Biology subjects

Fernandez, F.

Publications and source records attributed to Fernandez, F..

18 recordsLinked to original sources

bioRxiv2026

Orbitrap Collision Cross Section Measurements Enhance Isomer Annotations in Lipidomics

Despite advances in high-resolution mass spectrometry (HRMS), confident lipid annotation remains challenging due to the extensive chemical diversity of the lipidome and the prevalence of isomeric species. Ion mobility collision cross section (CCS) measurements provide structural information that complements HRMS; however, not all HRMS platforms can perform these measurements, necessitating a trade-off among mass resolution, accuracy, and robustness. Here, we introduce a method to infer lipid CCS values directly from liquid chromatography (LC)-Orbitrap MS experiments (OrbiCCS). We show that Orbitrap mass analyzer pressure readings, and therefore CCS values, are influenced by the LC gradient solvent composition, requiring correction using isotopically labeled internal standards injected post-column. We also show that hundreds of lipid features can be assigned OrbiCCS values in a single LC run, with average precision better than 1% and an accuracy of 1-2% relative to reference DTCCS and TIMSCCS values. This excellent CCS accuracy not only enables more reliable annotation of lipid species in complex mixtures by matching OrbiCCS values to reference databases but also accelerates lipid structural elucidation based on the unknowns position in OrbiCCS-retention time-m/z space.

biochemistry↗

bioRxiv2026

Experience shapes infants' electrophysiological responses to faces from 3 to 9 months

The types of faces that infants see impact their developing ability to engage with and individuate people from familiar and unfamiliar social groups, a phenomenon known as perceptual narrowing. However, the neural mechanisms that underlie infants processing of different faces as a function of experience remain poorly understood. To address this gap, the present study analyzes electroencephalography data collected while 3-month-olds (N=24), 6-month-olds (N=26), and 9-month-olds (N=18) viewed female and male faces of a familiar or unfamiliar social group. Infants neural responses to faces differed by group familiarity from 3 months of age, with increased responses to the more familiar face types in early components (P1, N290), and to the more unfamiliar face types in later components (P400, Nc). Face sex and group familiarity interacted to shape N290 and P400 amplitudes at 3- and 9-months. Specifically, N290 amplitudes were greater in response to female faces of a familiar group at 3 months, and to male faces of a familiar group at 9 months. In contrast, P400 amplitudes were greater in response to male faces of an unfamiliar group at 3 months old, and greatest in response to both female faces of a familiar group and to male faces of an unfamiliar group at 9 months. Source reconstruction of the Nc revealed greater reconstructed current density in response to faces of an unfamiliar social group across all ages. These findings contribute to a growing body of knowledge examining how perceptual experiences shape infants understanding of their social world.

neuroscience↗

bioRxiv2026

A Multimodal Workflow for Spatial Metabolic Neighborhood Mapping in Neural Rosette Cultures

Neural rosettes are hallmarks of the neural progenitor cell stage that is a necessary pre-condition for manufacturing central nervous system lineages. Characterization of early changes during differentiation through positional arrangement and metabolic shifts that occur in a multi-day protocol would facilitate cell culture quality monitoring and optimization of batch culture yield. We describe an analytical framework for identifying neural rosettes from confocal microscopy within a colony of differentiating stem cells and translating co-registered, cell-resolved MALDI imaging data into interpretable readouts that are compatible with cell manufacturing needs. Rather than evaluating hundreds of ion images sequentially, the pipeline converts each region of interest into a single-cell feature matrix and summarizes whole-spectrum variation using PCA, graph-based Leiden clustering, and UMAP visualization. The resultant metabolic neighborhoods provide quantification of molecular heterogeneity within colonies and - when mapped back to x-y space - form coherent spatial domains. Together, these outputs create a practical bridge between multimodal MALDI capabilities and process-relevant interpretation: neighborhoods can be compared across conditions, ranked markers can be prioritized as putative critical quality attributes, and spatial organization can be quantified without manual, feature-by-feature screening.

developmental biology↗

bioRxiv2026

GPCRs as Targets for Human Brain Modulation: A Multi-omic Atlas of Cell-Type Specific Expression

G Protein coupled receptors (GPCRs) are the largest class of clinically validated drug targets with nearly 35% of all approved therapeutic agents acting on these receptors. To further explore the potential of this class of receptors for the development of circuit-specific and mechanism-based therapeutic strategies for neurological disorders, we focused on GPCRs with no known endogenous ligand, orphan GPCRs (oGPCRs), because knowledge of their functions in the human brain remains rudimentary. Here, we utilized fluorescence activated nuclear sorting and sequencing (FANSseq) to generate deep molecular profiles of cell type specific nuclei isolated from post-mortem brains to generate an atlas of oGPCR expression across multiple regions of the human brain. We identified 22 oGPCRs that displayed selective cell-type enrichment both in RNA transcript expression and chromatin accessibility. We further validated each of these targets for cell-type specific expression in human brains and developed an open-source web atlas of all oGPCR expression in the human brain to serve as a neuro-resource for the broader scientific community. These studies reveal novel cell-type specific expression patterns of several oGPCRs, suggest potential endogenous roles for these receptors, and identify validated candidates for cell-type specific neuromodulation of the human brain. One Sentence SummaryThis study presents an atlas of orphan GPCR expression across the human brain for translational targeting.

neuroscience↗

bioRxiv2026

HLA-DRB1*15:01 drives sex- and age-dependent microglial activation and neuroimmune signaling

IntroductionThe major histocompatibility complex class II (MHC-II) pathway is central to adaptive immunity and immune tolerance, and age-related erosion of these mechanisms is increasingly recognized as a driver of chronic neuroinflammation. The HLA-DRB1*15:01 allele--the strongest genetic risk factor for multiple sclerosis in Caucasians--has been implicated in shaping pathogenic CD4 T-cell responses and broader neuroimmune vulnerability, yet how this allele modulates age- and sex-dependent neuroimmune processes within the central nervous system (CNS) remains poorly defined. MethodsWe investigated the impact of HLA-DRB1*15:01 expression using a humanized mouse model (HLA mice) and wild-type (WT) controls. Male and female mice were analyzed at 6, 9, and 15 months of age, with endocrine stratification in females. Behavioral testing, flow cytometry, immunofluorescence, and multiplex cytokine analyses were used to assess cognitive performance, glial activation and oxidative stress, astrocyte-microglia IL-3/IL-3R signaling, endothelial activation, selective immune cell accumulation at CNS borders, tissue organization, and hippocampal cytokine profiles. ResultsHLA mice developed age- and sex-dependent cognitive impairment, most pronounced in aged females. HLA-DRB1*15:01 expression promoted progressive microglial activation, characterized by increased CD14 and CD68 expression, elevated mitochondrial oxidative stress, altered astrocyte phenotypes, and enhanced IL-3/IL-3R signaling. Hippocampal axonal and myelin organization was disrupted in aged HLA mice, and this disruption was spatially associated with increased microglial presence. At CNS interfaces, HLA mice exhibited selective immune remodeling, including increased accumulation of CD4 T cells and NK1.1CD3 natural killer T (NKT) cells, particularly in females, accompanied by endothelial activation, as evidenced by elevated ICAM-1 and E-selectin expression. Hippocampal cytokine profiling revealed selective, sex-biased alterations, including increased IL-12p70 and reduced IL-10 and IL-2, without broad induction of classical inflammatory cytokines. ConclusionTogether, these findings demonstrate that HLA-DRB1*15:01 drives a coordinated, age- and sex-dependent neuroinflammatory program linking behavioral dysfunction, glial activation and oxidative stress, selective immune cell recruitment, endothelial activation, tissue remodeling, and targeted cytokine imbalance. This integrated phenotype provides mechanistic insight into how this major MS risk allele confers vulnerability to chronic neuroinflammation during aging, with heightened impact in females.

neuroscience↗

bioRxiv2025

Temporal Multi-Omic Analysis Uncovers Sex-Biased Molecular Programs Underlying Skeletal Muscle Adaptation to Endurance Training

BackgroundExercise training is known to benefit health and reduce disease risk. While skeletal muscle adaptations are fundamental to many of the health benefits of exercise training, the common and sex-specific molecular regulators that mediate these adaptations remain to be fully elucidated. MethodsTo this end, we leveraged skeletal muscle multi-omics data generated by the Molecular Transducers of Physical Activity Consortium (MoTrPAC), where 6 month-old male and female rats endurance trained for 1, 2, 4, or 8 weeks. Our objective was to identify shared and sex-specific multi-omic molecular responses to endurance training in skeletal muscle, and relate them to phenotypic adaptations. ResultsWe identified largely sexually-conserved transcriptomic and proteomic pathway enrichments in the gastrocnemius, which correlated with skeletal muscle responses from a published exercise study in humans. We uncovered sex-consistent post-translational modifications, including decreased oxidation of MYH2 and deacetylation of the {beta}-oxidation enzyme HADHA. Pathway enrichment analyses revealed sex-specific remodeling across the acetylome, redox proteome, and phosphoproteome; females decreased mitochondrial protein cysteine oxidation and increased mitochondrial cristae proteins, indicative of enhanced redox buffering and mitochondrial efficiency. Despite decreases in cysteine oxidation of key mitochondrial proteins, females displayed increases in the cysteine oxidation of proteins involved in glucose catabolism relative to males after 8 weeks of training, suggestive of sex-biased subcellular reactive oxygen species generation. Males demonstrated earlier induction of mitochondrial transcripts and predicted activation of mTOR. Although the increase in mitochondrial protein abundance was more modest in males, there was greater oxidation of mitochondrial proteins in response to training compared to females. ConclusionsThis work shows a large portion of the adaptive response to endurance training in skeletal muscle is shared between females and males, while there are distinct and nuanced sex-specific adaptations that are evident, particularly at the level of post-translational regulation.

physiology↗

bioRxiv2025

Integrative proteomics and metabolomics map reveals key sectors of defense metabolism in ginger against Pythium myriotylum

Ginger (Zingiber officinale) cultivation is severely threatened by rhizome rot caused by Pythium myriotylum. Hitherto, detail molecular machineries and metabolic pathways of defense against P. myriotylum in edible ginger are elusive. To elucidate the defense mechanisms, we employed integrative quantitative proteomics (TMT labelling) and high resolution untargeted metabolomics to investigate temporal defense responses of ginger during infection. Proteomics analysis revealed enrichment of cellular detoxification and secondary metabolism pathways indicating co-activation of oxidative stress management and its mediated defense metabolite biosynthesis. Key phenylpropanoid enzymes (PAL, C4H, CAD) and LOX, a regulator of jasmonic acid (JA) biosynthesis, were significantly up-regulated, correlating JA signaling with secondary metabolic defenses. Metabolomics profiling confirmed accumulation of phenylpropanoids, flavonoids, and terpenoids, including known antimicrobial metabolites such as gingerol, shogaol, curcumin, and gingerdione, alongside expression of their key regulatory enzyme was also induced. Notably, machine learning identified the monoterpenoid TGA as the top defense-associated metabolite. Functional assays demonstrated strong anti-P. myriotylum activity of TGA, which inhibited mycelial growth and suppressed expression of key pathogenicity-related genes (NIP1, GHs, cellulase). These findings highlight coordinated activation of detoxification and secondary metabolic pathways in ginger defense and establish TGA as a promising bio-control agent against P. myriotylum.

plant biology↗

bioRxiv2025

Endurance exercise drives temporal and sexual dimorphic multi-omic adaptations in liver metabolism-Findings from MoTrPAC.

The mechanisms by which exercise modulate liver metabolism, a central regulator of systemic metabolism, are poorly understood. Leveraging data from MoTrPAC, we analyzed liver adaptations across 1, 2, 4, and 8 weeks of exercise in male and female rats using multi-omic approaches. Female livers displayed a progressive increase in oxidative phosphorylation (OXPHOS) complexes (at the protein level), while male livers showed an increase in acetylation of OXPHOS, TCA cycle, and fatty acid oxidation enzymes. Exercise also enhanced liver cholesterol and bile acid synthesis, reducing liver lipid metabolites in males after 8 weeks of exercise. Male rats had higher fecal cholesterol and cholic acid levels, indicating a sex-specific mechanism of lipid excretion with exercise. Moreover, 8 weeks of training reduced markers related to hepatic stellate cell activation and fibrosis in both sexes. This study highlights the sexual dimorphic and temporal molecular signatures by which exercise modulates liver metabolism to provide hepatoprotective effects.

physiology↗

bioRxiv2025

Sexually distinct multi omic responses to progressive endurance exercise training in the rat lung. Findings from MoTrPAC

Despite the lungs being essential for ventilation and aerobic exercise capacity, conventionally the lungs are not thought to adapt to exercise training. Endurance exercise is key to pulmonary rehabilitation programs, which also displays sex-specific differences in therapeutic efficacy. Given the molecular underpinnings of sex-specific lung adaptations to endurance exercise are uncharacterized, we used a multi-omics approach to study sex differences in the lungs of 6-month-old Fischer 344 rats in response to an 8 week progressive endurance treadmill training protocol. This was accomplished by reannotating publicly accessible data from the Molecular Transducers of Physical Activity Consortium (MoTrPAC) and integrating newly-analyzed acetylome data to assess multi-omic sex differences in sedentary and progressively trained states. Female rats displayed enrichment in immune-related features and pathways at the transcriptome and proteome level that were maintained with training. Conversely, in the male rat lung there was an overall decrease in immune pathways following 8 weeks of training. Sexually conserved responses to training included increased enrichment in transcriptomic pathways related to type I alveoli and proteomic pathways related to cilia, and decreased mitochondrial protein acetylation. In both sexes, features known to be enriched in lung diseases were attenuated with training. Together our findings provide novel insight into sex specific responses to endurance exercise training in the rat lung and may offer translational insight into sex-specific differences in lung disease pathogenesis and treatment.

physiology↗

bioRxiv2025

A systematic review of climate-change driven range shifts in mosquito vectors

As global temperatures rise, concerns about shifting mosquito ranges--and accompanying changes in the transmission of malaria, dengue, and other diseases--are mounting. However, systematic evidence for climate-driven changes in mosquito ranges remains limited. We conducted a systematic review of studies documenting expansions or contractions in medically important mosquito species. In total, 178 studies on six continents identified range expansions in 118 mosquito species. While over a third of these studies cited warming as a driver, fewer than 10% performed statistical tests of the role of climate. Instead, most expansions were linked to human-aided dispersal (e.g., trade, travel), land-use changes, and urbanization. Although several studies reported poleward or upward expansions consistent with climate warming, none demonstrated warm-edge contractions driven by rising temperatures, which are theoretically predicted in some settings. Rather than expanding into newly suitable areas, many expansions appear to be filling preexisting thermally suitable habitats. Our findings highlight the need for long-term mosquito monitoring, rigorous climate-attribution methods, and better documentation of confounding factors like land-use change and vector control efforts to disentangle climate-driven changes from other anthropogenic factors.

ecology↗

bioRxiv2024

Pangenome analysis of Clostridium scindens: a collection of diverse bile acid and steroid metabolizing commensal gut bacterial strains

Clostridium scindens is a commensal gut bacterium capable of forming the secondary bile acids deoxycholic acid and lithocholic acid from the primary bile acids cholic acid and chenodeoxycholic acid, respectively, as well as converting glucocorticoids to androgens. Historically, only two strains, C. scindens ATCC 35704 and C. scindens VPI 12708, have been characterized in vitro and in vivo to any significant extent. The formation of secondary bile acids is important in maintaining normal gastrointestinal function, in regulating the structure of the gut microbiome, in the etiology of such diseases such as cancers of the GI tract, and in the prevention of Clostridium difficile infection. We therefore wanted to determine the pangenome of 34 cultured strains of C. scindens and a set of 200 metagenome-assembled genomes (MAGs) to understand the variability among strains. The results indicate that the 34 strains of C. scindens have an open pangenome with 12,720 orthologous gene groups, and a core genome with 1,630 gene families, in addition to 7,051 and 4,039 gene families in the accessory and unique (i.e., strain-exclusive) genomes, respectively. The core genome contains 39% of the proteins with predicted metabolic function, and, in the unique genome, the function of storage and processing of information prevails, with 34% of the proteins being in that category. The pangenome profile including the MAGs also proved to be open. The presence of bile acid inducible (bai) and steroid-17,20-desmolase (des) genes was identified among groups of strains. The analysis reveals that C. scindens strains are distributed into two clades, indicating the possible onset of C. scindens separation into two species, confirmed by gene content, phylogenomic, and average nucleotide identity (ANI) analyses. This study provides insight into the structure and function of the C. scindens pangenome, offering a genetic foundation of significance for many aspects of research on the intestinal microbiota and bile acid metabolism.

microbiology↗

bioRxiv2023

The unknown lipids project: harmonized methods improve compound identification and data reproducibility in an inter-laboratory untargeted lipidomics study

Untargeted lipidomics allows analysis of a broader range of lipids than targeted methods and permits discovery of unknown compounds. Previous ring trials have evaluated the reproducibility of targeted lipidomics methods, but inter-laboratory comparison of compound identification and unknown feature detection in untargeted lipidomics has not been attempted. To address this gap, five laboratories analyzed a set of mammalian tissue and biofluid reference samples using both their own untargeted lipidomics procedures and a common chromatographic and data analysis method. While both methods yielded informative data, the common method improved chromatographic reproducibility and resulted in detection of more shared features between labs. Spectral search against the LipidBlast in silico library enabled identification of over 2,000 unique lipids. Further examination of LC-MS/MS and ion mobility data, aided by hybrid search and spectral networking analysis, revealed spectral and chromatographic patterns useful for classification of unknown features, a subset of which were highly reproducible between labs. Overall, our method offers enhanced compound identification performance compared to targeted lipidomics, demonstrates the potential of harmonized methods to improve inter-site reproducibility for quantitation and feature alignment, and can serve as a reference to aid future annotation of untargeted lipidomics data.

systems biology↗

bioRxiv2023

Native Triboelectric Nanogenerator Ion Mobility-Mass Spectrometry of Egg Proteins Relevant to Objects of Cultural Heritage at Picoliter and Nanomolar Quantities.

Native mass spectrometry (nMS) has found widespread success in measuring native-like protein structures in the gas-phase and, when combined with ion mobility (IM), is capable of measuring protein collision cross sections (CCS) and stabilities. These methods are well validated, but often rely on samples that are abundantly available through repeated recombinant protein expression. For ultra-precious and irreplaceable samples from cultural heritage objects, protein content can be far below the micromolar and microliter levels required for robust protein experiments, a major hurdle in characterizing protein higher order structure and degradation mechanisms. Combining triboelectric nanogenerators (TENG) and IM-MS enables measuring protein size and stability rapidly from ultra-small sample quantities. Here, TENG IM-MS is implemented with standard and sub-micron emitters to characterize proteins relevant to cultural heritage objects, and demonstrates native structures can be obtained even at nanomolar concentrations and picoliter quantities.

biophysics↗

bioRxiv2022

Ion Mobility for Unknown Metabolite Identification: Hope or Hype?

Ion mobility (IM) spectrometry provides semi-orthogonal data to mass spectrometry (MS), showing promise for identifying unknown metabolites in complex non-targeted metabolomics datasets. While current literature has showcased IM-MS for identifying unknowns under near ideal circumstances, less work has been conducted to evaluate the performance of this approach in metabolomics studies involving highly complex samples with difficult matrices. Here, we present a workflow incorporating de novo molecular formula annotation and MS/MS structure elucidation using SIRIUS 4 with experimental IM collision cross-section (CCS) measurements and machine learning CCS predictions to identify differential unknown metabolites in mutant strains of Caenorhabditis elegans. For many of those ion features this workflow enabled the successful filtering of candidate structures generated by in silico MS/MS predictions, though in some cases annotations were challenged by significant hurdles in instrumentation performance and data analysis. While for 37% of differential features we were able to successfully collect both MS/MS and CCS data, fewer than half of these features benefited from a reduction in the number of possible candidate structures using CCS filtering due to poor matching of the machine learning training sets, limited accuracy of experimental and predicted CCS values, and lack of candidate structures resulting from the MS/MS data. When using a CCS error cutoff of {+/-}3%, an average 28% of candidate structures could be successfully filtered. Herein, we identify and describe the bottlenecks and limitations associated with the identification of unknowns in non-targeted metabolomics using IM-MS to focus and provide insight on areas requiring further improvement.

biochemistry↗

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↗