Biology subjects

Moore, R. J.

Publications and source records attributed to Moore, R. J..

18 recordsLinked to original sources

bioRxiv2025

Sex- and estrous-specific effects of paradoxical (REM) sleep deprivation: Neurobehavioral changes and hippocampal neuroinflammation

With millions suffering from sleep disorders in todays modern society, a better understanding of sleep disruption related cognitive outcomes is urgently needed. To that end, a preclinical investigation into the effects of sleep deprivation (SD) on neurobehavioral outcomes and associated hippocampal neuroinflammation was conducted in male and female rats. Due to epidemiological identification of sex differences in many aspects of sleep disorders, sex and estrous cycle stage factors were investigated. Sprague-Dawley rats underwent 120 h of paradoxical SD using a modified multiple platform flower pot method. At 96 h SD, animals were trained on neurobehavioral Novel Object Recognition (NOR) and Passive-Avoidance Task (PAT) paradigms. Prior to NOR/PAT testing at 120 h SD, Elevated Zero Maze (EZM) assessed anxiolytic-like behavior. SD impaired PAT performance among males and females. Anxiolytic-like and locomotor behavior was increased and NOR performance impaired in males after SD. Estrous cycle stage determined by cytological analysis of daily wet smears found females to exhibit estrous-specific differences across all neurobehavioral paradigms, with increased anxiolytic-like behavior and impaired PAT performance only among SD females in estrus. Immunohistochemical analysis of the hippocampus after 120 h SD found microgliosis, but not astrogliosis, in the CA1/2 of males and females in estrus. This study contributes to a better understanding of sex- and estrous-specific difference in sleep disruption induced neurobehavioral outcomes and associated hippocampal inflammation. Further research is needed to investigate the molecular mechanisms underlying the interaction between estrous cycle, hippocampal microgliosis, and sleep disruption cognitive outcomes.

animal behavior and cognition↗

bioRxiv2025

Discovery of non-opioid receptor protein targets of fentanyl across tissues from animal models and humans using photoaffinity probes

Synthetic opioids such as fentanyl and related analogs have been widely used for pain management. However, their negative side effects, including respiratory depression and high potential for addiction, underscore the need for a deeper understanding of fentanyls interactions with proteins throughout the human body. Fentanyl analogs bind and activate opioid receptors in the central and peripheral nervous systems, triggering numerous downstream signaling pathways. Increasingly, fentanyl has been shown to interact with non-opioid receptors, and elucidation of these non-canonical fentanyl-protein interactions may provide insights into the mechanisms contributing to fentanyls adverse effects and illuminate novel countermeasure strategies. To identify proteins in mammalian tissues that may interact with fentanyl, we designed and synthesized three affinity-based probes (AfBPs) that include the fentanyl core and feature a diazirine photoaffinity group and alkyne handle for click chemistry at different positions. Molecular docking simulations predicted that these AfBPs bind the mu opioid receptor similarly to fentanyl. Affinity-based protein profiling using the FA-T1 probe in vitro in tissues from six animal species identified histamine N-methyltransferase (HNMT), endophilin-B1 (SH3GLB1), fructosamine-3-kinase (FN3K), cutA divalent cation tolerance analog (CUTA), and monoamine oxidase B (MAOB) among the top proteins that bind fentanyl in multiple species and tissue types. Molecular docking of fentanyl and remifentanil with these protein structures identified putative binding sites. The interaction of fentanyl with specific proteins was empirically assessed through protein structural analyses. These findings highlight potential fentanyl-protein interactions that may contribute to the acute and long-term impacts of fentanyl exposures.

pharmacology and toxicology↗

bioRxiv2024

Increased Inflammation as well as Decreased Endoplasmic Reticulum Stress and Translation Differentiate Pancreatic Islets of Pre-symptomatic Stage 1 Type 1 Diabetes and Non-diabetic Cases

Aims/hypothesisProgression to type 1 diabetes (T1D) is associated with genetic factors, the presence of autoantibodies, and a decline in {beta} cell insulin secretion in response to glucose. Very little is known regarding the molecular changes that occur in human insulin-secreting {beta}-cells prior to the onset of T1D. Herein, we applied an unbiased proteomics approach to identify changes in proteins and potential mechanisms of islet dysfunction in islet autoantibody-positive organ donors with pre-symptomatic stage 1 T1D (HbA1c [≤] 6). We aimed to identify pathways in islets that are indicative of {beta}-cell dysfunction. MethodsMultiple islet sections were collected through laser microdissection of frozen pancreatic tissues of organ donors positive for islet autoantibodies (AAb+, n=5), compared to age/sex-matched nondiabetic controls (ND, n=5) obtained from the Network for Pancreatic Organ donors with Diabetes (nPOD). Islet sections were subjected to mass spectrometry-based proteomics and analyzed with label-free quantification followed by pathway and functional annotations. ResultsAnalyses resulted in [~]4,500 proteins identified with low false discovery rate (FDR) <1%, with 2,165 proteins reliably quantified in every islet sample. We observed large inter-donor variations that presented a challenge for statistical analysis of proteome changes between donor groups. We therefore focused on the three multiple AAb+ cases (mAAb+) with high genetic risk and their three matched controls for a final statistical analysis. Approximately 10% of the proteins (n=202) were significantly different between mAAb+ cases versus ND. The significant alterations clustered around major functions for upregulation in the immune response and glycolysis, and downregulation in endoplasmic reticulum (ER) stress response as well as protein translation and synthesis. The observed proteome changes were further supported by several independent published datasets, including proteomics dataset from in vitro proinflammatory cytokine-treated human islets and single cell RNA-seq data sets from AAb+ cases. Conclusion/interpretationIn-situ human islet proteome alterations at the stage 1 of AAb+ T1D centered around several major functional categories, including an expected increase in immune response genes (elevated antigen presentation / HLA), with decreases in protein synthesis and ER stress response, as well as compensatory metabolic response. The dataset serves as a proteomics resource for future studies on {beta} cell changes during T1D progression and pathogenesis.

pathology↗

bioRxiv2024

Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of [~]3500 proteins at a spatial resolution of 50 {micro}m and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.

systems biology↗

bioRxiv2024

Spatial top-down proteomics for the functional characterization of human kidney

BackgroundThe Human Proteome Project has credibly detected nearly 93% of the roughly 20,000 proteins which are predicted by the human genome. However, the proteome is enigmatic, where alterations in amino acid sequences from polymorphisms and alternative splicing, errors in translation, and post-translational modifications result in a proteome depth estimated at several million unique proteoforms. Recently mass spectrometry has been demonstrated in several landmark efforts mapping the human proteoform landscape in bulk analyses. Herein, we developed an integrated workflow for characterizing proteoforms from human tissue in a spatially resolved manner by coupling laser capture microdissection, nanoliter-scale sample preparation, and mass spectrometry imaging. ResultsUsing healthy human kidney sections as the case study, we focused our analyses on the major functional tissue units including glomeruli, tubules, and medullary rays. After laser capture microdissection, these isolated functional tissue units were processed with microPOTS (microdroplet processing in one-pot for trace samples) for sensitive top-down proteomics measurement. This provided a quantitative database of 616 proteoforms that was further leveraged as a library for mass spectrometry imaging with near-cellular spatial resolution over the entire section. Notably, several mitochondrial proteoforms were found to be differentially abundant between glomeruli and convoluted tubules, and further spatial contextualization was provided by mass spectrometry imaging confirming unique differences identified by microPOTS, and further expanding the field-of-view for unique distributions such as enhanced abundance of a truncated form (1-74) of ubiquitin within cortical regions. ConclusionsWe developed an integrated workflow to directly identify proteoforms and reveal their spatial distributions. Where of the 20 differentially abundant proteoforms identified as discriminate between tubules and glomeruli by microPOTS, the vast majority of tubular proteoforms were of mitochondrial origin (8 of 10) where discriminate proteoforms in glomeruli were primarily hemoglobin subunits (9 of 10). These trends were also identified within ion images demonstrating spatially resolved characterization of proteoforms that has the potential to reshape discovery-based proteomics because the proteoforms are the ultimate effector of cellular functions. Applications of this technology have the potential to unravel etiology and pathophysiology of disease states, informing on biologically active proteoforms, which remodel the proteomic landscape in chronic and acute disorders.

biochemistry↗

bioRxiv2022

A Deep Redox Proteome Profiling Workflow and Its Application to Skeletal Muscle of a Duchene Muscular Dystrophy Model

Perturbation to the redox state accompanies many diseases and its effects are viewed through oxidation of biomolecules, including proteins, lipids, and nucleic acids. The thiol groups of protein cysteine residues undergo an array of redox post-translational modifications (PTMs) that are important for regulation of protein and pathway function. To better understand what proteins are redox regulated following a perturbation, it is important to be able to comprehensively profile protein thiol oxidation at the proteome level. Herein, we report a deep redox proteome profiling workflow and demonstrate its application in measuring the changes in thiol oxidation along with global protein expression in skeletal muscle from mdx mice, a model of Duchenne Muscular Dystrophy (DMD). In depth coverage of the thiol proteome was achieved with >18,000 Cys sites from 5608 proteins in muscle being quantified. Compared to the control group, mdx mice exhibit markedly increased thiol oxidation, where ~2% shift in the median oxidation occupancy was observed. Pathway analysis for the redox data revealed that coagulation system and immune-related pathways were among the most susceptible to increased thiol oxidation in mdx mice, whereas protein abundance changes were more enriched in pathways associated with bioenergetics. This study illustrates the importance of deep redox profiling in gaining a greater insight into oxidative stress regulation and pathways/processes being perturbed in an oxidizing environment. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=190 SRC="FIGDIR/small/504013v1_ufig1.gif" ALT="Figure 1"> View larger version (74K): org.highwire.dtl.DTLVardef@1917f1org.highwire.dtl.DTLVardef@1730cd0org.highwire.dtl.DTLVardef@4e4820org.highwire.dtl.DTLVardef@1615f4c_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIDeep redox profiling workflow results in stoichiometric quantification of thiol oxidation for > 18,000 Cys sites in muscle C_LIO_LIThiol redox changes were much more pronounced than protein abundance changes for the overlapping set of proteins C_LIO_LIRedox changes are most significant in coagulation and immune response pathways while abundance changes on bioenergetics pathways C_LI

biochemistry↗

bioRxiv2022

Parallel measurement of transcriptomes and proteomes from same single cells using nanodroplet splitting

Single-cell multiomics provides comprehensive insights into gene regulatory networks, cellular diversity, and temporal dynamics. Here, we introduce nanoSPLITS (nanodroplet SPlitting for Linked-multimodal Investigations of Trace Samples), an integrated platform that enables global profiling of the transcriptome and proteome from same single cells using RNA sequencing and mass spectrometry-based proteomics, respectively. Benchmarking of nanoSPLITS demonstrated excellent measurement precision, with deep proteomic and transcriptomic profiling of single-cells. We applied nanoSPLITS to cyclin-dependent kinase 1 inhibited cells and found phospho-signaling events could be quantified alongside global protein and mRNA measurements, providing new insights into cell cycle regulation. We also extended nanoSPLITS to single-cells isolated from human pancreatic islets, introducing an efficient approach for facile identification of unknown cell types, and detecting their protein markers by mapping transcriptomic data to existing large-scale single-cell RNA sequencing reference databases. Herein, we establish nanoSPLITS as a new multiomic technology incorporating global proteomics and anticipate the approach will be critical to furthering our understanding of single-cell systems.

systems biology↗

bioRxiv2022

A streamlined tandem tip-based workflow for sensitive nanoscale phosphoproteomics

Effective phosphoproteome of nanoscale sample analysis remains a daunting task, primarily due to significant sample loss associated with non-specific surface adsorption during enrichment of low stoichiometric phosphopeptide. We developed a novel tandem tip phosphoproteomics sample preparation method that is capable of sample cleanup and enrichment without additional sample transfer, and its integration with our recently developed SOP (Surfactant-assisted One-Pot sample preparation) and iBASIL (improved Boosting to Amplify Signal with Isobaric Labeling) approaches provides a streamlined workflow enabling sensitive, high-throughput nanoscale phosphoproteome measurements. This approach significantly reduces both sample loss and processing time, allowing the identification of >3,000 (>9,500) phosphopeptides from 1 (10) {micro}g of cell lysate using the label-free method without a spectral library. It also enabled precise quantification of [~]600 phosphopeptides from 100 cells sorted by FACS (single-cell level input for the enriched phosphopeptides) and [~]700 phosphopeptides from human spleen tissue voxels with a spatial resolution of 200 {micro}m (equivalent to [~]100 cells) in a high-throughput manner. The new workflow opens avenues for phosphoproteome profiling of mass-limited samples at the low nanogram level.

biochemistry↗

bioRxiv2022

CD81 partners with CD44 in promoting exosome biogenesis, tumor cluster formation, and lung metastasis in triple negative breast cancer

Tumor-initiating cells with reprogramming plasticity are thought to be essential for cancer development and metastatic regeneration in many cancers; however, the molecular mechanisms are not fully understood. This study reports that CD81, a tetraspanin protein marker of small extracellular vesicles (exosomes), functions as a binding partner of CD44 and facilitates self-renewal of tumor initiating cells. Using machine learning-assisted protein structure modeling, co-immunoprecipitation, and mutagenesis approaches, we further demonstrate that CD81 interacts with CD44 on the cellular membrane through their extracellular regions. In-depth global and phosphoproteomic analyses of clustering tumor cells unveils endocytosis-related signature pathways of proteins and phosphorylation patterns regulated by CD81 and CD44 specifically or shared between two. Notably, CRISPR Cas9-mediated depletion of either CD44 or CD81 results in loss of both proteins in cancer cell-secreted exosomes, a state which abolishes exosome-induced self-renewal of recipient cells for mammosphere formation. CD81 is expressed in >80% of human circulating tumor cells (CTCs) and specifically enriched in clustered CTCs along with CD44 isolated from breast cancer patients. Mimicking the phenotypes of CD44 deficiency, loss of CD81 also inhibits tumor cluster aggregation, tumorigenesis, and lung metastasis of triple negative breast cancer (TNBC), supporting the clinical significance of CD81 in association with patient outcomes. Our study highlights the novel role of CD81 and its partnership with CD44 in cancer exosomes, self-renewal, CTC clustering, and metastasis initiation of TNBC.

cancer biology↗

bioRxiv2021

High-throughput and high-efficiency sample preparation for single-cell proteomics using a nested nanowell chip

Global quantification of protein abundances in single cells would provide more direct information on cellular function phenotypes and complement transcriptomics measurements. However, single-cell proteomics (scProteomics) is still immature and confronts technical challenges, including limited proteome coverage, poor reproducibility, as well as low throughput. Here we describe a nested nanoPOTS (N2) chip to dramatically improve protein recovery, operation robustness, and processing throughput for isobaric-labeling-based scProteomics workflow. The N2 chip allows reducing cell digestion volume to <30 nL and increasing processing capacity to > 240 single cells in one microchip. In the analysis of [~]100 individual cells from three different cell lines, we demonstrate the N2 chip-based scProteomics platform can robustly quantify [~]1500 proteins and reveal functional differences. Our analysis also reveals low protein abundance variations (median CVs < 16.3%), highlighting the utility of such measurements, and also suggesting the single-cell proteome is highly stable for the cells cultured under identical conditions.

systems biology↗

bioRxiv2021

Robust, sensitive, and quantitative single-cell proteomics based on ion mobility filtering

Unbiased single-cell proteomics (scProteomics) promises to advance our understanding of cell functions within complex biological systems. However, a major challenge for current methods is their ability to identify and provide accurate quantitative information for low abundance proteins. Herein, we describe an ion mobility-enhanced mass spectrometry acquisition and peptide identification method, TIFF (Transferring Identification based on FAIMS Filtering), designed to improve the sensitivity and accuracy of label-free scProteomics. TIFF significantly extends the ion accumulation times for peptide ions by filtering out singly charged background ions. The peptide identities are then assigned by a 3-dimensional MS1 feature matching approach (retention time, accurate mass, and FAIMS compensation voltage). The TIFF method enabled unbiased proteome analysis to a depth of >1,700 proteins in single HeLa cells with >1,100 proteins consistently quantified. As a demonstration, we applied the TIFF method to obtain temporal proteome profiles of >150 single murine macrophage cells during a lipopolysaccharide stimulation experiment and identified time-dependent proteome profiles.

systems biology↗

bioRxiv2021

Enhancing top-down proteomics of brain tissue with FAIMS

Proteomic investigations of Alzheimers and Parkinsons disease have provided valuable insights into neurodegenerative disorders. Thus far, these investigations have largely been restricted to bottom-up approaches, hindering the degree to which one can characterize a proteins "intact" state. Top-down proteomics (TDP) overcomes this limitation, however it is typically limited to observing only the most abundant proteoforms and of a relatively small size. Therefore, offline fractionation techniques are commonly used to reduce sample complexity, limiting throughput. A higher throughput alternative is online fractionation, such as gas phase high-field asymmetric waveform ion mobility spectrometry (FAIMS). Utilizing a high complexity sample derived from Alzheimers disease brain tissue, we describe how the addition of FAIMS to TDP can robustly improve the depth of proteome coverage. For example, implementation of FAIMS at -50 compensation voltage (CV) more than doubled the mean number of non-redundant proteoforms observed (1,833 {+/-} 17, n = 3), compared to without (754 {+/-} 35 proteoforms). We also found FAIMS can influence the transmission of proteoforms and their charge envelopes based on their size. Importantly, FAIMS enabled the identification of intact amyloid beta (A{beta}) proteoforms, including the aggregation-prone A{beta}1-42 variant which is strongly linked to Alzheimers disease.

biochemistry↗

bioRxiv2020

Cloning and functional expression of a food-grade circular bacteriocin, plantacyclin B21AG, in probiotic Lactobacillus plantarum WCFS1

There is an increasing consumer demand for minimally processed, preservative free and microbiologically safe food. These factors, combined with risks of antibiotic resistance, have led to interest in bacteriocins produced by lactic acid bacteria (LAB) as natural food preservatives and as protein therapeutics. We previously reported the discovery of plantacyclin B21AG, a novel circular bacteriocin produced by Lactobacillus plantarum B21. Here, we describe the cloning and functional expression of the bacteriocin gene cluster in the probiotic Lactobacillus plantarum WCFS1. Genome sequencing demonstrated that the bacteriocin is encoded on a 20 kb native plasmid, designated as pB21AG01. Seven open reading frames (ORFs) putatively involved in bacteriocin production, secretion and immunity were cloned into an E. coli/Lactobacillus shuttle vector, pTRKH2. The resulting plasmid, pCycB21, was transformed into L. plantarum WCFS1. The cell free supernatants (CFS) of both B21 and WCFS1 (pCycB21) showed an antimicrobial activity of 800 AU/mL when tested against the WCFS1 (pTRKH2) indicator strain, indicating functional expression of plantacyclin B21AG. Real-time PCR analysis revealed that the relative copy number of pB21AG01 was 7.60 {+/-} 0.79 in L. plantarum B21 whilst pCycB21 and pTRKH2 was 0.51 {+/-} 0.05 and 25.19 {+/-} 2.68 copies, respectively in WCFS1. This indicates that the bacteriocin gene cluster is located on a highly stable, low copy number plasmid pB21AG01 in L. plantarum B21. Inclusion of the native promoter for the bacteriocin operon from pB21AG01 may result in similar inhibitory zones observed in both wild type and recombinant hosts despite the low copy number of pCycB21.

microbiology↗

bioRxiv2019

Oregano powder reduces Streptococcus and increases SCFA concentration in a mixed bacterial culture assay of chicken.

Food borne illnesses have a world-wide economic impact and industries are continuously developing technologies to reduce the spread of disease caused by microorganisms. Antimicrobial growth promoters (AGPs) have been used to decrease microbiological infections in animals and their potential transfer to humans. In recent years there has been a global trend to remove AGPs from animal feed in an attempt to reduce the spread of antimicrobial resistant genes into the human population. Phytobiotics, such as oregano powder, are one of the potential replacements for AGPs due to their well-established antimicrobial components. 16S rRNA gene amplicons were used to determine the effect of oregano powder (1% w/v) on the microbiota of mixed bacterial cell cultures, which were obtained from the ceca of traditionally grown meat chickens (broilers). Oregano powder had a mild effect on the microbial cell cultures increasing Enterococcus faecium, rearranging ratios of members in the genus Lactobacillus and significantly reducing the genus Streptococcus (p=1.6e-3). Beneficial short chain fatty acids (SCFA), acetic and butyric acid, were also significantly increased in oregano powder supplemented cultures. These results suggest that oregano powder at a concentration of 1 % (w/v) may have beneficial influences on mixed microbial communities and SCFA production.

microbiology↗

bioRxiv2019

MetFish: A Metabolomics Platform for Studying Microbial Communities in Chemically Extreme Environments

Metabolites have essential roles in microbial communities, including as mediators of nutrient and energy exchange, cell-to-cell communication, and antibiosis. However, detecting and quantifying metabolites and other chemicals in samples having extremes in salt or mineral content using liquid chromatography-mass spectrometry (LC-MS)-based methods remains a significant challenge. Here we report a facile method based on in situ chemical derivatization followed by extraction for analysis of metabolites and other chemicals in hypersaline samples, enabling for the first time direct LC-MS-based exo-metabolomics analysis in sample matrices containing up to 2 molar total dissolved salts. The method, MetFish, is applicable to molecules containing amine, carboxylic acid, carbonyl, or hydroxyl functional groups, and can be integrated into either targeted or untargeted analysis pipelines. In targeted analyses, MetFish provided limits of quantification as low as 1 nM, broad linear dynamic ranges (up to 5-6 orders of magnitude) with excellent linearity, and low median inter-day reproducibility (e.g. 2.6%). MetFish was successfully applied in targeted and untargeted exo-metabolomics analyses of microbial consortia, quantifying amino acid dynamics in the exo-metabolome during community succession; in situ in a native prairie soil, whose exo-metabolome was isolated using a hypersaline extraction; and in input and produced fluids from a hydraulically fractured well, identifying dramatic changes in the exo-metabolome over time in the well.

microbiology↗

bioRxiv2018

Rapidly Assessing the Quality of Targeted Proteomics Experiments Through Monitoring Stable-isotope Labeled Standards

Targeted proteomics experiments based on selected reaction monitoring (SRM) have gained wide adoption in clinical biomarker, cellular modeling and numerous other biological experiments due to their highly accurate and reproducible quantification. The quantitative accuracy in targeted proteomics experiments is reliant on the stable-isotope, heavy-labeled peptide standards which are spiked into a sample and used as a reference when calculating the abundance of endogenous peptides. Therefore, the quality of measurement for these standards is a critical factor in determining whether data acquisition was successful. With improved MS instrumentation that enables the monitoring of hundreds of peptides in hundreds to thousands of samples, quality assessment is increasingly important and cannot be performed manually. We present Q4SRM, a software tool that rapidly checks the signal from all heavy labeled peptides and flags those that fail quality control metrics. Using four metrics, the tool detects problems both with individual SRM transitions and the collective group of transitions that monitor a single peptide. The programs speed enables its use at the point of data acquisition and can be ideally run immediately upon the completion of an LC-SRM-MS analysis.

bioinformatics↗

bioRxiv2018

An intermittent hypercaloric diet alters gut microbiota, prefrontal cortical gene expression and social behaviours in rats

Excessive consumption of high fat and high sugar (HFHS) diets are known to alter reward processing and aspects of behaviour, and change microbiota profiles. Studies in gnotobiotic mice also provide evidence that gut microorganisms influence social behaviour. To further investigate these interactions, the impact of intermittent access to a HFHS diet on social behaviour, gene expression and microbiota composition was examined. Rats were permitted intermittent daily access (2h / day) to a palatable HFHS diet for 28 days across the adolescent period. Social interaction, social memory and novel object recognition were assessed during this period. Following testing, RT-PCR was conducted on hippocampal and prefrontal cortex (PFC) samples. 16S ribosomal RNA amplicon sequencing was used for identification and relative quantification of bacterial taxa. Reduced social interaction behaviours, and impaired social memory and novel object recognition were observed in HFHS diet rats. Reduced levels of monoamine oxidase A (Maoa), catechol-O-methyltransferase (Comt) and brain derived neurotrophic factor (Bdnf) mRNA were observed in the PFC of HFHS diet rats. The relative abundance of a number of specific taxa differed significantly between the two diet groups, in particular, Lachnospiraceae and Ruminoccoceae bacteria, which also predicted social behaviours, novel object recognition performance and Maoa expression. This is the first study to show that limited daily access to HFHS diet alters social behaviour and cognition in rats. Furthermore, behavioural changes are associated with alterations to cortical gene expression of enzymes involved in monoamine synthesis and neuroplasticity, and microbiota profiles predicted diet-induced changes to behaviour and gene expression.

neuroscience↗

bioRxiv2018

Integrated systems biology and imaging of the smallest free-living eukaryote Ostreococcus tauri

Ostreococcus tauri is an ancient phototrophic microalgae that possesses favorable genetic and cellular characteristics for reductionist studies probing biosystem design and dynamics. Here multimodal bioimaging and multi-omics techniques were combined to interrogate O. tauri cellular changes in response to variations in bioavailable nitrogen and carbon ratios. Confocal microscopy, stimulated Raman scattering, and cryo-soft x-ray tomography revealed whole cell ultrastructural dynamics and composition while proteomic and lipidomic profiling captured changes at the molecular and macromolecular scale.\n\nDespite several energy dense long-chain triacylglycerol lipids showing more than 40-fold higher abundance under N deprivation, only a few proteins directly associated with lipid biogenesis showed significant expression changes. However, the entire pathway for starch granule biosynthesis was highly upregulated suggesting much of the cellular energy is preferentially directed towards starch over lipid accumulation. Additionally, three of the five most downregulated and five of the ten most upregulated proteins during severe nitrogen depletion were unnamed protein products that warrant additional biochemical analysis and functional annotation to control carbon transformation dynamics in this smallest eukaryote.

systems biology↗