Biology subjects

Fernandez, F.

Publications and source records attributed to Fernandez, F..

4 recordsLinked to original sources

bioRxiv2022

Evolution of SARS-CoV-2 during the first year of the COVID-19 pandemic in Northwestern Argentina

Studies about the evolution of SARS-CoV-2 lineages in different backgrounds such as naive populations, are still scarce, especially from South America. The aim of this work was to study the introduction and diversification pattern of SARS-CoV-2 during the first year of the COVID-19 pandemic in the Northwestern Argentina (NWA) region and to analyze the evolutionary dynamics of the main lineages found. In this study, we analyzed a total of 260 SARS-CoV-2 whole-genome sequences from Argentina, belonging to the Provinces of Jujuy, Salta and Tucuman, from March 31st, 2020, to May 22nd, 2021, which covered the full first wave and the early second wave of the COVID-19 pandemic in Argentina. In the first wave, eight lineages were identified: B.1.499 (76.9%), followed by N.5 (10.2%), B.1.1.274 (3.7%), B.1.1.348 (3.7%), B.1 (2.8%), B.1.600 (0.9%), B.1.1.33 (0.9%) and N.3 (0.9%). During the early second wave, the first-wave lineages were displaced by the introduction of variants of concern (VOC) (Alpha, Gamma), or variants of interest (VOI) (Lambda, Zeta, Epsilon) and other lineages with more limited distribution. Phylodynamic analyses of the B.1.499 and N.5, the two most prevalent lineages in NWA, revealed that the substitution rate of lineage N.5 (7.9 x 10-4 substitutions per site per year, s/s/y) was a [~]40% faster than that of lineage B.1.499 (5.9 x 10-4 s/s/y), although both are in the same order of magnitude than other non-VOC lineages. No mutations associated with a biological characteristic of importance were observed as signatures markers of the phylogenetic groups established in Northwestern Argentina, however, single sequences in non-VOC lineages did present mutations of biological importance or associated with VOCs as sporadic events, showing that many of these mutations could emerge from circulation in the general population. This study contributed to the knowledge about the evolution of SARS-CoV-2 in a pre-vaccination and without post-exposure immunization period.

bioinformatics↗

bioRxiv2022

Integration of imaging modalities with lipidomic characterization to investigate MSCs potency metrics

Mesenchymal stem cells (MSCs) are widely used as therapeutics targets for numerous autoimmune diseases. However, MSC therapies have had limited success so far in clinical trials, mainly being heterogenous population it is difficult to determine MSCs efficiencies. It is critical to understand internal signaling of individual MSCs population that directly affect the cell phenotype. Lipid signaling is closely associated with cell shape so, a holistic approach to understand how changes in lipid metabolites trickles all the way to single cell phenotype could reveal deeper understanding of MSCs functional regulation. So, we aim to evaluate lipid metabolic profiles of single cell MSCs with known variability in immune regulation and explore the phenotypic changes that occur because of differences in lipid signaling. We use longitudinal label free phase imaging strategies to obtain cell phenotypic features which are directly correlated with single cell lipid metabolome obtained using advanced MALDI-MSI technique. Correlation maps indicate associations between lipid signaling and phenotypic changes in MSCs. Moreover, a novel machine learning clustering approach detects the heterogeneity in the MSCs subpopulation then methodically see how each heterogenous population is being impacted by the changes in lipid profiles which could be linked to the functional behaviors of the cell.

cell biology↗

bioRxiv2021

Uncovering Xenobiotics in the Dark Metabolome using Ion Mobility Spectrometry, Mass Defect Analysis and Machine Learning

The identification of xenobiotics in nontargeted metabolomic analyses is a vital step in understanding human exposure. Xenobiotic metabolism, excretion, and co-existence with other endogenous molecules however greatly complicate nontargeted studies. While mass spectrometry (MS)-based platforms are commonly used in metabolomic measurements, deconvoluting endogenous metabolites and xenobiotics is often challenged by the lack of xenobiotic parent and metabolite standards as well as the numerous isomers possible for each small molecule m/z feature. Here, we evaluate the use of ion mobility spectrometry coupled with MS (IMS-MS) and mass defect filtering in a xenobiotic structural annotation workflow to reduce large metabolomic feature lists and uncover potential xenobiotic classes and species detected in the metabolomic studies. To evaluate the workflow, xenobiotics having known high toxicities including per- and polyfluoroalkyl substances (PFAS), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) were examined. Initially, to address the lack of available IMS collision cross section (CCS) values for per- and polyfluoroalkyl substances (PFAS), 88 PFAS standards were evaluated with IMS-MS to both develop a targeted PFAS CCS library and for use in machine learning predictions. The CCS values for biomolecules and xenobiotics were then plotted versus m/z, clearly distinguishing the biomolecules and halogenated xenobiotics. The xenobiotic structural annotation workflow was then used to annotate potential PFAS features in NIST human serum. The workflow reduced the 2,423 detected LC-IMS-MS features to 80 possible PFAS with 17 confidently identified through targeted analyses and 48 additional features correlating with possible CompTox entries.

biochemistry↗

bioRxiv2021

The Circadian Phase Response Curve to Light: Conservation across Seasons and Anchorage to Sunset

Phototherapy outcomes are dependent on the precision by which the magnitude and direction of lights circadian phase-shifting effects can be predicted. Such predictions are largely based on photic phase-response curves (PRCs) generated from animals housed under seasonally agnostic equatorial photoperiods with alternating 12-hour segments of light and darkness. Most of the human population, however, lives at northerly latitudes (20-50{degrees} N of the Equator) where seasonal variations in the light-dark schedule are pronounced. Here, we address this disconnect by constructing the first high-resolution seasonal atlas for light-induced circadian phase-resetting. Testing the light responses of nearly 4,000 Drosophila at 120 timepoints across 5 seasonally relevant photoperiods (i.e., LD 8:16, 10:14, 12:12, 14:10, and 16:8; 24 hourly intervals surveyed in each), we determined that many aspects of the circadian PRC waveform are conserved with increasing daylength. Surprisingly though, irrespective of LD schedule, the start of the PRCs always remained anchored to the timing of subjective sunset, creating a differential overlap of the advance zone with the morning hours after subjective sunrise that was maximized under summer photoperiods and minimized under winter photoperiods. These data suggest that circadian photosensitivity is effectively extinguished by the early winter morning and out of optimal phase alignment with the wake schedules of many individuals (which revolve around the timing of sunrise regardless of season). They raise the possibility that phototherapy protocols for conditions such as seasonal depression might be improved with programmed light exposure during the final hours of sleep.

animal behavior and cognition↗