Effect of light on ex situ production of symbiotic corals

The increasing interest in coral culture for biotechnological applications, to supply the marine aquarium trade, or for reef restoration programs, has prompted researchers to optimize coral culture protocols, with emphasis to ex situ production. When cultured ex situ, the growth performance of corals can be influenced by several physical, chemical and biological parameters. For corals harbouring zooxanthellae, light is one of such key factors, as it can influence the photosynthetic performance of these endosymbionts, as well as coral physiology, survival and growth. The economic feasibility of ex situ coral aquaculture is strongly dependent on production costs, namely those associated with the energetic needs directly resulting from the use of artificial lighting systems. In the present study we developed a versatile modular culture system for experimental coral production ex situ, assembled solely using materials and equipment readily available from suppliers all over the world; this approach allows researchers from different institutions to perform truly replicated experimental set-ups, with the possibility to directly compare experimental results. Afterwards, we aimed to evaluate the effect of contrasting Photosynthetically Active Radiation (PAR) levels, and light spectra emission on zooxanthellae photochemical performance, through the evaluation of the maximum quantum yield of PSII (Fv/Fm) (monitored non-invasively and non-destructively through Pulse Amplitude Modulation fluorometry, PAM), chlorophyll a content (also determined non-destructively by using the spectral reflectance index Normalized Difference Vegetation Index, NDVI), photosynthetic and accessory pigments, number of zooxanthellae, coral survival and growth. We studied two soft coral species, Sarcophyton cf. glaucum and Sinularia flexibilis, as they are good representatives of two of the most specious genera in family Alcyoniidae, which include several species with interest for biotechnological applications, as well as for the marine aquarium trade; we also studied two commercially important scleractinian corals: Acropora formosa and Stylophora pistillata. We used different light sources: hydrargyrum quartz iodide (HQI) lamps with different light color temperatures, T5 fluorescent lamps, Light Emitting Plasma (LEP) and Light Emitting Diode (LED). The results achieved revealed that keeping S. flexibilis fragments under the same light conditions as their mother colonies seems to be photobiologically acceptable for a short-term husbandry, notwithstanding the fact that they can be successfully stocked at lower PAR intensities. We also proved that low PAR intensities are suitable to support the ex situ culture S. cf. glaucum in captivity at lower production costs, since the survival recorded during the experiment was 100%, the physiological wellness of coral fragments was evidenced, and we did not detect significant differences in coral growth. Finally, we concluded that blue light sources, such as LED lighting, allow a higher growth for A. formosa and S. pistillata, and promote significant differences on microstructure organization and macrostructure morphometry in coral skeletons; these findings may have potential applications as bone graft substitutes for veterinary and/or other medical uses. Thus, LED technology seems to be a promising option for scleractinian corals aquaculture ex situ.

Nanosensor for assessing the risk of a cardiovascular disease

The incidence of cardiovascular diseases (CVD) has been increasing according to the European and global statistics. Thus, the development of new analytical devices, such as biosensors for assessing the risk of CVD could become a valuable approach for the improvement of healthcare service. In latest years, the nanotechnology has provided new materials with improved electronic properties which have an important contribution in the transduction mechanism of biosensors. Thus, in this thesis, biosensors based on field effect transistors with single-walled carbon nanotubes (NTFET) were developed for the detection of C-reactive protein (CRP) in clinical samples, that is, blood serum and saliva from a group of control patients and a group of CVD risk patients. CRP is an acute-phase protein, which is commonly known as the best validated biomarker for the assessment of CVD, the single-walled carbon nanotubes (SWCNT) were applied as transduction components, and the immunoreaction (interaction between the CRP antigen and the antibodies specific to CRP) was used as the mechanism of molecular recognition for the label-free detection of CRP. After the microfabrication of field effect transistors (FET), the screening of the most important variables for the dispersion of SWCNT, the assemblage of NTFET, and their application on standard solutions of CRP, it was found that NTFET respond accurately to CRP both in saliva and in serum samples, since similar CRP levels were found with the NTFET and the traditional methodology (ELISA technique). On the other hand, a strong correlation between salivary and serum CRP was found with NTFET, which means that saliva could be used, based on non-invasive sampling, as an alternative fluid to blood serum. It was also shown that NTFET could discriminate control patients from CVD risk patients, allowing the determination of a cut-off value for salivary CRP of 1900 ng L-1, which corresponds to the well established cut-off of 3 mg L-1 for CRP in serum, constituting an important finding for the possible establishment of a new range of CRP levels based on saliva. According to the data provided from the volunteer patients regarding their lipoprotein profile and lifestyle factors, it was concluded that the control and the CVD risk patients could be separated taking into account the various risk factors established in literature as strong contributors for developing a CVD, such as triglycerides, serum CRP, total cholesterol, LDL cholesterol, body mass index, Framingham risk score, hypertension, dyslipidemia, and diabetes mellitus. Thus, this work could provide an additional contribution to the understanding of the association of biomarkers levels in serum and saliva samples, and above all, cost-effective, rapid, label-free, and disposable NTFET were developed, based on a noninvasive sampling, for the assessment of CVD risk, thus constituting a potential point-of-care technology.

Metabolic signature of lung cancer: a metabolomic study of human tissues and biofluids

This thesis reports the application of metabolomics to human tissues and biofluids (blood plasma and urine) to unveil the metabolic signature of primary lung cancer. In Chapter 1, a brief introduction on lung cancer epidemiology and pathogenesis, together with a review of the main metabolic dysregulations known to be associated with cancer, is presented. The metabolomics approach is also described, addressing the analytical and statistical methods employed, as well as the current state of the art on its application to clinical lung cancer studies. Chapter 2 provides the experimental details of this work, in regard to the subjects enrolled, sample collection and analysis, and data processing. In Chapter 3, the metabolic characterization of intact lung tissues (from 56 patients) by proton High Resolution Magic Angle Spinning (HRMAS) Nuclear Magnetic Resonance (NMR) spectroscopy is described. After careful assessment of acquisition conditions and thorough spectral assignment (over 50 metabolites identified), the metabolic profiles of tumour and adjacent control tissues were compared through multivariate analysis. The two tissue classes could be discriminated with 97% accuracy, with 13 metabolites significantly accounting for this discrimination: glucose and acetate (depleted in tumours), together with lactate, alanine, glutamate, GSH, taurine, creatine, phosphocholine, glycerophosphocholine, phosphoethanolamine, uracil nucleotides and peptides (increased in tumours). Some of these variations corroborated typical features of cancer metabolism (e.g., upregulated glycolysis and glutaminolysis), while others suggested less known pathways (e.g., antioxidant protection, protein degradation) to play important roles. Another major and novel finding described in this chapter was the dependence of this metabolic signature on tumour histological subtype. While main alterations in adenocarcinomas (AdC) related to phospholipid and protein metabolisms, squamous cell carcinomas (SqCC) were found to have stronger glycolytic and glutaminolytic profiles, making it possible to build a valid classification model to discriminate these two subtypes. Chapter 4 reports the NMR metabolomic study of blood plasma from over 100 patients and near 100 healthy controls, the multivariate model built having afforded a classification rate of 87%. The two groups were found to differ significantly in the levels of lactate, pyruvate, acetoacetate, LDL+VLDL lipoproteins and glycoproteins (increased in patients), together with glutamine, histidine, valine, methanol, HDL lipoproteins and two unassigned compounds (decreased in patients). Interestingly, these variations were detected from initial disease stages and the magnitude of some of them depended on the histological type, although not allowing AdC vs. SqCC discrimination. Moreover, it is shown in this chapter that age mismatch between control and cancer groups could not be ruled out as a possible confounding factor, and exploratory external validation afforded a classification rate of 85%. The NMR profiling of urine from lung cancer patients and healthy controls is presented in Chapter 5. Compared to plasma, the classification model built with urinary profiles resulted in a superior classification rate (97%). After careful assessment of possible bias from gender, age and smoking habits, a set of 19 metabolites was proposed to be cancer-related (out of which 3 were unknowns and 6 were partially identified as N-acetylated metabolites). As for plasma, these variations were detected regardless of disease stage and showed some dependency on histological subtype, the AdC vs. SqCC model built showing modest predictive power. In addition, preliminary external validation of the urine-based classification model afforded 100% sensitivity and 90% specificity, which are exciting results in terms of potential for future clinical application. Chapter 6 describes the analysis of urine from a subset of patients by a different profiling technique, namely, Ultra-Performance Liquid Chromatography coupled to Mass Spectrometry (UPLC-MS). Although the identification of discriminant metabolites was very limited, multivariate models showed high classification rate and predictive power, thus reinforcing the value of urine in the context of lung cancer diagnosis. Finally, the main conclusions of this thesis are presented in Chapter 7, highlighting the potential of integrated metabolomics of tissues and biofluids to improve current understanding of lung cancer altered metabolism and to reveal new marker profiles with diagnostic value.