Independent Validation and Assay Standardization of Improved Metabolic Biomarker Signature to Differentiate Pancreatic Ductal Adenocarcinoma From Chronic Pancreatitis.

BACKGROUND & AIMS: Pancreatic ductal adenocarcinoma cancer (PDAC) is a highly lethal malignancy requiring efficient detection when the primary tumor is still resectable. We previously developed the MxPancreasScore comprising 9 analytes and serum carbohydrate antigen 19-9 (CA19-9), achieving an accuracy of 90.6%. The necessity for 5 different analytical platforms and multiple analytical runs, however, hindered clinical applicability. We therefore aimed to develop a simpler single-analytical run, single-platform diagnostic signature. METHODS: We evaluated 941 patients (PDAC, 356; chronic pancreatitis [CP], 304; nonpancreatic disease, 281) in 3 multicenter independent tests, and identification (ID) and validation cohort 1 (VD1) and 2 (VD2) were evaluated. Targeted quantitative plasma metabolite analysis was performed on a liquid chromatography-tandem mass spectrometry platform. A machine learning-aided algorithm identified an improved (i-Metabolic) and minimalistic metabolic (m-Metabolic) signatures, and compared them for performance. RESULTS: The i-Metabolic Signature, (12 analytes plus CA19-9) distinguished PDAC from CP with area under the curve (95% confidence interval) of 97.2% (97.1%-97.3%), 93.5% (93.4%-93.7%), and 92.2% (92.1%-92.3%) in the ID, VD1, and VD2 cohorts, respectively. In the VD2 cohort, the m-Metabolic signature (4 analytes plus CA19-9) discriminated PDAC from CP with a sensitivity of 77.3% and specificity of 89.6%, with an overall accuracy of 82.4%. For the subset of 45 patients with PDAC with resectable stages IA-IIB tumors, the sensitivity, specificity, and accuracy were 73.2%, 89.6%, and 82.7%, respectively; for those with detectable CA19-9 >2 U/mL, 81.6%, 88.7%, and 84.5%, respectively; and for those with CA19-9 <37 U/mL, 39.7%, 94.1%, and 76.3%, respectively. CONCLUSIONS: The single-platform, single-run, m-Metabolic signature of just 4 metabolites used in combination with serum CA19-9 levels is an innovative accurate diagnostic tool for PDAC at the time of clinical presentation, warranting further large-scale evaluation.

Soybean Yield Formation Physiology - A Foundation for Precision Breeding Based Improvement.

The continued improvement of crop yield is a fundamental driver in agriculture and is the goal of both plant breeders and researchers. Plant breeders have been remarkably successful in improving crop yield, as demonstrated by the continued release of varieties with improved yield potential. This has largely been accomplished through performance-based selection, without specific knowledge of the molecular mechanisms underpinning these improvements. Insight into molecular mechanisms has been provided by plant molecular, genetic, and biochemical research through elucidation of the function of genes and pathways that underlie many of the physiological processes that contribute to yield potential. Despite this knowledge, the impact of most genes and pathways on yield components have not been tested in key crops or in a field environment for yield assessment. This gap is difficult to bridge, but field-based physiological knowledge offers a starting point for leveraging molecular targets to successfully apply precision breeding technologies such as genome editing. A better understanding of both the molecular mechanisms underlying crop yield physiology and yield limiting processes under field conditions is essential for elucidating which combinations of favorable alleles are required for yield improvement. Consequently, one goal in plant biology should be to more fully integrate crop physiology, breeding, genetics, and molecular knowledge to identify impactful precision breeding targets for relevant yield traits. The foundation for this is an understanding of yield formation physiology. Here, using soybean as an example, we provide a top-down review of yield physiology, starting with the fact that yield is derived from a population of plants growing together in a community. We review yield and yield-related components to provide a basic overview of yield physiology, synthesizing these concepts to highlight how such knowledge can be leveraged for soybean improvement. Using genome editing as an example, we discuss why multiple disciplines must be brought together to fully realize the promise of precision breeding-based crop improvement.

Plasma Metabolome Profiling Identifies Metabolic Subtypes of Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers. Developing biomarkers for early detection and chemotherapeutic response prediction is crucial to improve the dismal prognosis of PDAC patients. However, molecular cancer signatures based on transcriptome analysis do not reflect intratumoral heterogeneity. To explore a more accurate stratification of PDAC phenotypes in an easily accessible matrix, plasma metabolome analysis using MxP® Global Profiling and MxP® Lipidomics was performed in 361 PDAC patients. We identified three metabolic PDAC subtypes associated with distinct complex lipid patterns. Subtype 1 was associated with reduced ceramide levels and a strong enrichment of triacylglycerols. Subtype 2 demonstrated increased abundance of ceramides, sphingomyelin and other complex sphingolipids, whereas subtype 3 showed decreased levels of sphingolipid metabolites in plasma. Pathway enrichment analysis revealed that sphingolipid-related pathways differ most among subtypes. Weighted correlation network analysis (WGCNA) implied PDAC subtypes differed in their metabolic programs. Interestingly, a reduced expression among related pathway genes in tumor tissue was associated with the lowest survival rate. However, our metabolic PDAC subtypes did not show any correlation to the described molecular PDAC subtypes. Our findings pave the way for further studies investigating sphingolipids metabolisms in PDAC.

Identification and validation of a multivariable prediction model based on blood plasma and serum metabolomics for the distinction of chronic pancreatitis subjects from non-pancreas disease control subjects.

OBJECTIVE: Chronic pancreatitis (CP) is a fibroinflammatory syndrome leading to organ dysfunction, chronic pain, an increased risk for pancreatic cancer and considerable morbidity. Due to a lack of specific biomarkers, diagnosis is based on symptoms and specific but insensitive imaging features, preventing an early diagnosis and appropriate management. DESIGN: We conducted a type 3 study for multivariable prediction for individual prognosis according to the TRIPOD guidelines. A signature to distinguish CP from controls (n=160) was identified using gas chromatography-mass spectrometry and liquid chromatography-tandem mass spectrometry on ethylenediaminetetraacetic acid (EDTA)-plasma and validated in independent cohorts. RESULTS: A Naive Bayes algorithm identified eight metabolites of six ontology classes. After algorithm training and computation of optimal cut-offs, classification according to the metabolic signature detected CP with an area under the curve (AUC) of 0.85 ((95% CI 0.79 to 0.91). External validation in two independent cohorts (total n=502) resulted in similar accuracy for detection of CP compared with non-pancreatic controls in EDTA-plasma (AUC 0.85 (95% CI 0.81 to 0.89)) and serum (AUC 0.87 (95% CI 0.81 to 0.95)). CONCLUSIONS: This is the first study that identifies and independently validates a metabolomic signature in plasma and serum for the diagnosis of CP in large, prospective cohorts. The results could provide the basis for the development of the first routine laboratory test for CP.

Effects of Long-Term Storage at -80 °C on the Human Plasma Metabolome.

High-quality biological samples are required for the favorable outcome of research studies, and valid data sets are crucial for successful biomarker identification. Prolonged storage of biospecimens may have an artificial effect on compound levels. In order to investigate the potential effects of long-term storage on the metabolome, human ethylenediaminetetraacetic acid (EDTA) plasma samples stored for up to 16 years were analyzed by gas and liquid chromatography-tandem mass spectrometry-based metabolomics. Only 2% of 231 tested plasma metabolites were altered in the first seven years of storage. However, upon longer storage periods of up to 16 years and more time differences of few years significantly affected up to 26% of the investigated metabolites when analyzed within subject age groups. Ontology classes that were most affected included complex lipids, fatty acids, energy metabolism molecules, and amino acids. In conclusion, the human plasma metabolome is adequately stable to long-term storage at -80 °C for up to seven years but significant changes occur upon longer storage. However, other biospecimens may display different sensitivities to long-term storage. Therefore, in retrospective studies on EDTA plasma samples, analysis is best performed within the first seven years of storage.

The impact of urbanisation on community structure, gene abundance and transcription rates of microbes in upland swamps of Eastern Australia.

The Temperate Highland Peat Swamps on Sandstone of the Sydney Basin occur in the headwaters of Sydney's drinking water catchments and are listed as endangered ecosystems, yet they have suffered habitat losses and degradation due to human impacts such as urbanisation. Despite ongoing efforts to restore and better protect upland swamps, they remain poorly understood, potentially hindering the effectiveness of management efforts. Essential to overall ecosystem function and the provision of services for human and environmental benefit are the microbial component of wetland ecosystems. In the case of these swamps, the microbes, have not yet been studied. Here, we investigated differences in the microbial community of upland swamps in urbanised catchments compared to swamps from natural catchments in the Blue Mountains. A total of twelve swamps were sampled, six from within urbanised catchments and six with intact vegetation catchments, to compare sediment conditions and microbial community and genes expression and abundances. Catchment impervious area and number of stormwater drains entering a swamp, indicators for urbanisation, positively correlated with the pH and ammonium concentration of swamp sediment. Community analysis of the 16S rRNA gene (T-RFLP, qPCR) revealed the elevated pH of urbanised swamps coincided with changes to the abundance of bacteria and archaea. Furthermore, RT-qPCR revealed genes involved in carbon cycling (mcrA & pmoA) were more likely to be found in urbanised swamps. Taken together, our results indicate that urbanisation of the Blue Mountains is impacting the environmental services provided by the microbial community of upland swamps in the Sydney Basin.

Comprehensive plasma and tissue profiling reveals systemic metabolic alterations in cardiac hypertrophy and failure.

AIMS: Heart failure is characterized by structural and metabolic cardiac remodelling. The aim of the present study is to expand our understanding of the complex metabolic alterations in the transition from pathological hypertrophy to heart failure and exploit the results from a translational perspective. METHODS AND RESULTS: Mice were subjected to transverse aortic constriction (TAC) or sham surgery and sacrificed 2 weeks, 4 weeks, or 6 weeks after the procedure. Samples from plasma, liver, skeletal muscle, and heart were collected and analysed using metabolomics. Cardiac samples were also analysed by transcriptional profiling. Progressive alterations of key cardiac metabolic pathways and gene expression patterns indicated impaired mitochondrial function and a metabolic switch during transition to heart failure. Similar to the heart, liver, and skeletal muscle revealed significant metabolic alterations such as depletion of essential fatty acids and glycerolipids in late stages of heart failure. Circulating metabolites, particularly fatty acids, reflected cardiac metabolic defects, and deteriorating heart function. For example, inverse correlation was found between plasma and the heart levels of triacylglycerol (C18:1, C18:2, C18:3), and sphingomyelin (d18:1, C23:0) already at an early stage of heart failure. Interestingly, combining metabolic and transcriptional data from cardiac tissue revealed that decreased carnitine shuttling and transportation preceded mitochondrial dysfunction. We, thus, studied the therapeutic potential of OCTN2 (Organic Cation/Carnitine Transporter 2), an important factor for carnitine transportation. Cardiac overexpression of OCTN2 using an adeno-associated viral vector significantly improved ejection fraction and reduced interstitial fibrosis in mice subjected to TAC. CONCLUSION: Comprehensive plasma and tissue profiling reveals systemic metabolic alterations in heart failure, which can be used for identification of novel biomarkers and potential therapeutic targets.

Inhibition of saturated very-long-chain fatty acid biosynthesis by mefluidide and perfluidone, selective inhibitors of 3-ketoacyl-CoA synthases.

The trifluoromethanesulphonanilides mefluidide and perfluidone are used in agriculture as plant growth regulators and herbicides. Despite the fact that mefluidide and perfluidone have been investigated experimentally for decades, their mode of action is still unknown. In this study, we used a cascade approach of different methods to clarify the mode of action and target site of mefluidide and perfluidone. Physiological profiling using an array of biotests and metabolic profiling in treated plants of Lemna paucicostata suggested a common mode of action in very-long-chain fatty acid (VLCFA) synthesis similar to the known 3-ketoacyl-CoA synthase (KCS) inhibitor metazachlor. Detailed analysis of fatty acid composition in Lemna plants showed a decrease of saturated VLCFAs after treatment with mefluidide and perfluidone. To study compound effects on enzyme level, recombinant KCSs from Arabidopsis thaliana were expressed in Saccharomyces cerevisiae. Enzyme activities of seven KCS proteins from 17 tested were characterized by their fatty acid substrate and product spectrum. For the KCS CER6, the VLCFA product spectrum in vivo, which consists of tetracosanoic acid, hexacosanoic acid and octacosanoic acid, is reported here for the first time. Similar to metazachlor, mefluidide and perfluidone were able to inhibit KCS1, CER6 and CER60 enzyme activities in vivo. FAE1 and KCS2 were inhibited by mefluidide only slightly, whereas metazachlor and perfluidone were strong inhibitors of these enzymes with IC(50) values in µM range. This suggests that KCS enzymes in VLCFA synthesis are the primary herbicide target of mefluidide and perfluidone.

On the mode of action of the herbicides cinmethylin and 5-benzyloxymethyl-1, 2-isoxazolines: putative inhibitors of plant tyrosine aminotransferase.

BACKGROUND: The mode of action of the grass herbicides cinmethylin and 5-benzyloxymethyl-1,2-isoxazolines substituted with methylthiophene (methiozolin) or pyridine (ISO1, ISO2) was investigated. RESULTS: Physiological profiling using a series of biotests and metabolic profiling in treated duckweed (Lemna paucicostata L.) suggested a common mode of action for the herbicides. Symptoms of growth inhibition and photobleaching of new fronds in Lemna were accompanied with metabolite changes indicating an upregulation of shikimate and tyrosine metabolism, paralleled by decreased plastoquinone and carotenoid synthesis. Supplying Lemna with 10 µM of 4-hydroxyphenylpyruvate (4-HPP) reversed phytotoxic effects of cinmethylin and isoxazolines to a great extent, whereas the addition of L-tyrosine was ineffective. It was hypothesised that the herbicides block the conversion of tyrosine to 4-HPP, catalysed by tyrosine aminotransferase (TAT), in the prenylquinone pathway which provides plastoquinone, a cofactor of phytoene desaturase in carotenoid synthesis. Accordingly, enhanced resistance to ISO1 treatment was observed in Arabidopsis thaliana L. mutants, which overexpress the yeast prephenate dehydrogenase in plastids as a TAT bypass. In addition, the herbicides were able to inhibit TAT7 activity in vitro for the recombinant enzyme of A. thaliana. CONCLUSION: The results suggest that TAT7 or another TAT isoenzyme is the putative target of the herbicides.

Physionomics and metabolomics-two key approaches in herbicidal mode of action discovery.

BACKGROUND: For novel herbicides identified in greenhouse screens, efficient research is important to discover and chemically optimise new leads with new modes of action (MoAs). RESULTS: The metabolic and physiological response pattern to a herbicide can be viewed as the result of changes elicited in the molecular and biochemical process chain. These response patterns are diagnostic of a herbicide's MoA. At the starting point of MoA characterisation, an array of bioassays is used for comprehensive physiological profiling of herbicide effects. This physionomics approach enables discrimination between known, novel or multiple MoAs of a compound and provides a first clue to a new MoA. Metabolic profiling is performed with the use of treated Lemna paucicostata plants. After plant extraction and chromatography and mass spectrometry, changes in levels of approximately 200 identified and 300 unknown analytes are quantified. Check for known MoA assignment is performed by multivariate statistical data analyses. Distinct metabolite changes, which can direct to an affected enzymatic step, are visualised in a biochemical pathway view. Subsequent target identification includes metabolite feeding and molecular, biochemical and microscopic methods. CONCLUSION: The value of this cascade strategy is exemplified by new herbicides with MoAs in plastoquinone, auxin or very-long-chain fatty acid synthesis.