Hot spots for allosteric regulation on protein surfaces.

Recent work indicates a general architecture for proteins in which sparse networks of physically contiguous and coevolving amino acids underlie basic aspects of structure and function. These networks, termed sectors, are spatially organized such that active sites are linked to many surface sites distributed throughout the structure. Using the metabolic enzyme dihydrofolate reductase as a model system, we show that: (1) the sector is strongly correlated to a network of residues undergoing millisecond conformational fluctuations associated with enzyme catalysis, and (2) sector-connected surface sites are statistically preferred locations for the emergence of allosteric control in vivo. Thus, sectors represent an evolutionarily conserved "wiring" mechanism that can enable perturbations at specific surface positions to rapidly initiate conformational control over protein function. These findings suggest that sectors enable the evolution of intermolecular communication and regulation.

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.

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.

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.

High-Order Epistasis in Catalytic Power of Dihydrofolate Reductase Gives Rise to a Rugged Fitness Landscape in the Presence of Trimethoprim Selection.

Evolutionary fitness landscapes of several antibiotic target proteins have been comprehensively mapped showing strong high-order epistasis between mutations, but understanding these effects at the biochemical and structural levels remained open. Here, we carried out an extensive experimental and computational study to quantitatively understand the evolutionary dynamics of Escherichia coli dihydrofolate reductase (DHFR) enzyme in the presence of trimethoprim-induced selection. To facilitate this, we developed a new in vitro assay for rapidly characterizing DHFR steady-state kinetics. Biochemical and structural characterization of resistance-conferring mutations targeting a total of ten residues spanning the substrate binding pocket of DHFR revealed distinct changes in the catalytic efficiencies of mutated DHFR enzymes. Next, we measured biochemical parameters (Km, Ki, and kcat) for a mutant library carrying all possible combinations of six resistance-conferring DHFR mutations and quantified epistatic interactions between them. We found that the high-order epistasis in catalytic power of DHFR (kcat and Km) creates a rugged fitness landscape under trimethoprim selection. Taken together, our data provide a concrete illustration of how epistatic coupling at the level of biochemical parameters can give rise to complex fitness landscapes, and suggest new strategies for developing mutant specific inhibitors.

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.

Coping, Attributions, and Health Functioning Among Adolescents with Chronic Illness and Their Parents: Reciprocal Relations Over Time.

The purpose of the study was to identify bidirectional and longitudinal links between attributions, coping, and health functioning among adolescents with chronic illness and their parents. Religious/spiritual coping, attributional styles, and health functioning were assessed among adolescents with chronic illness at two time points approximately 21 months apart. Parental coping and attributions at both time points were also measured. Longitudinal links between variables were tested using an autoregressive cross-lagged path model; adolescent age and disease differences were evaluated via multigroup modeling. Poorer adolescent health functioning at baseline predicted higher use of parent optimistic attributional style at follow-up. Adolescent optimistic attributional style at baseline predicted more positive and less negative religious/spiritual coping at follow-up; adolescent negative religious/spiritual coping at baseline predicted more positive religious/spiritual coping at follow-up. Parent optimistic attributional style and positive religious/spiritual coping at baseline predicted the same constructs among adolescents at follow-up. With respect to age differences, parental negative religious/spiritual coping at baseline was associated with poorer health functioning among younger, but not older, adolescents at follow-up. There were no disease differences in the model. Important links were identified in this family-based model of coping, attributions, and health functioning. The results highlight specific targets for interventions to improve health functioning and coping among adolescents with chronic illness, including parental religious/spiritual coping and adolescent attributional style.

An evolution-based strategy for engineering allosteric regulation.

Allosteric regulation provides a way to control protein activity at the time scale of milliseconds to seconds inside the cell. An ability to engineer synthetic allosteric systems would be of practical utility for the development of novel biosensors, creation of synthetic cell signaling pathways, and design of small molecule pharmaceuticals with regulatory impact. To this end, we outline a general approach-termed rational engineering of allostery at conserved hotspots (REACH)-to introduce novel regulation into a protein of interest by exploiting latent allostery that has been hard-wired by evolution into its structure. REACH entails the use of statistical coupling analysis (SCA) to identify 'allosteric hotspots' on protein surfaces, the development and implementation of experimental assays to test hotspots for functionality, and a toolkit of allosteric modulators to impinge on endogenous cellular circuitry. REACH can be broadly applied to rewire cellular processes to respond to novel inputs.

shRNA library screening identifies nucleocytoplasmic transport as a mediator of BCR-ABL1 kinase-independent resistance.

The mechanisms underlying tyrosine kinase inhibitor (TKI) resistance in chronic myeloid leukemia (CML) patients lacking explanatory BCR-ABL1 kinase domain mutations are incompletely understood. To identify mechanisms of TKI resistance that are independent of BCR-ABL1 kinase activity, we introduced a lentiviral short hairpin RNA (shRNA) library targeting ∼5000 cell signaling genes into K562(R), a CML cell line with BCR-ABL1 kinase-independent TKI resistance expressing exclusively native BCR-ABL1. A customized algorithm identified genes whose shRNA-mediated knockdown markedly impaired growth of K562(R) cells compared with TKI-sensitive controls. Among the top candidates were 2 components of the nucleocytoplasmic transport complex, RAN and XPO1 (CRM1). shRNA-mediated RAN inhibition or treatment of cells with the XPO1 inhibitor, KPT-330 (Selinexor), increased the imatinib sensitivity of CML cell lines with kinase-independent TKI resistance. Inhibition of either RAN or XPO1 impaired colony formation of CD34(+) cells from newly diagnosed and TKI-resistant CML patients in the presence of imatinib, without effects on CD34(+) cells from normal cord blood or from a patient harboring the BCR-ABL1(T315I) mutant. These data implicate RAN in BCR-ABL1 kinase-independent imatinib resistance and show that shRNA library screens are useful to identify alternative pathways critical to drug resistance in CML.

Evolution-Based Functional Decomposition of Proteins.

The essential biological properties of proteins-folding, biochemical activities, and the capacity to adapt-arise from the global pattern of interactions between amino acid residues. The statistical coupling analysis (SCA) is an approach to defining this pattern that involves the study of amino acid coevolution in an ensemble of sequences comprising a protein family. This approach indicates a functional architecture within proteins in which the basic units are coupled networks of amino acids termed sectors. This evolution-based decomposition has potential for new understandings of the structural basis for protein function. To facilitate its usage, we present here the principles and practice of the SCA and introduce new methods for sector analysis in a python-based software package (pySCA). We show that the pattern of amino acid interactions within sectors is linked to the divergence of functional lineages in a multiple sequence alignment-a model for how sector properties might be differentially tuned in members of a protein family. This work provides new tools for studying proteins and for generally testing the concept of sectors as the principal units of function and adaptive variation.

Hot topics, urgent priorities, and ensuring success for racial/ethnic minority young investigators in academic pediatrics.

BACKGROUND: The number of racial/ethnic minority children will exceed the number of white children in the USA by 2018. Although 38% of Americans are minorities, only 12% of pediatricians, 5% of medical-school faculty, and 3% of medical-school professors are minorities. Furthermore, only 5% of all R01 applications for National Institutes of Health grants are from African-American, Latino, and American Indian investigators. Prompted by the persistent lack of diversity in the pediatric and biomedical research workforces, the Academic Pediatric Association Research in Academic Pediatrics Initiative on Diversity (RAPID) was initiated in 2012. RAPID targets applicants who are members of an underrepresented minority group (URM), disabled, or from a socially, culturally, economically, or educationally disadvantaged background. The program, which consists of both a research project and career and leadership development activities, includes an annual career-development and leadership conference which is open to any resident, fellow, or junior faculty member from an URM, disabled, or disadvantaged background who is interested in a career in academic general pediatrics. METHODS: As part of the annual RAPID conference, a Hot Topic Session is held in which the young investigators spend several hours developing a list of hot topics on the most useful faculty and career-development issues. These hot topics are then posed in the form of six "burning questions" to the RAPID National Advisory Committee (comprised of accomplished, nationally recognized senior investigators who are seasoned mentors), the RAPID Director and Co-Director, and the keynote speaker. RESULTS/CONCLUSIONS: The six compelling questions posed by the 10 young investigators-along with the responses of the senior conference leadership-provide a unique resource and "survival guide" for ensuring the academic success and optimal career development of young investigators in academic pediatrics from diverse backgrounds. A rich conversation ensued on the topics addressed, consisting of negotiating for protected research time, career trajectories as academic institutions move away from an emphasis on tenure-track positions, how "non-academic" products fit into career development, racism and discrimination in academic medicine and how to address them, coping with isolation as a minority faculty member, and how best to mentor the next generation of academic physicians.

Melting of Duplex DNA in the Absence of ATP by the NS3 Helicase Domain through Specific Interaction with a Single-Strand/Double-Strand Junction.

Helicases unwind double-stranded nucleic acids, remove secondary structures from single-stranded nucleic acids, and remove proteins bound to nucleic acids. For many helicases, the mechanisms for these different functions share the ability to translocate with a directional bias as a result of ATP binding and hydrolysis. Nonstructural protein 3 (NS3) is an essential enzyme expressed by the hepatitis C virus (HCV) and is known to catalyze the unwinding of both DNA and RNA substrates in a 3'-to-5' direction. We investigated the role of nucleic acid binding in the unwinding mechanism by examining ATP-independent unwinding. We observed that even in the absence of ATP, the NS3 helicase domain (NS3h) unwound duplexes only when they contained a 3'-tail (i.e., 3'-to-5' directionality). Blunt-ended duplexes and 5'-tailed duplexes were not melted even in the presence of a large excess concentration of the protein. NS3h was found to diffuse rapidly along single-stranded DNA at a rate of 30 nucleotides(2) s(-1). Upon encountering an appropriate single-strand/double-strand (ss/ds) junction, NS3h slowly melted the duplex under conditions with an excess protein concentration relative to DNA concentration. When a biotin-streptavidin block was placed into the ssDNA region, no melting of DNA was observed, suggesting that NS3h must diffuse along the ssDNA, and that the streptavidin blocked the diffusion. We conclude that the specific interaction between NS3h and the ss/dsDNA junction, coupled with diffusion, allows binding energy to melt duplex DNA with a directional bias. Alternatively, we found that the full-length NS3 protein did not exhibit strict directionality and was dependent on duplex DNA length. NS3 was able to unwind the duplex even in the presence of the biotin-streptavidin block. We propose a noncanonical model of unwinding for NS3 in which the enzyme binds directly to the duplex via protein-protein interactions to melt the substrate.

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.

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.

Effect of computer-assisted interviewing on self-reported sexual behavior data in a microbicide clinical trial.

In a microbicide safety and effectiveness trial (HPTN 035) in Malawi, 585 women completed the same questionnaire through a face-to-face interview (FTFI) and an audio computer-assisted self-interview (ACASI). Concordance between FTFI and ACASI responses ranged from 72.0 % for frequency of sex in the past week to 95.2 % for anal intercourse (AI) in the past 3 months. Reported gel and condom use at last sex act were marginally lower with ACASI than FTFI (73.5 % vs. 77.2 %, p = 0.11 and 60.9 % vs. 65.5 %, p = 0.05, respectively). More women reported AI with ACASI than FTFI (5.0 % vs. 0.2 %, p < 0.001). Analyses of consistency of responses within ACASI revealed that 15.0 % of participants in the condom-only arm and 28.7 % in the gel arm provided at least one discrepant answer regarding total sex acts and sex acts where condom and gel were used (19.2 % reported one inconsistent answer, 8.1 % reported two inconsistent answers, and 1.4 % reported three inconsistent answers). While ACASI may provide more accurate assessments of sensitive behaviors in HIV prevention trials, it also results in a high level of internally inconsistent responses.

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.

Binding by the hepatitis C virus NS3 helicase partially melts duplex DNA.

Binding of NS3 helicase to DNA was investigated by footprinting with KMnO(4), which reacts preferentially with thymidine residues in single-stranded DNA (ssDNA) compared to those in double-stranded DNA (dsDNA). A distinct pattern of reactivity was observed on ssDNA, which repeated every 8 nucleotides (nt) and is consistent with the known binding site size of NS3. Binding to a DNA substrate containing a partial duplex was also investigated. The DNA contained a 15 nt overhang made entirely of thymidine residues adjacent to a 22 bp duplex that contained thymidine at every other position. Surprisingly, the KMnO(4) reactivity pattern extended from the ssDNA into the dsDNA region of the substrate. Lengthening the partial duplex to 30 bp revealed a similar pattern extending from the ssDNA into the dsDNA, indicating that NS3 binds within the duplex region. Increasing the length of the ssDNA portion of the partial duplex by 4 nt resulted in a shift in the footprinting pattern for the ssDNA by 4 nt, which is consistent with binding to the 3'-end of the ssDNA. However, the footprinting pattern in the dsDNA region was shifted by only 1-2 bp, indicating that binding to the ssDNA-dsDNA region was preferred. Footprinting performed as a function of time indicated that NS3 binds to the ssDNA rapidly, followed by slower binding to the duplex. Hence, multiple molecules of NS3 can bind along a ssDNA-dsDNA partial duplex by interacting with the ssDNA as well as the duplex DNA.

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.