Irreversibility in bacterial regulatory networks.

Irreversibility, in which a transient perturbation leaves a system in a new state, is an emergent property in systems of interacting entities. This property has well-established implications in statistical physics but remains underexplored in biological networks, especially for bacteria and other prokaryotes whose regulation of gene expression occurs predominantly at the transcriptional level. Focusing on the reconstructed regulatory network of Escherichia coli, we examine network responses to transient single-gene perturbations. We predict irreversibility in numerous cases and find that the incidence of irreversibility increases with the proximity of the perturbed gene to positive circuits in the network. Comparison with experimental data suggests a connection between the predicted irreversibility to transient perturbations and the evolutionary response to permanent perturbations.

The genetic landscape of a metabolic interaction.

While much prior work has explored the constraints on protein sequence and evolution induced by physical protein-protein interactions, the sequence-level constraints emerging from non-binding functional interactions in metabolism remain unclear. To quantify how variation in the activity of one enzyme constrains the biochemical parameters and sequence of another, we focus on dihydrofolate reductase (DHFR) and thymidylate synthase (TYMS), a pair of enzymes catalyzing consecutive reactions in folate metabolism. We use deep mutational scanning to quantify the growth rate effect of 2696 DHFR single mutations in 3 TYMS backgrounds under conditions selected to emphasize biochemical epistasis. Our data are well-described by a relatively simple enzyme velocity to growth rate model that quantifies how metabolic context tunes enzyme mutational tolerance. Together our results reveal the structural distribution of epistasis in a metabolic enzyme and establish a foundation for the design of multi-enzyme systems.

A continuous epistasis model for predicting growth rate given combinatorial variation in gene expression and environment.

Quantifying and predicting growth rate phenotype given variation in gene expression and environment is complicated by epistatic interactions and the vast combinatorial space of possible perturbations. We developed an approach for mapping expression-growth rate landscapes that integrates sparsely sampled experimental measurements with an interpretable machine learning model. We used mismatch CRISPRi across pairs and triples of genes to create over 8,000 titrated changes in E. coli gene expression under varied environmental contexts, exploring epistasis in up to 22 distinct environments. Our results show that a pairwise model previously used to describe drug interactions well-described these data. The model yielded interpretable parameters related to pathway architecture and generalized to predict the combined effect of up to four perturbations when trained solely on pairwise perturbation data. We anticipate this approach will be broadly applicable in optimizing bacterial growth conditions, generating pharmacogenomic models, and understanding the fundamental constraints on bacterial gene expression. A record of this paper's transparent peer review process is included in the supplemental information.

Engineering Proteins Using Statistical Models of Coevolutionary Sequence Information.

Homologous protein sequences are wonderfully diverse, indicating many possible evolutionary "solutions" to the encoding of function. Consequently, one can construct statistical models of protein sequence by analyzing amino acid frequency across a large multiple sequence alignment. A central premise is that covariance between amino acid positions reflects coevolution due to a shared functional or biophysical constraint. In this review, we describe the implementation and discuss the advantages, limitations, and recent progress on two coevolution-based modeling approaches: (1) Potts models of protein sequence (direct coupling analysis [DCA]-like), and (2) the statistical coupling analysis (SCA). Each approach detects interesting features of protein sequence and structure-the former emphasizes local physical contacts throughout the structure, while the latter identifies larger evolutionarily coupled networks of residues. Recent advances in large-scale gene synthesis and high-throughput functional selection now motivate additional work to benchmark model performance across quantitative function prediction and de novo design tasks.

The Genetic Landscape of a Metabolic Interaction.

Enzyme abundance, catalytic activity, and ultimately sequence are all shaped by the need of growing cells to maintain metabolic flux while minimizing accumulation of deleterious intermediates. While much prior work has explored the constraints on protein sequence and evolution induced by physical protein-protein interactions, the sequence-level constraints emerging from non-binding functional interactions in metabolism remain unclear. To quantify how variation in the activity of one enzyme constrains the biochemical parameters and sequence of another, we focused on dihydrofolate reductase (DHFR) and thymidylate synthase (TYMS), a pair of enzymes catalyzing consecutive reactions in folate metabolism. We used deep mutational scanning to quantify the growth rate effect of 2,696 DHFR single mutations in 3 TYMS backgrounds under conditions selected to emphasize biochemical epistasis. Our data are well-described by a relatively simple enzyme velocity to growth rate model that quantifies how metabolic context tunes enzyme mutational tolerance. Together our results reveal the structural distribution of epistasis in a metabolic enzyme and establish a foundation for the design of multi-enzyme systems.

The Continued Impact of the COVID-19 Pandemic on Pediatric Obesity: A Commentary on the Return to a Healthy New "Normal".

Two years into this pandemic, mental health symptoms are more prevalent in children and adolescents, routine wellness visits have decreased, individuals and families are experiencing increased stress, and food and nutrition insecurity are on the rise. Pediatric overweight and obesity are yet another health condition that has been impacted by the pandemic. The current commentary aims to (a) summarize a variety of factors contributing to worsening obesity and healthy lifestyle choices in youth throughout the pandemic and to (b) provide recommendations for healthcare providers on navigating this challenge. Specific health behaviors, such as increased sedentary behavior, decreased physical activity, a change to families' home-food environments, and an increase in sleep dysregulation have contributed to increased weight gain in children and adolescents. As uncertainty continues with the advent of various COVID-19 variants, it remains important to consider how the pandemic has impacted pediatric overweight and obesity.

Accelerating Biological Insight for Understudied Genes.

The rapid expansion of genome sequence data is increasing the discovery of protein-coding genes across all domains of life. Annotating these genes with reliable functional information is necessary to understand evolution, to define the full biochemical space accessed by nature, and to identify target genes for biotechnology improvements. The majority of proteins are annotated based on sequence conservation with no specific biological, biochemical, genetic, or cellular function identified. Recent technical advances throughout the biological sciences enable experimental research on these understudied protein-coding genes in a broader collection of species. However, scientists have incentives and biases to continue focusing on well documented genes within their preferred model organism. This perspective suggests a research model that seeks to break historic silos of research bias by enabling interdisciplinary teams to accelerate biological functional annotation. We propose an initiative to develop coordinated projects of collaborating evolutionary biologists, cell biologists, geneticists, and biochemists that will focus on subsets of target genes in multiple model organisms. Concurrent analysis in multiple organisms takes advantage of evolutionary divergence and selection, which causes individual species to be better suited as experimental models for specific genes. Most importantly, multisystem approaches would encourage transdisciplinary critical thinking and hypothesis testing that is inherently slow in current biological research.

Structurally distributed surface sites tune allosteric regulation.

Our ability to rationally optimize allosteric regulation is limited by incomplete knowledge of the mutations that tune allostery. Are these mutations few or abundant, structurally localized or distributed? To examine this, we conducted saturation mutagenesis of a synthetic allosteric switch in which Dihydrofolate reductase (DHFR) is regulated by a blue-light sensitive LOV2 domain. Using a high-throughput assay wherein DHFR catalytic activity is coupled to E. coli growth, we assessed the impact of 1548 viable DHFR single mutations on allostery. Despite most mutations being deleterious to activity, fewer than 5% of mutations had a statistically significant influence on allostery. Most allostery disrupting mutations were proximal to the LOV2 insertion site. In contrast, allostery enhancing mutations were structurally distributed and enriched on the protein surface. Combining several allostery enhancing mutations yielded near-additive improvements to dynamic range. Our results indicate a path toward optimizing allosteric function through variation at surface sites.

Many proteins exhibit a property called 'allostery'. In allostery, an input signal at a specific site of a protein ­ such as a molecule binding, or the protein absorbing a photon of light ­ leads to a change in output at another site far away. For example, the protein might catalyze a chemical reaction faster or bind to another molecule more tightly in the presence of the input signal. This protein 'remote control' allows cells to sense and respond to changes in their environment. An ability to rapidly engineer new allosteric mechanisms into proteins is much sought after because this would provide an approach for building biosensors and other useful tools. One common approach to engineering new allosteric regulation is to combine a 'sensor' or input region from one protein with an 'output' region or domain from another. When researchers engineer allostery using this approach of combining input and output domains from different proteins, the difference in the output when the input is 'on' versus 'off' is often small, a situation called 'modest allostery'. McCormick et al. wanted to know how to optimize this domain combination approach to increase the difference in output between the 'on' and 'off' states. More specifically, McCormick et al. wanted to find out whether swapping out or mutating specific amino acids (each of the individual building blocks that make up a protein) enhances or disrupts allostery. They also wanted to know if there are many possible mutations that change the effectiveness of allostery, or if this property is controlled by just a few amino acids. Finally, McCormick et al. questioned where in a protein most of these allostery-tuning mutations were located. To answer these questions, McCormick et al. engineered a new allosteric protein by inserting a light-sensing domain (input) into a protein involved in metabolism (a metabolic enzyme that produces a biomolecule called a tetrahydrofolate) to yield a light-controlled enzyme. Next, they introduced mutations into both the 'input' and 'output' domains to see where they had a greater effect on allostery. After filtering out mutations that destroyed the function of the output domain, McCormick et al. found that only about 5% of mutations to the 'output' domain altered the allosteric response of their engineered enzyme. In fact, most mutations that disrupted allostery were found near the site where the 'input' domain was inserted, while mutations that enhanced allostery were sprinkled throughout the enzyme, often on its protein surface. This was surprising in light of the commonly-held assumption that mutations on protein surfaces have little impact on the activity of the 'output' domain. Overall, the effect of individual mutations on allostery was small, but McCormick et al. found that these mutations can sometimes be combined to yield larger effects. McCormick et al.'s results suggest a new approach for optimizing engineered allosteric proteins: by introducing mutations on the protein surface. It also opens up new questions: mechanically, how do surface sites affect allostery? In the future, it will be important to characterize how combinations of mutations can optimize allosteric regulation, and to determine what evolutionary trajectories to high performance allosteric 'switches' look like.

Historic Firsts: Aeromedical Evacuation and the Transportation Isolation System.

This short communication highlights the US Air Force's recent success with having their aeromedical evacuation crews use the Transportation Isolation System for the first time operationally to transport patients positive for coronavirus disease 2019.

Silicosis.

Occupational exposures to dust with elevated levels of respirable crystalline silica in artificial stone increase workers' risk for silicosis.

A simplified strategy for titrating gene expression reveals new relationships between genotype, environment, and bacterial growth.

A lack of high-throughput techniques for making titrated, gene-specific changes in expression limits our understanding of the relationship between gene expression and cell phenotype. Here, we present a generalizable approach for quantifying growth rate as a function of titrated changes in gene expression level. The approach works by performing CRISPRi with a series of mutated single guide RNAs (sgRNAs) that modulate gene expression. To evaluate sgRNA mutation strategies, we constructed a library of 5927 sgRNAs targeting 88 genes in Escherichia coli MG1655 and measured the effects on growth rate. We found that a compounding mutational strategy, through which mutations are incrementally added to the sgRNA, presented a straightforward way to generate a monotonic and gradated relationship between mutation number and growth rate effect. We also implemented molecular barcoding to detect and correct for mutations that 'escape' the CRISPRi targeting machinery; this strategy unmasked deleterious growth rate effects obscured by the standard approach of ignoring escapers. Finally, we performed controlled environmental variations and observed that many gene-by-environment interactions go completely undetected at the limit of maximum knockdown, but instead manifest at intermediate expression perturbation strengths. Overall, our work provides an experimental platform for quantifying the phenotypic response to gene expression variation.

Weight outcomes in children with developmental disabilities from a multidisciplinary clinic.

BACKGROUND: Children with developmental disabilities experience disparately high rates of obesity yet there are few reports detailing clinical outcomes for this population. AIM: To describe outcomes of obesity treatment for children with developmental disabilities and a comparison group of children without developmental disabilities. METHODS AND PROCEDURES: We examined weight outcomes of children with and without developmental disabilities seen in a family-centered, multidisciplinary treatment center over a ten-year period. We stratified by age and developmental disability diagnosis. We assessed whether intake demographic or health behavior data was associated with successful reduction of adiposity over six and twelve month follow-up periods, using a ≥5% absolute reduction in percent over the 95th percentile body mass index (BMIp95) as the primary outcome. OUTCOMES AND RESULTS: Over a ten-year period, 148 of 556 children in the obesity clinic (27 %) had a developmental disability. In children <12 years of age, 36 % of children with developmental disabilities reduced their adiposity compared with 18 % of children without developmental disabilities at six months, p = .01. This pattern continued at twelve months. Active transport to school was associated with reduced adiposity for those without a disability. Older children with disabilities rarely had a significant reduction (2 of 26 children), and they took more medications with weight-related side effects. CONCLUSIONS AND IMPLICATIONS: Younger children with developmental disabilities experienced relative success in reducing their adiposity. Challenges to addressing obesity in this population include structural barriers to physical activity and medications for behavioral management with weight-related side effects.

Timely Delivery of Discharge Medications to Patients' Bedsides: A Patient-centered Quality Improvement Project.

INTRODUCTION: Patients who are unable to fill prescriptions after discharge are at risk of hospital readmission. Ensuring that patients have prescriptions in hand at the time of discharge is a critical component of a safe and effective discharge process. Using a "Meds to Beds" program, we aimed to increase the percentage of patients discharged from Holtz Children's Hospital with medications in hand from 49% to 80%, reduce turnaround time (TAT) from electronic prescription signature to bedside delivery from 4.9 hours (±2.6 hours) to 2 hours, and increase caregiver satisfaction. METHODS: We formed a multidisciplinary team and implemented 4 patient-centered interventions through iterative plan-do-study-act cycles. Statistical process control charts were used to understand the impact of the interventions over 10 months. Hospital length of stay and discharges before 2:00 pm were used as balancing measures. We measured caregiver satisfaction using a telephone survey administered by pediatric residents within 7 days after discharge. RESULTS: The mean percentage of patients discharged with medications in hand increased to 76%. TAT decreased to 3.5 hours (±1.8 hours). Length of stay did not significantly increase, whereas the percentage of patients discharged before 2:00 pm did. Caregivers of patients who had prescriptions delivered to their bedside reported high levels of satisfaction. CONCLUSIONS: Using a "Meds to Beds" program, we increased the percentage of patients discharged with medications in hand, decreased TAT with reduced variability, and achieved high levels of caregiver satisfaction. Importantly, there was a shift in the culture of the institution toward improved medication access for patients.

Assessing Burnout and Associated Risk Factors in Medical Students.

PURPOSE: Our study aims to build on existing literature by assessing factors that may be associated with an increased risk of burnout amongst medical students, particularly students of color. METHODS: Our cross-sectional survey included the Copenhagen Burnout Inventory (CBI) and additional de novo questions. Surveys were administered electronically in June 2017 using a convenience sampling method. RESULTS: A total of 162 survey results were recorded. Of those, 159 completed demographic information with 43% of respondents being non-White, 64% women, 50% reported not having a mentor in medicine, 30% having an immediate family member in medicine, and 71% being concerned about the financial burden associated with medical school. Black students were more likely to be the first in their family to attend college, not have a physician family member, and have financial concerns. The average CBI burnout scores (n = 138) indicated that overall students are not experiencing burnout. However, nearly 50% of students experience personal, 42% work, and 12% client related burnout based on their individual scores. Women were significantly more likely to experience work related burnout (p = 0. 028) and had significantly higher personal burnout scores (p = 0.017). Additionally, Black students have significantly higher personal burnout scores (p = 0.013) compared to all other reported races. CONCLUSION: Although factors assessed during this study showed no significant effect, the data trends suggest that both women and Black students experienced higher rates of burnout. Further discussion regarding solutions to burnout is required in order to intervene early on in training for those at highest risk.

Altered expression of a quality control protease in E. coli reshapes the in vivo mutational landscape of a model enzyme.

Protein mutational landscapes are shaped by the cellular environment, but key factors and their quantitative effects are often unknown. Here we show that Lon, a quality control protease naturally absent in common E. coli expression strains, drastically reshapes the mutational landscape of the metabolic enzyme dihydrofolate reductase (DHFR). Selection under conditions that resolve highly active mutants reveals that 23.3% of all single point mutations in DHFR are advantageous in the absence of Lon, but advantageous mutations are largely suppressed when Lon is reintroduced. Protein stability measurements demonstrate extensive activity-stability tradeoffs for the advantageous mutants and provide a mechanistic explanation for Lon's widespread impact. Our findings suggest possibilities for tuning mutational landscapes by modulating the cellular environment, with implications for protein design and combatting antibiotic resistance.

Psychopathology and Adolescent Bariatric Surgery: A Topical Review to Support Psychologists in Assessment and Treatment Considerations.

The rising rates of severe obesity among adolescents in the United States indicate a dire need for more intensive weight management strategies. While current evidence suggests that bariatric surgery is a safe and efficacious intervention for adolescents, the linkages with psychopathology before and after surgery are not well understood. Psychologists are an integral part of the interdisciplinary surgery team and play an important role in preparing youth for bariatric surgery as well as supporting adolescents post-surgery. The present manuscript reviews the literature on psychopathology in the context of adolescent bariatric surgery, discusses consideration of psychopathology as a contraindication for surgery, and provides recommendations on how psychologist members of the bariatric surgery team may balance attention to motivation and adherence to medical recommendations with assessment and treatment of psychopathology. Finally, the importance of continued research to confirm clinical consensus regarding decision-making and expansion of psychological resources within adolescent bariatric surgery programs are discussed.

Strategies for Engineering and Rewiring Kinase Regulation.

Eukaryotic protein kinases (EPKs) catalyze the transfer of a phosphate group onto another protein in response to appropriate regulatory cues. In doing so, they provide a primary means for cellular information transfer. Consequently, EPKs play crucial roles in cell differentiation and cell-cycle progression, and kinase dysregulation is associated with numerous disease phenotypes including cancer. Nonnative cues for synthetically regulating kinases are thus much sought after, both for dissecting cell signaling pathways and for pharmaceutical development. In recent years advances in protein engineering and sequence analysis have led to new approaches for manipulating kinase activity, localization, and in some instances specificity. These tools have revealed fundamental principles of intracellular signaling and suggest paths forward for the design of therapeutic allosteric kinase regulators.

Trends in gabapentin and baclofen exposures reported to U.S. poison centers.

Context: Prescriptions for nonopioid pharmacological therapies such as gabapentin and baclofen have been increasing. While gabapentin and baclofen are less likely than opioids to result in fatal overdose, they are each associated with dependence, misuse and adverse effects.Objective: The objective of this study is to evaluate and describe trends in adult exposures to gabapentin and baclofen reported to U.S. Poison Centers.Methods: This was a retrospective review of data collected by U.S. Poison Centers and entered in the National Poison Data System. We identified all cases of exposures to gabapentin (2013-2017) and baclofen (2014-2017) in patients aged 18 years and over. We then analyzed demographics, common co-ingestions, medical outcomes, and geographic distribution.Results: During the five-year period (2013-2017), there were 74,175 gabapentin exposures. All gabapentin exposures increased by 72.3%; isolated exposures increased by 67.1%; and isolated abuse/misuse exposures increased by 119.9%. During the four-year period (2014-2017), there were 15,397 baclofen exposures. All baclofen exposures increased by 36.2%; isolated exposures increased by 35.0%; and isolated abuse/misuse exposures increased by 31.7%. Co-ingestions of sedatives and opioids were common for both medications. Admissions to a health care facility were required in 16.7% of isolated gabapentin exposures, and 52.1% of isolated baclofen exposures. Intentional suspected suicide attempts with isolated gabapentin exposures increased by 80.5% over a five-year period; and increased by 43% for isolated baclofen exposures over a four-year period. All states saw increases in gabapentin exposures and most states saw increases in baclofen exposures, gabapentin misuse/abuse, and baclofen misuse/abuse.Conclusion: Gabapentin and baclofen misuse, toxicity, use in suicide attempts, and associated healthcare utilization among adults in the United States have significantly increased since 2013. Careful consideration and risk-benefit analysis should be employed when prescribing these medications.