Biology subjects

Stanley, J. A.

Publications and source records attributed to Stanley, J. A..

7 recordsLinked to original sources

bioRxiv2026

Trauma-Exposed Adolescents Show Reduced Cortical Glutamate Modulation during Inhibitory Control with Negative Emotional Stimuli

BackgroundChildhood trauma exposure (TE) may heighten negative emotional responses, overwhelm cognitive control, and increase risk for anxiety disorders. Cognitive control is facilitated by glutamatergic (Glu) excitatory neurotransmission within the dorsal anterior cingulate cortex (dACC). Dynamic changes in dACC Glu levels were investigated using {superscript 1}H functional magnetic resonance spectroscopy (1H fMRS) to assess the impact of negative emotional processing on neural mechanisms supporting cognitive control in TE-youth. MethodsFifty adolescents were categorized into two TE-Groups: Higher (Mtrauma=6{+/-}1events) and Lower (Mtrauma=3{+/-}1events). 1H fMRS from the dACC was acquired during an inhibitory motor control task requiring tapping responses to stimuli under two Response Modes, "NonSelective" (100% response) and "Selective" (80% response, 20% inhibition), executed with two Stimuli Conditions, "Squares" (no emotion) and "Faces" (emotion). Glu modulation (relative to basal levels) was tested across TE-Group, Stimuli Condition, and their interaction. Within each Stimuli Condition, Glu modulation was tested across Response Modes by TE-Group. ResultsWe observed a 2-way interaction of TE-Group x Stimuli Condition ({chi}2=4.66, p=0.031). Post-hoc tests revealed significantly lower Glu modulation in Higher TE vs Lower TE (p=.023) during Faces but not Squares. This Glu modulation did not differ across Response Modes. Within the Higher TE-Group, Glu was significantly reduced during Faces compared to Squares (p<.001). Basal dACC Glu levels did not differ between groups. ConclusionsTE-Group differences in adolescent dACC Glu modulation were observed during cognitive control performed with emotional, but not non-emotional, stimuli, highlighting the value of 1H fMRS for detecting trauma-related differences in task-related excitatory neurochemical dynamics.

neuroscience↗

bioRxiv2026

A novel mathematical construction for identifying attractors from task-driven fMRI data

Functional brain imaging data can provide a window into the task-driven network states that shape brain function (or dysfunction). Conventionally, these network states can be represented as bivariate correlation matrices (which are formed from fMRI time series from multiple brain regions/nodes within any task window). Here, we treat these conventional connectivity matrices as connectivity terrains in order to recover local structure. In principle, any such terrain can be traversed node by node, where from any node, one can move towards its nearest functional neighbor (i.e., its maximally correlated node). In terrains with meaningful structure, such traversals across multiple nodes should converge to attractor nodes; here, the nodes that flow into a shared attractor form an attractor basin, which effectively is a sub-network within the system. Extant methods (e.g., degree distribution and characteristic path length) can summarize global network properties but cannot identify attractor nodes and basins. Here, we construct a new relation, called transitive maximal correlation (TMC) that can recover attractors and attractor basins in connectivity terrains. Node A is said to be transitively maximally correlated to node B if and only if B is an attractor into which A flows. We first develop the mathematical basis for deriving a TMC matrix TMC(M) from a bivariate correlation matrix M (before explaining this with hypothetical data). We next apply the TMC relation to connectivity terrains derived from real fMRI time series data, where these data were acquired in two distinct task-domains (that varied in their extent of cross-cerebral demand): i) associative learning and ii) visually guided motor control. We show that TMC is remarkably sensitive to inter-hemispheric structure in the connectivity terrain; here, attractor pairs that were inter-hemispheric homologues were more likely to be observed for the cross-cerebral learning task, than the more circumscribed motor-control data. We confirm the condition-specific sensitivity of TMC showing that observed attractor basins differed significantly across conditions of the learning task. Finally, we demonstrate that TMC complements graph theoretic constructions like path length and betweenness centrality. We suggest that TMC is a mathematically sound and novel method for capturing functional properties of brain networks.

neuroscience↗

bioRxiv2021

Ubiquitous mRNA decay fragments in E. coli redefine the functional transcriptome

Bacterial mRNAs have short life cycles, in which transcription is rapidly followed by translation and degradation within seconds to minutes. The resulting diversity of mRNA molecules across different life-cycle stages impacts their functionality but has remained unresolved. Here we quantitatively map the 3' status of cellular RNAs in Escherichia coli during steady-state growth and report a large fraction of molecules (median>60%) that are fragments of canonical full-length mRNAs. The majority of RNA fragments are decay intermediates, whereas nascent RNAs contribute to a smaller fraction. Despite the prevalence of decay intermediates in total cellular RNA, these intermediates are underrepresented in the pool of ribosome-associated transcripts and can thus distort quantifications for the abundance of full-length, functional mRNAs. The large heterogeneity within mRNA molecules in vivo highlights the importance in discerning functional transcripts and provides a lens for studying the dynamic life cycle of mRNAs.

molecular biology↗

bioRxiv2020

Unraveling Oxidative Stress Resistance: Molecular Properties Govern Proteome Vulnerability

AbstractOxidative stress alters cell viability, from microorganism irradiation sensitivity to human aging and neurodegeneration. Deleterious effects of protein carbonylation by reactive oxygen species (ROS) make understanding molecular properties determining ROS-susceptibility essential. The radiation-resistant bacterium Deinococcus radiodurans accumulates less carbonylation than sensitive organisms, making it a key model for deciphering properties governing oxidative stress resistance. We integrated shotgun redox proteomics, structural systems biology, and machine learning to resolve properties determining protein damage by {gamma}-irradiation in Escherichia coli and D. radiodurans at multiple scales. Local accessibility, charge, and lysine enrichment accurately predict ROS-susceptibility. Lysine, methionine, and cysteine usage also contribute to ROS-resistance of the D. radiodurans proteome. Our model predicts proteome maintenance machinery and proteins protecting against ROS are more resistant in D. radiodurans. Our findings substantiate that protein-intrinsic protection impacts oxidative stress resistance, identifying causal molecular properties. One Sentence SummaryProteins differ in intrinsic susceptibility to oxidation, a mode of evolutionary adaptation for stress tolerance in bacteria.

systems biology↗

bioRxiv2020

C. elegans processes sensory information to choose between freeloading and self-defense strategies

Hydrogen peroxide is the preeminent chemical weapon that organisms use for combat. Individual cells rely on conserved defenses to prevent and repair peroxide-induced damage, but whether similar defenses might be coordinated across cells in animals remains poorly understood. Here, we identify a neuronal circuit in the nematode Caenorhabditis elegans that processes information perceived by two sensory neurons to control the induction of hydrogen-peroxide defenses in the organism. We found that catalases produced by Escherichia coli, the nematodes food source, can deplete hydrogen peroxide from the local environment and thereby protect the nematodes. In the presence of E. coli, the nematodes neurons signal via TGF{beta}-insulin/IGF1 relay to target tissues to repress expression of catalases and other hydrogen-peroxide defenses. This adaptive strategy is the first example of a multicellular organism modulating its defenses when it expects to freeload from the protection provided by molecularly orthologous defenses from another species.

neuroscience↗

bioRxiv2020

The SensorOverlord predicts the accuracy of measurements with ratiometric biosensors

Two-state ratiometric biosensors change conformation and spectral properties in response to specific biochemical inputs. Much effort over the past two decades has been devoted to engineering biosensors specific for ions, nucleotides, amino acids, and biochemical potentials. The utility of these biosensors is diminished by empirical errors in fluorescence-ratio signal measurement, which reduce the range of input values biosensors can measure accurately. Here, we present a formal framework and a web-based tool, the SensorOverlord, that predicts the input range of two-state ratiometric biosensors given the experimental error in measuring their signal. We demonstrate the utility of this tool by predicting the range of values that can be measured accurately by biosensors that detect pH, NAD+, NADH, NADPH, histidine, and glutathione redox potential. The SensorOverlord enables users to compare the predicted accuracy of biochemical measurements made with different biosensors, and subsequently select biosensors that are best suited for their experimental needs.

cell biology↗

bioRxiv2019

Enhancers predominantly regulate gene expression in vivo via transcription initiation.

Gene transcription occurs via a cycle of linked events including initiation, promoter proximal pausing and elongation of RNA polymerase II (Pol II). A key question is how do transcriptional enhancers influence these events to control gene expression? Here we have used a new approach to quantify transcriptional initiation and pausing in vivo, while simultaneously identifying transcription start sites (TSSs) and pause-sites (TPSs) from single RNA molecules. When analyzed in parallel with nascent RNA-seq, these data show that differential gene expression is achieved predominantly via changes in transcription initiation rather than Pol II pausing. Using genetically engineered mouse models deleted for specific enhancers we show that these elements control gene expression via Pol II recruitment and/or initiation rather than via promoter proximal pause release. Together, our data show that enhancers, in general, control gene expression predominantly by Pol II recruitment and initiation rather than via pausing.

genomics↗