MCR-ALS analysis of 1H NMR spectra by segments to study the zebrafish exposure to acrylamide

Multivariate curve resolution-based data fusion approaches applied in 1H NMR metabolomic analysis of healthy cohorts

BACKGROUND

Metabolomics plays a critical role in deciphering metabolic alterations within individuals, demanding the use of sophisticated analytical methodologies to navigate its intricate complexity. While many studies focus on single biofluid types, simultaneous analysis of multiple matrices enhances understanding of complex biological mechanisms. Consequently, the development of data fusion methods enabling multiblock analysis becomes essential for comprehensive insights into metabolic dynamics.

RESULTS

This study introduces a novel guideline for jointly analyzing diverse metabolomic datasets (serum, urine, metadata) with a focus on metabolic differences between groups within a healthy cohort. The guideline presents two fusion strategies, 'Low-Level data fusion' (LLDF) and 'Mid-Level data fusion' (MLDF), employing a sequential application of Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS), linking the outcomes of successive analyses. MCR-ALS is a versatile method for analyzing mixed data, adaptable at various stages of data processing-encompassing resonance integration, data compression, and exploratory analysis. The LLDF and MLDF strategies were applied to 1H NMR spectral data extracted from urine and serum samples, coupled with biochemical metadata sourced from 145 healthy volunteers.

SIGNIFICANCE

Both methodologies effectively integrated and analysed multiblock datasets, unveiling the inherent data structure and variables associated with discernible factors among healthy cohorts. While both approaches successfully detected sex-related differences, the MLDF strategy uniquely revealed components linked to age. By applying this analysis, we aim to enhance the interpretation of intricate biological mechanisms and uncover variations that may not be easily discernible through individual data analysis.

Application of segmented analysis via multivariate curve resolution with alternating least squares to 1H-nuclear magnetic resonance spectroscopy to identify different sugar sources

The different types of sugar employed in the food industry exhibit chemical similarity and are mostly dominated by sucrose. Owing to the sugar origin of and differences in production, the presence of certain minor organic compounds differs. To differentiate between sugars based on their botanical source, geographical origin, or storage conditions, commercial brown sugars and sugar beet extracts were analyzed by ¹H NMR spectroscopy applying a segmented analysis by means of multivariate curve resolution-alternating least squares (MCR-ALS). Principal component analysis and partial least squares-discriminant analysis yielded excellent differentiation between sugars from different sources after the application of this preprocessing strategy; without loss of chemical information and with direct interpretation of the results. By applying a segmented analysis via MCR-ALS to ¹H NMR sugar data, similar spectroscopic profiles could be differentiated. This improved the selectivity of ¹H NMR spectroscopy for sugar source differentiation which can be useful for industrial sugar authentication purposes.

NMR-based metabolomics applied to ecotoxicology with zebrafish (Danio rerio) as a prominent model for metabolic profiling and biomarker discovery: Overviewing the most recent approaches

Metabolomics is an innovative approach used in the medical, toxicological, and biological sciences. As an interdisciplinary topic, metabolomics and its relation with the environment and toxicological research are extensive. The use of substances, such as drugs and pesticides, contributes to the continuous releasing of xenobiotics into the environment, harming organisms and their habitats. In this context, fish are important bioindicators of the environmental condition and have often been used as model species. Among them, zebrafish (Danio rerio) presents itself as a versatile and straightforward option due to its unique attributes for research. Zebrafish proves to be a valuable model for toxicity assays and also for metabolomics profiling by analytical tools. Thus, NMR-based metabolomics associated with statistical analysis can reasonably assist researchers in critical factors related to discovering and validating biomarkers through accurate diagnosis. Therefore, this review aimed to report the studies that applied zebrafish as a model for (eco)toxicological assays and essentially utilized NMR-based metabolomics analysis to assess the biochemical profile and thus suggest the potential biological marker.

The Assembly of Bacteria Living in Natural Environments Shapes Neuronal Integrity and Behavioral Outputs in Caenorhabditis elegans

Bacterivore nematodes are the most abundant animals in the biosphere, largely contributing to global biogeochemistry. Thus, the effects of environmental microbes on the nematodes' life-history traits are likely to contribute to the general health of the biosphere. Caenorhabditis elegans is an excellent model to study the behavioral and physiological outputs of microbial diets. However, the effects of complex natural bacterial assemblies have only recently been reported, as most studies have been carried out with monoxenic cultures of laboratory-reared bacteria. Here, we quantified the physiological, phenotypic, and behavioral traits of C. elegans feeding on two bacteria that were coisolated with wild nematodes from a soil sample. These bacteria were identified as a putative novel species of Stenotrophomonas named Stenotrophomonas sp. strain Iso1 and a strain of Bacillus pumilus designated Iso2. The distinctive behaviors and developmental patterns observed in animals fed with individual isolates changed when bacteria were mixed. We studied in more depth the degeneration rate of the touch circuit of C. elegans and show that B. pumilus alone is protective, while the mix with Stenotrophomonas sp. is degenerative. The analysis of the metabolite contents of each isolate and their combination identified NAD⁺ as being potentially neuroprotective. In vivo supplementation shows that NAD⁺ restores neuroprotection to the mixes and also to individual nonprotective bacteria. Our results highlight the distinctive physiological effects of bacteria resembling native diets in a multicomponent scenario rather than using single isolates on nematodes. IMPORTANCE Do behavioral choices depend on animals' microbiota? To answer this question, we studied how different bacterial assemblies impact the life-history traits of the bacterivore nematode C. elegans using isolated bacteria found in association with wild nematodes in Chilean soil. We identified the first isolate, Iso1, as a novel species of Stenotrophomonas and isolate Iso2 as Bacillus pumilus. We find that worm traits such as food choice, pharyngeal pumping, and neuroprotection, among others, are dependent on the biota composition. For example, the neurodegeneration of the touch circuit needed to sense and escape from predators in the wild decreases when nematodes are fed on B. pumilus, while its coculture with Stenotrophomonas sp. eliminates neuroprotection. Using metabolomics analysis, we identify metabolites such as NAD⁺, present in B. pumilus yet lost in the mix, as being neuroprotective and validated their protective effects using in vivo experiments.