analysis was also able to classify GNB to GPC infected urine samples with high accuracy (96%). This technique appears to be a promising, rapid, and noninvasive approach to probing GNB and GPC infected urine specimens with its distinguishing metabolic profile. The determination of infection will be very important for rapidly and efficiently measuring the efficacy of a tailored treatment, leading to prompt and appropriate care of UTI patients.

The pharmacological activities of Compound Salvia Plebeia Granules on treating urinary tract infection

AIM OF THE STUDY

Compound Salvia Plebeia Granules (CSPG) had been used for treating urinary tract infection (UTI) for more than 20 years in Drum Tower hospital, but there were lack of sufficient pharmacology studies. The aim of this study was to testify the effects of CSPG on UTI, namely to prove its diuretic, antiblastic, antipyretic and antidynous activities.

MATERIALS AND METHODS

This study evaluated the diuretic effect of CSPG on water load Sprague-Dawley (SD) male rats by the method of metabolic cage, and then analysed the contents of Na(+), K(+), and Cl(-) in urine. The antiblastic activity of CSPG was testified by various kinds of strains in vitro. The antipyretic effect was evaluated by carrageenan-induced fever model in mice. Antidynous activity was demonstrated by the method of acetic acid-induced writhing.

RESULTS

Intragastric (i.g.) administration of CSPG (20-40 g/kg) (equivalent to crude herb) produced a dose-related diuretic effect on water load mice and promoted excreting of Na(+), K(+), and Cl(-) in urine. In addition, the minimal inhibitory concentrations (MICs) of CSPG on Escherichia coli and Staphylococcus aureus were separately 0.25 g/ml and 0.5 g/ml. Moreover, i.g. the doses of CSPG ranging from 25.2 to 50.4 g/kg showed significantly antipyretic effect on carrageenan-induced fever in mice. CSPG (12.6-50.4 g/kg) can also produce dose-related antidynous effects on acetic acid-induced writhing in mice.

CONCLUSIONS

The results described the integrity report of pharmacological studies of CSPG and indicated that it had significantly diuretic, antiblastic, antipyretic, anti-inflammatory and antidynous activities which support its folk medicine use on UTI.

Correlative and quantitative 1H NMR-based metabolomics reveals specific metabolic pathway disturbances in diabetic rats

Type 1 diabetes was induced in Sprague-Dawley rats using streptozotocin. Rat urine samples (8 diabetic and 10 control) were analyzed by 1H nuclear magnetic resonance (NMR) spectroscopy. The derived metabolites using univariate and multivariate statistical analysis were subjected to correlative analysis. Plasma metabolites were measured by a series of bioassays. A total of 17 urinary metabolites were identified in the 1H NMR spectra and the loadings plots after principal components analysis. Diabetic rats showed significantly increased levels of glucose (P < 0.00001), alanine (P < 0.0002), lactate (P < 0.05), ethanol (P < 0.05), acetate (P < 0.05), and fumarate (P < 0.05) compared with controls. Plasma assays showed higher amounts of glucose, urea, triglycerides, and thiobarbituric acid-reacting substances in diabetic rats. Striking differences in the Pearson's correlation of the 17 NMR-detected metabolites were observed between control and diabetic rats. Detailed analysis of the altered metabolite levels and their correlations indicate a significant disturbance in the glucose metabolism and tricarboxylic acid (TCA) cycle and a contribution from gut microbial metabolism. Specific perturbed metabolic pathways include the glucose-alanine and Cori cycles, the acetate switch, and choline metabolism. Detection of the altered metabolic pathways and bacterial metabolites using this correlative and quantitative NMR-based metabolomics approach should help to further the understanding of diabetes-related mechanisms.