Biology subjects

Krause, B.

Publications and source records attributed to Krause, B..

9 recordsLinked to original sources

bioRxiv2025

Auditory discrimination and identification of time of day for natural soundscapes

Following research on the auditory discrimination of natural soundscapes by human listeners [Apoux, Miller-Viacava, Ferriere, Dai, Krause, Sueur and Lorenzi (2023). J. Acoust. Soc. Am. 153, 2706], the present study assessed the ability of normal-hearing listeners to identify and/or discriminate the time of day (Dawn, Midday, Dusk, and Night) for soundscapes recorded in temperate and tropical forests. Identification was assessed using a single-interval four-alternative forced-choice task. Discrimination was assessed using a three-interval oddity task, where the listener was required to pick the odd one out. While identification of time of day was generally poor, discrimination was significantly above chance, indicating that listeners could hear some differences associated with the time of day, but could not effectively use those differences to assign the correct verbal label. The contribution of level, fine spectral, temporal envelope and temporal fine structure cues to discrimination was assessed. None of these cues appeared to be critical for time of day discrimination. Instead, it is suggested that listeners based their decisions on gross spectral cues, including aspects such as those related to ambient-noise spectral distributions.

ecology↗

bioRxiv2025

The proteasome maturation factor POMP moonlights as a stress-induced transcriptional regulator

Proteostasis - the maintenance of proteins at proper concentrations, conformations, and subcellular locations - is essential for cellular function and is governed by tightly regulated protein synthesis and degradation pathways. The Proteasome Maturation Protein (POMP) is a key chaperone involved in assembling the proteasome, the primary complex responsible for protein degradation. Despite the conserved role of POMP, its loss produces contrasting proteostatic effects in yeast and mammalian cells, pointing to additional, unexplored functions. In this study, we investigated the possibility that POMP plays a moonlighting role in proteostasis regulation. We discovered that upon proteasome disruption, POMP rapidly accumulates in the nucleolus in a manner dependent on HSF1 and reactive oxygen species (ROS). Proteomic analysis of POMP interactors revealed RNA processing factors and transcriptomic profiling showed that nucleolar POMP orchestrates a protective transcriptional program. Our findings indicate POMP is a built-in sensor and effector within the proteasome assembly pathway, capable of buffering disturbances in proteasome function through a novel, non-canonical role. Notably, this mechanism is developmentally controlled and active in neurodegenerative disease contexts. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=163 SRC="FIGDIR/small/650603v1_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@196cd2borg.highwire.dtl.DTLVardef@177d240org.highwire.dtl.DTLVardef@18c9bcborg.highwire.dtl.DTLVardef@483b94_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2023

Obesogenic diet in mice leads to inflammation and oxidative stress in the mother in association with sex-specific changes in fetal development, inflammatory markers and placental transcriptome

IntroductionObesity during pregnancy is related to adverse maternal and neonatal outcomes. Factors involved in these outcomes may include increased maternal insulin resistance, inflammation, oxidative stress and nutrient mishandling. The placenta is the primary determinant of fetal outcomes, and its function can be impacted by maternal obesity. The aim of this study in mice was to determine the effect of obesity on maternal lipid handling, inflammatory and redox state, and placental oxidative stress, inflammatory signaling, and gene expression relative to female and male fetal growth. MethodsFemale mice were fed control or obesogenic high-fat/high-sugar diet (HFHS) from 9 weeks prior to and during pregnancy. On day 18.5 of pregnancy, maternal plasma, and liver, placenta, and fetal serum were collected to examine the immune and redox state. The placental labyrinth zone (Lz) was dissected for RNA-sequencing analysis of gene expression changes. ResultsHFHS diet induced, in the dams, hepatic steatosis, oxidative stress (reduced catalase, elevated protein oxidation) and activation of pro-inflammatory pathways (p38-MAPK) along with imbalanced circulating cytokine concentrations (increased IL-6 and decreased IL-5 and IL-17A). HFHS fetuses were asymmetrically growth-restricted, showing sex-specific changes in circulating cytokines (GM-CSF, TNF-, IL-6 and IFN-{gamma}). Morphology of the placenta Lz was modified by a HFHS diet, in association with sex-specific alterations in the expression of genes and proteins implicated in oxidative stress, inflammation, and stress signaling. Placental gene expression changes were comparable to that seen in models of intrauterine inflammation and were related to a transcriptional network involving transcription factors, LYL1 and PLAG1. DiscussionThis study shows that fetal growth restriction with maternal obesity is related to elevated oxidative stress, inflammatory pathways, and sex-specific placental changes. Our data are important given the marked consequences and the rising rates of obesity worldwide.

physiology↗

bioRxiv2023

IMPROVING ANTIBODY AFFINITY USING LABORATORYDATA WITH LANGUAGE MODEL GUIDED DESIGN

AO_SCPLOWBSTRACTC_SCPLOWProtein design involves navigating vast sequence spaces to discover sequences with desired traits. Language models (LMs) pretrained on universal protein datasets have shown potential to make this search space tractable. However, LMs trained solely on natural sequences have limitations in creating proteins with novel functions. In this work, we used a combination of methods to finetune pretrained LMs on laboratory data collected in an anti-CD40L single domain antibody library campaign to develop an ensemble scoring function to model the fitness landscape and guide the design of new antibodies. Laboratory experiments confirmed improved CD40L affinity in the designed antibodies. Notably, the designs improved the affinities of four antibodies, originally ranging from 1 nanomolar to 100 picomolar, all to below 25 picomolar, approaching the limit of detection. This work is a promising step towards realizing the potential of LMs to leverage laboratory data to develop improved treatments for diseases.

synthetic biology↗

bioRxiv2022

Improved high-dimensional multivariate autoregressive model estimation of human electrophysiological data using fMRI priors

Multivariate autoregressive (MVAR) model estimation enables assessment of causal interactions in brain networks. However, accurately estimating MVAR models for high-dimensional electrophysiological recordings is challenging due to the extensive data requirements. Hence, the applicability of MVAR models for study of brain behavior over hundreds of recording sites has been very limited. Prior work has focused on different strategies for selecting a subset of important MVAR coefficients in the model and is motivated by the potential of MVAR models and the data requirements of conventional least-squares estimation algorithms. Here we propose incorporating prior information, such as fMRI, into MVAR model estimation using a weighted group LASSO regularization strategy. The proposed approach is shown to reduce data requirements by a factor of two relative to the recently proposed group LASSO method of Endemann et al. (2022) while resulting in models that are both more parsimonious and have higher fidelity to the ground truth. The effectiveness of the method is demonstrated using simulation studies of physiologically realistic MVAR models derived from iEEG data. The robustness of the approach to deviations between the conditions under which the prior information and iEEG data is obtained is illustrated using models from data collected in different sleep stages. This approach will allow accurate effective connectivity analyses over short time scales, facilitating investigations of causal interactions in the brain underlying perception and cognition during rapid transitions in behavioral state.

neuroscience↗

bioRxiv2022

Control of contextual memory through interneuronal α5-GABAA receptors

{gamma}-aminobutyric acid type A receptors that incorporate 5 subunits (5-GABAARs) are highly enriched in the hippocampus and are strongly implicated in control of learning and memory. Receptors located on pyramidal neuron dendrites have long been considered responsible, but here we report that their selective knockout from either interneurons (5-i-KO) or pyramidal neurons (5-pyr-KO) interferes with the ability of the general anesthetic etomidate to suppress contextual conditioning. Using Ca2+ imaging of CA1 pyramidal neuron activity in freely exploring mice to assess hippocampal function directly, we found that etomidate blocked the development of place cells and spatial engrams in wild type (WT) and 5-pyr-KO mice, but not in 5-i-KO mice. In addition, 5-i-KO mice developed weaker spatial engrams than WT mice under control conditions. These findings show that interneuronal 5-GABAARs serve a physiological role in promoting spatial learning, and that they mediate the suppression of hippocampus-dependent memory by etomidate.

neuroscience↗

bioRxiv2021

Deep neural language modeling enables functional protein generation across families

Bypassing natures evolutionary trajectory, de novo protein generation--defined as creating artificial protein sequences from scratch--could enable breakthrough solutions for biomedical and environmental challenges. Viewing amino acid sequences as a language, we demonstrate that a deep learning-based language model can generate functional artificial protein sequences across families, akin to generating grammatically and semantically correct natural language sentences on diverse topics. Our protein language model is trained by simply learning to predict the next amino acid for over 280 million protein sequences from thousands of protein families, without biophysical or coevolutionary modeling. We experimentally evaluate model-generated artificial proteins on five distinct antibacterial lysozyme families. Artificial proteins show similar activities and catalytic efficiencies as representative natural lysozymes, including hen egg white lysozyme, while reaching as low as 44% identity to any known naturally-evolved protein. The X-ray crystal structure of an enzymatically active artificial protein recapitulates the conserved fold and positioning of active site residues found in natural proteins. We demonstrate our language models ability to be adapted to different protein families by accurately predicting the functionality of artificial chorismate mutase and malate dehydrogenase proteins. These results indicate that neural language models successfully perform de novo protein generation across protein families and may prove to be a tool to shortcut evolution.

synthetic biology↗

bioRxiv2018

Pathway maps enable straightforward yet customized and semi-automated yet insightful analyses of omics data

To explore the molecular processes underlying some biological theme of interest based on public data, gene lists are used herein as input for the construction of annotated pathway maps, employing Cytoscape apps, and then high-throughput (\"omics\") gene expression data are overlaid onto these maps. Seeded with a published set of marker genes of the senescence-associated secretory phenotype and the genes of the cellular senescence KEGG pathway, a gene/protein interaction network and annotated clusters (a \"pathway map\") of cellular senescence are derived. The map can be amended, by adding some application-specific genes, and overlaid with gene expression data describing cellular senescence of fibroblasts and with disease-related gene expression data associated with prostate and pancreatic cancer, and with ischemic stroke, allowing insights into the role of cellular senescence in disease. Some gene expression data are derived from the \"Biomarker Benchmark repository\". The pathway map approach can be followed in principle for any biological theme of interest, fostering much-needed independence from the investigator-biased expert networks usually used for overlaying gene expression data.

genomics↗

bioRxiv2018

Pregnancy associated plasma protein-aa (Pappaa) regulates photoreceptor synaptic development to mediate visually guided behavior

To guide behavior, sensory systems detect the onset and offset of stimuli and process these distinct inputs via parallel pathways. In the retina, this strategy is implemented by splitting neural signals for light onset and offset via synapses connecting photoreceptors to ON and OFF bipolar cells, respectively. It remains poorly understood which molecular cues establish the architecture of this synaptic configuration to split light onset and offset signals. A mutant with reduced synapses between photoreceptors and one bipolar cell type, but not the other, could reveal a critical cue. From this approach, we report a novel synaptic role pregnancy associated plasma protein aa (pappaa) in promoting the structure and function of cone synapses that transmit light offset information. Electrophysiological and behavioral analyses indicated pappaa mutant zebrafish have dysfunctional cone to OFF bipolar cell synapses and impaired responses to light offset, but intact cone to ON bipolar cell synapses and light onset responses. Ultrastructural analyses of pappaa mutant cones showed a lack of presynaptic domains at synapses with OFF bipolar cells. pappaa is expressed postsynaptically to the cones during retinal synaptogenesis and encodes a secreted metalloprotease known to stimulate insulin-like growth factor 1 (IGF1) signaling. Induction of dominant negative IGF1 receptor expression during synaptogenesis reduced light offset responses. Conversely, stimulating IGF1 signaling at this time improved pappaa mutants light offset responses and cone presynaptic structures. Together, our results indicate Pappaa-regulated IGF1 signaling as a novel pathway that establishes how cone synapses convey light offset signals to guide behavior.\n\nSignificance StatementDistinct sensory inputs, like stimulus onset and offset, are often split at distinct synapses into parallel circuits for processing. In the retina, photoreceptors and ON and OFF bipolar cells form discrete synapses to split neural signals coding light onset and offset, respectively. The molecular cues that establish this synaptic configuration to specifically convey light onset or offset remain unclear. Our work reveals a novel cue: pregnancy associated plasma protein aa (pappaa), which regulates photoreceptor synaptic structure and function to specifically transmit light offset information. Pappaa is a metalloprotease that stimulates local insulin-like growth factor 1 (IGF1) signaling. IGF1 promotes various aspects of synaptic development and function and is broadly expressed; thus requiring local regulators, like Pappaa, to govern its specificity.

neuroscience↗