Access to highly specialized growth substrates and production of epithelial immunomodulatory metabolites determine survival of Haemophilus influenzae in human airway epithelial cells.

Haemophilus influenzae (Hi) infections are associated with recurring acute exacerbations of chronic respiratory diseases in children and adults including otitis media, pneumonia, chronic obstructive pulmonary disease and asthma. Here, we show that persistence and recurrence of Hi infections are closely linked to Hi metabolic properties, where preferred growth substrates are aligned to the metabolome of human airway epithelial surfaces and include lactate, pentoses, and nucleosides, but not glucose that is typically used for studies of Hi growth in vitro. Enzymatic and physiological investigations revealed that utilization of lactate, the preferred Hi carbon source, required the LldD L-lactate dehydrogenase (conservation: 98.8% of strains), but not the two redox-balancing D-lactate dehydrogenases Dld and LdhA. Utilization of preferred substrates was directly linked to Hi infection and persistence. When unable to utilize L-lactate or forced to rely on salvaged guanine, Hi showed reduced extra- and intra-cellular persistence in a murine model of lung infection and in primary normal human nasal epithelia, with up to 3000-fold attenuation observed in competitive infections. In contrast, D-lactate dehydrogenase mutants only showed a very slight reduction compared to the wild-type strain. Interestingly, acetate, the major Hi metabolic end-product, had anti-inflammatory effects on cultured human tissue cells in the presence of live but not heat-killed Hi, suggesting that metabolic endproducts also influence HI-host interactions. Our work provides significant new insights into the critical role of metabolism for Hi persistence in contact with host cells and reveals for the first time the immunomodulatory potential of Hi metabolites.

Diagnostic performance of expression of PCA3, Hepsin and miR biomarkers inejaculate in combination with serum PSA for the detection of prostate cancer.

BACKGROUND AND METHODS: Here, we report on the evaluation of the diagnostic performance of ejaculate-derived PCA3, Hepsin, and miRNAs to complement serum PSA to detect prostate cancer. cDNA was prepared from 152 candidate specimens following RNA isolation and amplification for PSA, PCA3 and Hepsin qPCR, with 66 having adequate RNA for all three assays. Small RNA sequencing and examination of PCa-associated miRNAs miR-200b, miR-200c, miR-375 and miR-125b was performed on 20 specimens. We compared findings from prostate biopsies using D'Amico and PRIAS classifications and in relation to whole gland histopathology following radical prostatectomy. Multivariate logistic regression modeling and clinical risk (incorporating standard clinicopathological variables) were performed for all ejaculate-based markers. RESULTS: While Hepsin alone was not of predictive value, the Hepsin:PCA3 ratio together with serum PSA, expressed as a univariate composite score based on multivariate logistic regression, was shown to be a better predictor than PSA alone of prostate cancer status (AUC 0.724 vs. 0.676) and risk, using D'Amico (AUC 0.701 vs. 0.680) and PRIAS (AUC 0.679 vs. 0.659) risk stratification criteria as classified using prostate biopsies. It was also possible to analyse a subgroup of patients for miRNA expression with miR-200c (AUC 0.788) and miR-375 (AUC 0.758) showing best single marker performance, while a combination of serum PSA, miR-200c, and miR-125b further improved prediction for prostate cancer status when compared to PSA alone determined by biopsy (AUC 0.869 vs. 0.672; P < 0.05), and risk (D'Amico/PRIAS) as well as by radical prostatectomy histology (AUC 0.809 vs. 0.690). For prostate cancer status by biopsy, at a sensitivity of 90%, the specificity of the test increased from 11% for PSA alone to 67% for a combination of PSA, miR-200c, and miR-125b. CONCLUSIONS: These results show that use of a combination of different types of genetic markers in ejaculate together with serum PSA are at least as sensitive as those reported in DRE urine. Furthermore, a combination of serum PSA and selected miRNAs improved prediction of prostate cancer status. This approach may be helpful in triaging patients for MRI and biopsy, when confirmed by larger studies.

A Genome-Wide Association Study of Serum Metabolite Profiles in Septic Shock Patients.

OBJECTIVES: We sought to assess whether genetic associations with metabolite concentrations in septic shock patients could be used to identify pathways of potential importance for understanding sepsis pathophysiology. DESIGN: Retrospective multicenter cohort studies of septic shock patients. SETTING: All participants who were admitted to 27 participating hospital sites in three countries (Australia, New Zealand, and the United Kingdom) were eligible for inclusion. PATIENTS: Adult, critically ill, mechanically ventilated patients with septic shock (n = 230) who were a subset of the Adjunctive Corticosteroid Treatment in Critically Ill Patients with Septic Shock trial (ClinicalTrials.gov number: NCT01448109). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A genome-wide association study was conducted for a range of serum metabolite levels for participants. Genome-wide significant associations (p ≤ 5 × 10-8) were found for the two major ketone bodies (3-hydroxybutyrate [rs2456680] and acetoacetate [rs2213037] and creatinine (rs6851961). One of these single-nucleotide polymorphisms (SNPs) (rs2213037) was located in the alcohol dehydrogenase cluster of genes, which code for enzymes related to the metabolism of acetoacetate and, therefore, presents a plausible association for this metabolite. None of the three SNPs showed strong associations with risk of sepsis, 28- or 90-day mortality, or Acute Physiology and Chronic Health Evaluation score (a measure of sepsis severity). CONCLUSIONS: We suggest that the genetic associations with metabolites may reflect a starvation response rather than processes involved in sepsis pathophysiology. However, our results require further investigation and replication in both healthy and diseased cohorts including those of different ancestry.

Combined functional genomic and metabolomic approaches identify new genes required for growth in human urine by multidrug-resistant Escherichia coli ST131.

Urinary tract infections (UTIs) are one of the most common bacterial infections in humans, with ~400 million cases across the globe each year. Uropathogenic Escherichia coli (UPEC) is the major cause of UTI and increasingly associated with antibiotic resistance. This scenario has been worsened by the emergence and spread of pandemic UPEC sequence type 131 (ST131), a multidrug-resistant clone associated with extraordinarily high rates of infection. Here, we employed transposon-directed insertion site sequencing in combination with metabolomic profiling to identify genes and biochemical pathways required for growth and survival of the UPEC ST131 reference strain EC958 in human urine (HU). We identified 24 genes required for growth in HU, which mapped to diverse pathways involving small peptide, amino acid and nucleotide metabolism, the stringent response pathway, and lipopolysaccharide biosynthesis. We also discovered a role for UPEC resistance to fluoride during growth in HU, most likely associated with fluoridation of drinking water. Complementary nuclear magnetic resonance (NMR)-based metabolomics identified changes in a range of HU metabolites following UPEC growth, the most pronounced being L-lactate, which was utilized as a carbon source via the L-lactate dehydrogenase LldD. Using a mouse UTI model with mixed competitive infection experiments, we demonstrated a role for nucleotide metabolism and the stringent response in UPEC colonization of the mouse bladder. Together, our application of two omics technologies combined with different infection-relevant settings has uncovered new factors required for UPEC growth in HU, thus enhancing our understanding of this pivotal step in the UPEC infection pathway. IMPORTANCE: Uropathogenic Escherichia coli (UPEC) cause ~80% of all urinary tract infections (UTIs), with increasing rates of antibiotic resistance presenting an urgent threat to effective treatment. To cause infection, UPEC must grow efficiently in human urine (HU), necessitating a need to understand mechanisms that promote its adaptation and survival in this nutrient-limited environment. Here, we used a combination of functional genomic and metabolomic techniques and identified roles for the metabolism of small peptides, amino acids, nucleotides, and L-lactate, as well as the stringent response pathway, lipopolysaccharide biosynthesis, and fluoride resistance, for UPEC growth in HU. We further demonstrated that pathways involving nucleotide metabolism and the stringent response are required for UPEC colonization of the mouse bladder. The UPEC genes and metabolic pathways identified in this study represent targets for the development of innovative therapeutics to prevent UPEC growth during human UTI, an urgent need given the rapidly rising rates of global antibiotic resistance.

Performance evaluation of algorithms for the classification of metabolic 1H NMR fingerprints.

Nontargeted metabolite fingerprinting is increasingly applied to biomedical classification. The choice of classification algorithm may have a considerable impact on outcome. In this study, employing nested cross-validation for assessing predictive performance, six binary classification algorithms in combination with different strategies for data-driven feature selection were systematically compared on five data sets of urine, serum, plasma, and milk one-dimensional fingerprints obtained by proton nuclear magnetic resonance (NMR) spectroscopy. Support Vector Machines and Random Forests combined with t-score-based feature filtering performed well on most data sets, whereas the performance of the other tested methods varied between data sets.

Investigating potential mechanisms of obesity by metabolomics.

Obesity is a serious health problem with an increased risk of several common diseases including diabetes, cardiovascular disease, and cancer. Metabolomics is an emerging analytical technique for systemic determination of metabolite profiles, which is useful for understanding the biochemical changes in obesity or related diseases both in individual organs and at the organism level. Increasingly, this technology has been applied to the study of obesity, complementing transcriptomics and/or proteomics analyses. Indeed, the alterations of metabolites in biofluids/tissues are direct indicators of variations in physiology or pathology. In this paper, we will examine the obesity-related alterations in significant metabolites that have been identified by metabolomics as well as their metabolic pathway associations. Issues concerning the screening of biologically significant metabolites related to obesity will also be discussed.

Folate vitamers in the Australian green plum: Through growth and ripening and across locations.

The green plum is a native fruit of Australia that grows on the tree Buchanania obovata. This study aimed to confirm the high level of folate in green plums by analyzing a large number of ripe samples from multiple locations and to understand how folate vitamers change as the fruit grows through maturity stages. This study analyzed green plums for five vitamers of folate, H4folate, 5-CH3-H4folate, 5-CHO-H4folate, 10-CHO-PteGlu, and PteGlu (folic acid) using a stable isotope dilution assay on a liquid chromatograph mass spectrometer (LC-MS). Green plums were tested from four locations, two harvests and five maturity stages. Another 11 ripe samples, each from different tree clumps from one location, were also tested as were ripe red-colored green plums. The results show the 5-CH3-H4folate in green plum increases and accumulates in the fruit through development, ripening and senescence. The ripe green plums contain between 82.4 ± 5.5 and 149.4 ± 10.7 µg/100 g Fresh Weight (FW). The red-colored green plums are even higher in folate, with total folate measured as 192.5 ± 7.0 and 293.7 ± 27.4 µg/100 g FW, and further analysis of them is suggested. There is some variation in amounts of folate between fruit from different locations and sets of trees, but all ripe green plums tested are considered good dietary sources of folate.

Altered fatty acid metabolism in long duration road transport: An NMR-based metabonomics study in sheep.

The physical, endocrine, and metabolic responses of livestock to road transport have been evaluated by conventional hematological and biochemistry parameters for more than 20 years. However, these measures are relatively insensitive to subtle metabolic adaptations. We applied NMR-based metabonomics to assess system-wide metabolic responses as expressed in urine and serum of a large cohort of animals (n = 80) subjected to 12 and 48 h road transport. The profiling of (1)H NMR spectra revealed that the transported animals experienced altered gut and energy metabolism, muscle catabolism, and possibly a renal response. The animals transported for 48 h exhibited a deeper metabolic response to the transport event and a complex and expanded metabolic trajectory over the 72 h recovery period. Intriguingly, excretion of acyl glycines and a dicarboxylic acid was observed after transport and during recovery, implicating peroxisomal fatty acid oxidation as a metabolic response to transport-induced stress.

The Framework for Responsible Research With Australian Native Plant Foods: A Food Chemist's Perspective.

Australia is a rich source of biodiverse native plants that are mostly unstudied by western food science despite many of them being ethnofoods of Australian Indigenous people. Finding and understanding the relevant policy and legal requirements to scientifically assess these plants in a responsible way is a major challenge for food scientists. This work aims to give an overview of what the legal and policy framework is in relation to food chemistry on Australian native plant foods, to clarify the relationships between the guidelines, laws, policies and ethics and to discuss some of the challenges they present in food chemistry. This work provides the framework of Indigenous rights, international treaties, federal and state laws and ethical guidelines including key legislation and guidelines. It discusses the specific areas that are applicable to food chemistry: the collection of plant foods, the analysis of the samples and working with Indigenous communities. This brief perspective presents a framework that can be utilized by food chemists when developing responsible research involving plant foods native to northern Australia and can help them understand some of the complexity of working in this research area.

Cyanine-5-Driven Behaviours of Hyperbranched Polymers Designed for Therapeutic Delivery Are Cell-Type Specific and Correlated with Polar Lipid Distribution in Membranes.

The ability to predict the behaviour of polymeric nanomedicines can often be obfuscated by subtle modifications to the corona structure, such as incorporation of fluorophores or other entities. However, these interactions provide an intriguing insight into how selection of molecular components in multifunctional nanomedicines contributes to the overall biological fate of such materials. Here, we detail the internalisation behaviours of polymeric nanomedicines across a suite of cell types and extrapolate data for distinguishing the underlying mechanics of cyanine-5-driven interactions as they pertain to uptake and endosomal escape. By correlating the variance of rate kinetics with endosomal escape efficiency and endogenous lipid polarity, we identify that observed cell-type dependencies correspond with an underlying susceptibility to dye-mediated effects and nanomedicine accumulation within polar vesicles. Further, our results infer that the ability to translocate endosomal membranes may be improved in certain cell types, suggesting a potential role for diagnostic moieties in trafficking of drug-loaded nanocarriers.

The Nutritional Potential of the Native Australian Green Plum (Buchanania obovata) Compared to Other Anacardiaceae Fruit and Nuts.

The native Australian green plum (Buchanania obovata) is a small fruit that grows in the northern parts of the Northern Territory and Western Australia. The fruit belongs to the family Anacardiaceae, which includes the other agriculturally important fruit mangoes, pistachios and cashew nuts. The green plum is a favored species of fruit for the Aboriginal communities and an important bush food in the Northern Territory. To date, only minimal scientific studies have been performed on the green plum as a food. This review is about plant foods in the family Anacardiaceae and the key nutritional compounds that occur in these fruit and nuts. It looks at the more traditional nutrient profiles, some key health metabolites, allergens and anti-nutrients that occur, and the role these foods play in the health of populations. This provides a guide for future studies of the green plum to show what nutritional and anti-nutritional properties and compounds should be analyzed and if there are areas where future studies should focus. This review includes an update on studies and analysis of the green plum and how its nutritional properties give it potential as a food for diet diversification in Australia.

Using Genome-Scale Metabolic Networks for Analysis, Visualization, and Integration of Targeted Metabolomics Data.

Interpretation of metabolomics data in the context of biological pathways is important to gain knowledge about underlying metabolic processes. In this chapter we present methods to analyze genome-scale models (GSMs) and metabolomics data together. This includes reading and mining of GSMs using the SBTab format to retrieve information on genes, reactions, and metabolites. Furthermore, the chapter showcases the generation of metabolic pathway maps using the Escher tool, which can be used for data visualization. Lastly, approaches to constrain flux balance analysis (FBA) by metabolomics data are presented.

Haemophilus influenzae Glucose Catabolism Leading to Production of the Immunometabolite Acetate Has a Key Contribution to the Host Airway-Pathogen Interplay.

Chronic obstructive pulmonary disease (COPD) is characterized by abnormal inflammatory responses and impaired airway immunity, which provides an opportunistic platform for nontypeable Haemophilus influenzae (NTHi) infection. Clinical evidence supports that the COPD airways present increased concentrations of glucose, which may facilitate proliferation of pathogenic bacteria able to use glucose as a carbon source. NTHi metabolizes glucose through respiration-assisted fermentation, leading to the excretion of acetate, formate, and succinate. We hypothesized that such specialized glucose catabolism may be a pathoadaptive trait playing a pivotal role in the NTHi airway infection. To find out whether this is true, we engineered and characterized bacterial mutant strains impaired to produce acetate, formate, or succinate by inactivating the ackA, pflA, and frdA genes, respectively. While the inactivation of the pflA and frdA genes only had minimal physiological effects, the inactivation of the ackA gene affected acetate production and led to reduced bacterial growth, production of lactate under low oxygen tension, and bacterial attenuation in vivo. Moreover, bacterially produced acetate was able to stimulate the expression of inflammatory genes by cultured airway epithelial cells. These results back the notion that the COPD lung supports NTHi growth on glucose, enabling production of fermentative end products acting as immunometabolites at the site of infection. Thus, glucose catabolism may contribute not only to NTHi growth but also to bacterially driven airway inflammation. This information has important implications for developing nonantibiotic antimicrobials, given that airway glucose homeostasis modifying drugs could help prevent microbial infections associated with chronic lung disease.

Metabolic analyses reveal common adaptations in two invasive Haemophilus influenzae strains.

Non-typeable Haemophilus influenzae (NTHi) is a major pathogen in upper and lower respiratory tract infections in humans, and is increasingly also associated with invasive disease. We have examined two unrelated NTHi invasive disease isolates, R2866 and C188, in order to identify metabolic and physiological properties that distinguish them from respiratory tract disease isolates such as Hi2019. While the general use of the Hi metabolic network was similar across all three strains, the two invasive isolates secreted increased amounts of succinate, which can have anti-inflammatory properties. In addition, they showed a common shift in their carbon source utilization patterns, with strongly enhanced metabolism of nucleoside substrates, glucose and sialic acid. The latter two are major compounds present in blood and cerebrospinal fluid (CSF). Interestingly, C188 and R2866 also shared a reduced ability to invade or survive intracellularly in 16HBE14 bronchial epithelial cells relative to Hi2019 (4-fold (4 h), 25-fold (24 h) reduction). Altered metabolic properties, such as the ones observed here, could arise from genomic adaptations that NTHi undergo during infection. Together these data indicate that shifts in substrate preferences in otherwise conserved metabolic pathways may underlie strain niche specificity and thus have the potential to alter the outcomes of host-NTHi interactions.

Structural refinement of insecticidal plant proteinase inhibitors from Nicotiana alata.

Ornamental tobacco (Nicotiana alata) produces a series of 6 kDa proteinase inhibitors belonging to the potato type II inhibitor family. These proteins inhibit trypsin and chymotrypsin, the main digestive enzymes of predatory insects, thus leading to starvation, impaired larval development or death. In this context, the three-dimensional structures of these inhibitors are important for developing novel strategies for pest control. The solution structures of C1 and T1, the two main prototypes of the N. alata inhibitors, were originally determined more than a decade ago (J. Mol. Biol. 242, 231-243 (1994) and Biochemistry 34, 14304-14311 (1995)). Since then methods for NMR structure calculations have evolved considerably. Here we report the refinement of the structures of C1 and T1 with state-of-the-art protocols for NMR structure calculations. This refinement leads to an improved quality of the structures, making them a more reliable basis for the development of novel pesticides and modeling applications.

Modeling Meets Metabolomics-The WormJam Consensus Model as Basis for Metabolic Studies in the Model Organism Caenorhabditis elegans.

Metabolism is one of the attributes of life and supplies energy and building blocks to organisms. Therefore, understanding metabolism is crucial for the understanding of complex biological phenomena. Despite having been in the focus of research for centuries, our picture of metabolism is still incomplete. Metabolomics, the systematic analysis of all small molecules in a biological system, aims to close this gap. In order to facilitate such investigations a blueprint of the metabolic network is required. Recently, several metabolic network reconstructions for the model organism Caenorhabditis elegans have been published, each having unique features. We have established the WormJam Community to merge and reconcile these (and other unpublished models) into a single consensus metabolic reconstruction. In a series of workshops and annotation seminars this model was refined with manual correction of incorrect assignments, metabolite structure and identifier curation as well as addition of new pathways. The WormJam consensus metabolic reconstruction represents a rich data source not only for in silico network-based approaches like flux balance analysis, but also for metabolomics, as it includes a database of metabolites present in C. elegans, which can be used for annotation. Here we present the process of model merging, correction and curation and give a detailed overview of the model. In the future it is intended to expand the model toward different tissues and put special emphasizes on lipid metabolism and secondary metabolism including ascaroside metabolism in accordance to their central role in C. elegans physiology.

NMR-Based Metabolomics of Oral Biofluids.

NMR-based metabolomics is an established technique for characterizing the metabolite profile of biological fluids and investigating how metabolite profiles change in response to biological and/or clinical stimuli. Thus, NMR-based metabolomics has the potential to discover biomarkers for diagnosis, prognosis, and/or therapy of clinical conditions, as well as to unravel the physiology underlying clinical conditions. Here, we describe a detailed protocol for NMR-based metabolomics of oral biofluids, including sample collection, sample handling, NMR data acquisition, and processing. In addition, we give a general overview of the statistical analysis of the resulting metabolomic data.

Seminal plasma enables selection and monitoring of active surveillance candidates using nuclear magnetic resonance-based metabolomics: A preliminary investigation.

BACKGROUND: Diagnosis and monitoring of localized prostate cancer requires discovery and validation of noninvasive biomarkers. Nuclear magnetic resonance (NMR)-based metabolomics of seminal plasma reportedly improves diagnostic accuracy, but requires validation in a high-risk clinical cohort. MATERIALS AND METHODS: Seminal plasma samples of 151 men being investigated for prostate cancer were analyzed with 1H-NMR spectroscopy. After adjustment for buffer (add-to-subtract) and endogenous enzyme influence on metabolites, metabolite profiling was performed with multivariate statistical analysis (principal components analysis, partial least squares) and targeted quantitation. RESULTS: Seminal plasma metabolites best predicted low- and intermediate-risk prostate cancer with differences observed between these groups and benign samples. Lipids/lipoproteins dominated spectra of high grade samples with less metabolite contributions. Overall prostate cancer prediction using previously described metabolites was not validated. CONCLUSION: Metabolomics of seminal plasma in vitro may assist urologists with diagnosis and monitoring of either low or intermediate grade prostate cancer. Less clinical benefit may be observed for high-risk patients. Further investigation in active surveillance cohorts, and/or in combination with in vivo magnetic resonance spectroscopic imaging may further optimize localized prostate cancer outcomes.

Prostate-based biofluids for the detection of prostate cancer: A comparative study of the diagnostic performance of cell-sourced RNA biomarkers.

BACKGROUND: Prostate cancer (PCa) diagnosis requires improvement with the aid of more accurate biomarkers. Postejaculate urethral washings (PEUW) could be a physiological equivalent to urine obtained following rectal prostatic massage, the current basis for the prostate cancer antigen 3 (PCA3) test. The aim of this study was to investigate if PEUW contained prostate-based material, evidenced by the presence of prostate specific antigen (PSA), and to evaluate the diagnostic performance of PEUW-based biomarkers. METHODS: Male patients referred for elevated serum PSA or abnormal digital rectal examination provided ejaculate and PEUW samples. PSA, PCA3, and ß2-microglobulin (ß2M) were quantified in ejaculate and PEUW and compared with absolute and clinically significant (according to D'Amico criteria) PCa presence, as determined by biopsies. Diagnostic performance was determined and compared with serum PSA using receiver operating characteristic analysis. RESULTS: From 83 patients who provided PEUW samples, paired analysis with ejaculate samples was possible for 38 patients, while analysis in an unpaired, extended cohort was possible for 62 patients. PSA and PCA3 were detected in PEUW, normalized to ß2M, and PCA3:PSA was calculated. In predicting absolute PCa status, PCA3:ß2M in ejaculate [area under the curve (AUC) 0.717] and PEUW (AUC 0.569) were insignificantly better than PCA3:PSA (AUC 0.668 and 0.431, respectively) and comparable with serum PSA (AUC 0.617) with similar trends observed for the extended cohort. When considering clinically significant PCa presence, serum PSA in the comparison (AUC 0.640) and extended cohorts (AUC 0.665) was comparable with PCA3: ß2M (AUC 0.667) and PCA3:PSA (AUC 0.605) in ejaculate, with lower estimates for PEUW in the comparison (PCA3: ß2M AUC 0.496; PCA3:PSA AUC 0.342) and extended (PCA3: ß2M AUC 0.497; PCA3:PSA AUC 0.469) cohorts. The statistical analysis was limited by sample size. CONCLUSION: PEUW contains prostatic material, but has limited diagnostic accuracy when considering cell-derived DNA analysis. PCA3-based markers in ejaculate are comparable to serum PSA and digital rectal examination-urine markers.

Can atorvastatin with metformin change the natural history of prostate cancer as characterized by molecular, metabolomic, imaging and pathological variables? A randomized controlled trial protocol.

BACKGROUND: Atorvastatin and metformin are known energy restricting mimetic agents that act synergistically to produce molecular and metabolic changes in advanced prostate cancer (PCa). This trial seeks to determine whether these drugs favourably alter selected parameters in men with clinically-localized, aggressive PCa. METHODS/DESIGN: This prospective phase II randomized, controlled window trial is recruiting men with clinically significant PCa, confirmed by biopsy following multiparametric MRI and intending to undergo radical prostatectomy. Ethical approval was granted by the Royal Brisbane and Women's Hospital Human and The University of Queensland Medical Research Ethics Committees. Participants are being randomized into four groups: metformin with placebo; atorvastatin with placebo; metformin with atorvastatin; or placebo alone. Capsules are consumed for 8weeks, a duration selected as the most appropriate period in which histological and biochemical changes may be observed while allowing prompt treatment with curative intent of clinically significant PCa. At recruitment and prior to RP, participants provide blood, urine and seminal fluid. A subset of participants will undergo 7Tesla magnetic resonance spectroscopy to compare metabolites in-vivo with those in seminal fluid and biopsied tissue. The primary end point is biochemical evolution, defined using biomarkers (serum prostate specific antigen; PCA3 and citrate in seminal fluid and prostatic tissue). Standard pathological assessment will be undertaken. DISCUSSION: This study is designed to assess the potential synergistic action of metformin and atorvastatin on PCa tumour biology. The results may determine simple methods of tumour modulation to reduce disease progression.