Identification and recombinant expression of a cutinase from Papiliotrema laurentii that hydrolyzes natural and synthetic polyesters.

Given the multitude of extracellular enzymes at their disposal, many of which are designed to degrade nature's polymers (lignin, cutin, cellulose, etc.), fungi are adept at targeting synthetic polyesters with similar chemical composition. Microbial-influenced deterioration of xenobiotic polymeric surfaces is an area of interest for material scientists as these are important for the conservation of the underlying structural materials. Here, we describe the isolation and characterization of the Papiliotrema laurentii 5307AH (P. laurentii) cutinase, Plcut1. P. laurentii is basidiomycete yeast with the ability to disperse Impranil-DLN (Impranil), a colloidal polyester polyurethane, in agar plates. To test whether the fungal factor involved in this clearing was a secreted enzyme, we screened the ability of P. laurentii culture supernatants to disperse Impranil. Using size exclusion chromatography (SEC), we isolated fractions that contained Impranil-clearing activity. These fractions harbored a single ~22 kD band, which was excised and subjected to peptide sequencing. Homology searches using the peptide sequences identified, revealed that the protein Papla1 543643 (Plcut1) displays similarities to serine esterase and cutinase family of proteins. Biochemical assays using recombinant Plcut1 confirmed that this enzyme has the capability to hydrolyze Impranil, soluble esterase substrates, and apple cutin. Finally, we confirmed the presence of the Plcut1 in culture supernatants using a custom antibody that specifically recognizes this protein. The work shown here supports a major role for the Plcut1 in the fungal degradation of natural polyesters and xenobiotic polymer surfaces.IMPORTANCEFungi play a vital role in the execution of a broad range of biological processes that drive ecosystem function through production of a diverse arsenal of enzymes. However, the universal reactivity of these enzymes is a current problem for the built environment and the undesired degradation of polymeric materials in protective coatings. Here, we report the identification and characterization of a hydrolase from Papiliotrema laurentii 5307AH, an aircraft-derived fungal isolate found colonizing a biodeteriorated polymer-coated surface. We show that P. laurentii secretes a cutinase capable of hydrolyzing soluble esters as well as ester-based compounds forming solid surface coatings. These findings indicate that this fungus plays a significant role in biodeterioration through the production of a cutinase adept at degrading ester-based polymers, some of which form the backbone of protective surface coatings. The work shown here provides insights into the mechanisms employed by fungi to degrade xenobiotic polymers.

Associations between sleep health, negative reinforcement learning, and alcohol use among South Florida college students with elevated internalizing symptoms.

Negative reinforcement is proposed to mediate associations between sleep and alcohol use, especially among people with depression and/or anxiety symptoms. Worse sleep (e.g., shorter duration, less efficiency, more irregular timing) exacerbates negative emotions, which alcohol may temporarily relieve. Not yet examined, we propose sleep indirectly impacts early stages of alcohol use via differences in negative reinforcement learning (NRL), since sleep impacts emotion, reward response, and learning. The current study aimed to replicate associations between sleep and alcohol use, test associations with NRL, and examine indirect associations between sleep health and alcohol use via NRL among 60 underage college students (ages 18-20 years, 77% female) varying in depression and anxiety symptoms. Participants wore Fitbit smartwatches and completed daily diaries measuring sleep and substance use for ∼14 days before completing two computer tasks assessing social (SNRL) and monetary (MNRL) negative reinforcement learning. Robust generalized linear models tested direct associations within the proposed model. SNRL performance was positively associated with alcohol use, but no other associations were observed. Statistical mediation models failed to indicate indirect effects of sleep on alcohol use via SNRL or MNRL performance. Post-hoc exploratory models examining depression and anxiety symptoms as moderators of direct associations indicated several interactions. Positive associations between sleep timing variability and alcohol use were weakened at higher anxiety symptom severity and stronger at higher depression symptom severity. The positive association between SNRL performance and alcohol use was also stronger at higher depression symptom severity. Among students with elevated depression symptoms, variable sleep timing and stronger SNRL performance were independently associated with more alcohol use, but indirect effects were not supported. Future research should replicate findings, confirm causality of interactions, and examine sleep timing and behavioral responses to negative social stimuli as targets for improving alcohol-related outcomes among underage college students with elevated depressive symptoms.

Sleep fails to depotentiate amygdala-reactivity to negative emotional stimuli in youth with elevated symptoms of anxiety.

Sleep-related problems often precede escalating anxiety in early adolescence. Pushing beyond broad sleep-mental health associations and toward mechanistic theories of their interplay can inform etiological models of psychopathology. Recent studies suggest that sleep depotentiates neural (e.g., amygdala) reactivity during reexposure to negative emotional stimuli in adults. Persistent amygdala reactivity to negative experiences and poor sleep characterize anxiety, particularly at the transition to adolescence. We propose that sleep depotentiates amygdala reactivity in youth but fails to do so among youth with anxiety. Participants (n = 34; 18 males; age, mean [M] = 11.35, standard deviation [SD] = 2.00) recruited from the community and specialty anxiety clinics viewed valenced images (positive, negative, and neutral) across two fMRI sessions (Study, Test), separated by a 10-12-hour retention period of sleep or wake (randomized). Mixed linear models regressed basolateral amygdala (BLA) activation and BLA-medial prefrontal cortex (mPFC) functional connectivity to negative images on Time, Condition, and Anxiety Severity. There were greater reductions in BLA activations to negative target images from Study to Test in the Sleep Condition, which was blunted with higher anxiety (b = -0.065, z = -2.355, p = 0.019). No such sleep- or anxiety-related effects were observed for BLA-mPFC functional connectivity (ps > 0.05). Sleep supports depotentiation of amygdala reactivity to negative stimuli in youth, but this effect is blunted at higher levels of anxiety. Disruptions in sleep-related affective habituation may be a critical, modifiable driver of anxiety.

Neural Connectivity Subtypes Predict Discrete Attentional Bias Profiles Among Heterogeneous Anxiety Patients.

On average, anxious patients show altered attention to threat-including early vigilance towards threat and later avoidance of threat-accompanied by altered functional connectivity across brain regions. However, substantial heterogeneity within clinical, neural, and attentional features of anxiety is overlooked in typical group-level comparisons. We used a well-validated method for data-driven parsing of neural connectivity to reveal connectivity-based subgroups among 60 adults with transdiagnostic anxiety. Subgroups were externally compared on attentional patterns derived from independent behavioral measures. Two subgroups emerged. Subgroup A (68% of patients) showed stronger executive network influences on sensory processing regions and a paradigmatic "vigilance-avoidance" pattern on external behavioral measures. Subgroup B was defined by a larger number of limbic influences on sensory regions and exhibited a more atypical and inconsistent attentional profile. Neural connectivity-based categorization revealed an atypical, limbic-driven pattern of connectivity in a subset of anxious patients that generalized to atypical patterns of selective attention.

Protracted amygdalar response predicts efficacy of a computer-based intervention targeting attentional patterns in transdiagnostic clinical anxiety.

Individuals with clinical anxiety demonstrate an attention bias toward threatening information, which is thought to be partially driven by heightened amygdala activity to perceived threat. Attention Bias Modification (ABM) is a computer-based treatment that trains attention toward neutral stimuli and away from threatening stimuli. Alterations in initial processing of threat have been linked to ABM responses, but the impact of protracted processing in the aftermath of neutral and threatening information on ABM outcomes has not been well studied. Our study tested whether sustained activity in the amygdala, which occurred after neutral and threatening stimuli had been removed, could predict which individuals would respond well to ABM. Unmedicated anxious individuals underwent a baseline fMRI assessment during performance of a task sensitive to protracted emotional processing. Afterward, they were randomized to complete eight sessions of ABM (n = 38) or a sham training (n = 19). ABM patients who displayed greater sustained bilateral amygdalar response in the aftermath of neutral stimuli displayed the least improvement in self-reported (but not clinician-rated) vigilance symptoms. In contrast, amygdalar response did not predict improvement in sham patients. Results suggest that in certain anxious individuals, the amygdala may have a robust protracted response even to subjectively neutral cues, which could make these individuals a poor fit for ABM because of its focus on repeatedly retraining attention toward neutral cues. Findings may help elucidate neural mechanisms of ABM and promote the identification of a subset of anxious patients who would be good candidates for this intervention.

Towards personalized, brain-based behavioral intervention for transdiagnostic anxiety: Transient neural responses to negative images predict outcomes following a targeted computer-based intervention.

OBJECTIVE: Clinical anxiety is prevalent, highly comorbid with other conditions, and associated with significant medical morbidity, disability, and public health burden. Excessive attentional deployment toward threat is a transdiagnostic dimension of anxiety seen at both initial and sustained stages of threat processing. However, group-level observations of these phenomena mask considerable within-group heterogeneity that has been linked to treatment outcomes, suggesting that a transdiagnostic, individual differences approach may capture critical, clinically relevant information. METHOD: Seventy clinically anxious individuals were randomized to receive 8 sessions of attention bias modification (ABM; n = 41 included in analysis), a computer-based mechanistic intervention that specifically targets initial stages of threat processing, or a sham control (n = 21). Participants completed a mixed block/event-related functional MRI task optimized to discriminate transient from sustained neural responses to threat. RESULTS: Larger transient responses across a wide range of cognitive-affective regions (e.g., ventrolateral prefrontal cortex, anterior cingulate cortex, amygdala) predicted better clinical outcomes following ABM, in both a priori anatomical regions and whole-brain analyses; sustained responses did not. A spatial pattern recognition algorithm using transient threat responses successfully discriminated the top quartile of ABM responders with 68% accuracy. CONCLUSIONS: Neural alterations occurring on the relatively transient timescale that is specifically targeted by ABM predict favorable clinical outcomes. Results inform how to expand on the initial promise of neurocognitive treatments like ABM by fine-tuning their clinical indications (e.g., through personalized mechanistic intervention relevant across diagnoses) and by increasing the range of mechanisms that can be targeted (e.g., through synergistic treatment combinations and/or novel neurocognitive training protocols designed to tackle identified predictors of nonresponse). (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Pooled patient-level meta-analysis of children and adults completing a computer-based anxiety intervention targeting attentional bias.

Computer-based approaches, such as Attention Bias Modification (ABM), could help improve access to care for anxiety. Study-level meta-analyses of ABM have produced conflicting findings and leave critical questions unresolved regarding ABM's mechanisms of action and clinical potential. We pooled patient-level datasets from randomized controlled trials of children and adults with high-anxiety. Attentional bias (AB) towards threat, the target mechanism of ABM, was tested as an outcome and a mechanistic mediator and moderator of anxiety reduction. Diagnostic remission and Liebowitz Social Anxiety Scale (LSAS) were clinical outcomes available in enough studies to enable pooling. Per-patient data were obtained on at least one outcome from 13/16 eligible studies [86% of eligible participants; n=778]. Significant main effects of ABM on diagnostic remission (ABM-22.6%, control-10.8%; OR=2.57; p=0.006) and AB (ß* (95%CI)=-0.63 (-0.83, -0.42); p<0.00005) were observed. There was no main effect of ABM on LSAS. However, moderator analyses suggested ABM was effective for patients who were younger (≤37y), trained in the lab, and/or assessed by clinicians. Under the same conditions where ABM was effective, mechanistic links between AB and anxiety reduction were supported. Under these specific circumstances, ABM reduces anxiety and acts through its target mechanism, supporting ABM's theoretical basis while simultaneously suggesting clinical indications and refinements to improve its currently limited clinical potential.