Variability of Bile Baseline Excitation-emission Fluorescence of Two Tropical Freshwater Fish Species.

The quantification of pollutant metabolites in fish bile is an efficient approach to xenobiotic pollution monitoring in freshwaters since these measurements directly address exposure. Fluorescence excitation-emission matrix spectroscopy (EEMS) has demonstrated to be a highly specific and cost-effective technique for polycyclic aromatic hydrocarbon (PAH) and PAH-metabolite identification and quantification. EEMS ability to quantify these compounds strongly depends on the intensity and variability of the bile baseline fluorescence (BBF). We found large differences in BBF among Aequidens metae (AME) individuals and of these with Piaractus orinoquensis (PIO). Moreover, BBF was large enough that solvent dilutions of over 1:400 were needed to avoid inner filter effects. We used parallel factor analysis (PARAFAC) to model the intra- and inter-species BBF variability. PARAFAC successfully decomposed the EEMS set into three fluorophores present in all samples, although in concentrations spreading over ~ 3 orders of magnitude. One of the factors was identified as tryptophan. Tryptophan and Factor 2 were covariant and much more abundant in AME than in PIO, while Factor 3 was ~ 6 times more abundant in PIO than in AME. Also, tryptophan was ~ 10x more abundant in AME specimens immediately caught in rivers than in their laboratory-adapted peers. The PARAFAC decomposition effectiveness was confirmed by the positive proportionality of scores to dilution ratios. A large inner filter indicates that Factor 2 is as strong a light absorber as tryptophan. Our results stress the need to include bile matrix variable components for the detection and quantification of pollutant metabolites using PARAFAC.

Introducing the multi-dimensional spectral phasors: a tool for the analysis of fluorescence excitation-emission matrices.

The use of phasors to analyze fluorescence data was first introduced for time-resolved studies for a simpler mathematical analysis of the fluorescence-decay curves. Recently, this approach was extended to steady-state experiments with the introduction of the spectral phasors (SP), derived from the Fourier transform of the fluorescence emission spectrum. In this work, we revise key mathematical aspects that lead to an interpretation of SP as the characteristic function of a probability distribution. This formalism allows us to introduce a new tool, called multi-dimensional spectral phasor (MdSP) that seize, not only the information from the emission spectrum, but from the full excitation-emission matrix (EEM). In addition, we developed a homemade open-source Java software to facilitate the MdSP data processing. Due to this mathematical conceptualization, we settled a mechanism for the use of MdSP as a tool to tackle spectral signal unmixing problems in a more accurate way than SP. As a proof of principle, with the use of MdSP we approach two important biophysical questions: protein conformational changes and protein-ligand interactions. Specifically, we experimentally measure the EEM changes upon denaturation of human serum albumin (HSA) or during its association with the fluorescence dye 1,8-anilinonaphtalene sulphate (ANS) detected via tryptophan-ANS Förster Resonance Energy Transfer (FRET). In this sense, MdSP allows us to obtain information of the system in a simpler and finer way than the traditional SP. Specifically, understanding a protein's EEM as a molecular fingerprint opens new doors for the use of MdSP as a tool to analyze and comprehend protein conformational changes and interactions.