Metamorphic proteins and how to find them.

In the last two decades, our existing notion that most foldable proteins have a unique native state has been challenged by the discovery of metamorphic proteins, which reversibly interconvert between multiple, sometimes highly dissimilar, native states. As the number of known metamorphic proteins increases, several computational and experimental strategies have emerged for gaining insights about their refolding processes and identifying unknown metamorphic proteins amongst the known proteome. In this review, we describe the current advances in biophysically and functionally ascertaining the structural interconversions of metamorphic proteins and how coevolution can be harnessed to identify novel metamorphic proteins from sequence information. We also discuss the challenges and ongoing efforts in using artificial intelligence-based protein structure prediction methods to discover metamorphic proteins and predict their corresponding three-dimensional structures.

Isolation of feline islets of Langerhans by selective osmotic shock produces glucose responsive islets.

Introduction: Pancreatic islet isolation is essential for studying islet physiology, pathology, and transplantation, and feline islets could be an important model for human type II diabetes mellitus (T2D). Traditional isolation methods utilizing collagenases inflict damage and, in cats, may contribute to the difficulty in generating functional islets, as demonstrated by glucose-stimulated insulin secretion (GSIS). GLUT2 expression in ß cells may allow for adaptation to hyperosmolar glucose solutions while exocrine tissue is selectively disrupted. Methods: Here we developed a protocol for selective osmotic shock (SOS) for feline islet isolation and evaluated the effect of different hyperosmolar glucose concentrations (300 mmol/L and 600 mmol/L) and incubation times (20 min and 40 min) on purity, morphology, yield, and GSIS. Results: Across protocol treatments, islet yield was moderate and morphology excellent. The treatment of 600 mmol/L glucose solution with 20 min incubation resulted in the highest stimulation index by GSIS. Discussion: Glucose responsiveness was demonstrated, permitting future in vitro studies. This research opens avenues for understanding feline islet function and transplantation possibilities and enables an additional islet model for T2D.

Early Correlates of School Readiness Before and During the COVID-19 Pandemic Linking Health and School Data.

Importance: Many known correlates of kindergarten readiness are captured in developmental and social screenings in primary care; little is known about how primary care data predicts school readiness. Objective: To identify early Kindergarten Readiness Assessment (KRA) correlates by linking electronic health record (EHR) data with school district KRA data and to examine potential outcomes of the COVID-19 pandemic using KRA scores between 2018 and 2021. Design, Setting, and Participants: This was a retrospective cohort study linking a large primary care practice (PCP) with school assessment data. Linkage used patient name, date of birth, and address. The setting was an urban school district and PCP affiliated with an academic medical center. Students had a KRA score from fall of 2018, 2019, or 2021 (no 2020 KRA due to the COVID-19 pandemic) and at least 1 prior well-child visit at the PCP. Exposures: Exposures included year KRA administered, reported child race and ethnicity, child sex, interpreter for medical visits, child ever failed Ages & Stages Questionnaire (ASQ) 18 to 54 months, ever rarely read to, Medicaid status, food insecurity, housing insecurity, problems with benefits, and caregiver depressive symptoms. Main Outcomes and Measures: KRA score (continuous), with a possible range of 0 to 300 (passing score = 270). Results: A total of 3204 PCP patients (mean [SD] age, 67 [4] months; 1612 male [50.3%]; 2642 Black [82.5%]; 94 Hispanic [2.9%]; 244 White [7.6%]) were matched to their KRA score. Mean (SD) KRA scores were significantly lower in 2021 (mean [SD], 260.0 [13.0]; 214 of 998 [21.4%]) compared with 2019 (mean [SD], 262.7 [13.5]; 317 of 1114 [28.5%]) and 2018 (mean [SD], 263.5 [13.6]; 351 of 1092 [32.1%]), a pattern mirrored in the larger school district. In the linear regression final model (n = 2883), the following binary variables significantly lowered the child's KRA score (points lowered [95% CI]) below a mean passing score of 270.8: child ever failed ASQ after 18 months (-6.7; 95% CI, -7.7 to -5.6), Medicaid insured (-5.7; 95% CI, -9.0 to -2.3), Hispanic ethnicity (-3.8; 95% CI, -6.9 to -0.6), requires interpreter (-3.6; 95% CI, -7.1 to -0.1), 2021 year (-3.5; 95% CI, -4.7 to -2.3), male sex (-2.7; 95% CI, -3.7 to -1.8), ever rarely read to (-1.5; 95% CI, -2.6 to -0.4), and food insecurity (-1.2; 95% CI, -2.4 to -0.1). Race, caregiver depression, housing insecurity, and problems receiving benefits were not associated with KRA scores in final model. Conclusions and Relevance: Findings of this cohort study suggest a deleterious association of the COVID-19 pandemic with early learning and development. There may be potential for PCPs and school districts to collaborate to identify and mitigate risks much earlier.

Sequence clustering confounds AlphaFold2.

Though typically associated with a single folded state, some globular proteins remodel their secondary and/or tertiary structures in response to cellular stimuli. AlphaFold21 (AF2) readily generates one dominant protein structure for these fold-switching (a.k.a. metamorphic) proteins2, but it often fails to predict their alternative experimentally observed structures3,4. Wayment-Steele, et al. steered AF2 to predict alternative structures of a few metamorphic proteins using a method they call AF-cluster5. However, their Paper lacks some essential controls needed to assess AF-cluster's reliability. We find that these controls show AF-cluster to be a poor predictor of metamorphic proteins. First, closer examination of the Paper's results reveals that random sequence sampling outperforms sequence clustering, challenging the claim that AF-cluster works by "deconvolving conflicting sets of couplings." Further, we observe that AF-cluster mistakes some single-folding KaiB homologs for fold switchers, a critical flaw bound to mislead users. Finally, proper error analysis reveals that AF-cluster predicts many correct structures with low confidence and some experimentally unobserved conformations with confidences similar to experimentally observed ones. For these reasons, we suggest using ColabFold6-based random sequence sampling7-augmented by other predictive approaches-as a more accurate and less computationally intense alternative to AF-cluster.

ColabFold predicts alternative protein structures from single sequences, coevolution unnecessary for AF-cluster.

Though typically associated with a single folded state, globular proteins are dynamic and often assume alternative or transient structures important for their functions1,2. Wayment-Steele, et al. steered ColabFold3 to predict alternative structures of several proteins using a method they call AF-cluster4. They propose that AF-cluster "enables ColabFold to sample alternate states of known metamorphic proteins with high confidence" by first clustering multiple sequence alignments (MSAs) in a way that "deconvolves" coevolutionary information specific to different conformations and then using these clusters as input for ColabFold. Contrary to this Coevolution Assumption, clustered MSAs are not needed to make these predictions. Rather, these alternative structures can be predicted from single sequences and/or sequence similarity, indicating that coevolutionary information is unnecessary for predictive success and may not be used at all. These results suggest that AF-cluster's predictive scope is likely limited to sequences with distinct-yet-homologous structures within ColabFold's training set.

SSDraw: Software for generating comparative protein secondary structure diagrams.

The program SSDraw generates publication-quality protein secondary structure diagrams from three-dimensional protein structures. To depict relationships between secondary structure and other protein features, diagrams can be colored by conservation score, B-factor, or custom scoring. Diagrams of homologous proteins can be registered according to an input multiple sequence alignment. Linear visualization allows the user to stack registered diagrams, facilitating comparison of secondary structure and other properties among homologous proteins. SSDraw can be used to compare secondary structures of homologous proteins with both conserved and divergent folds. It can also generate one secondary structure diagram from an input protein structure of interest. The source code can be downloaded (https://github.com/ncbi/SSDraw) and run locally for rapid structure generation, while a Google Colab notebook allows easy use.

SSDraw: software for generating comparative protein secondary structure diagrams.

The program SSDraw generates publication-quality protein secondary structure diagrams from three-dimensional protein structures. To depict relationships between secondary structure and other protein features, diagrams can be colored by conservation score, B-factor, or custom scoring. Diagrams of homologous proteins can be registered according to an input multiple sequence alignment. Linear visualization allows the user to stack registered diagrams, facilitating comparison of secondary structure and other properties among homologous proteins. SSDraw can be used to compare secondary structures of homologous proteins with both conserved and divergent folds. It can also generate one secondary structure diagram from an input protein structure of interest. The source code can be downloaded (https://github.com/ethanchen1301/SSDraw) and run locally for rapid structure generation, while a Google Colab notebook allows easy use.

Evolutionary selection of proteins with two folds.

Although most globular proteins fold into a single stable structure, an increasing number have been shown to remodel their secondary and tertiary structures in response to cellular stimuli. State-of-the-art algorithms predict that these fold-switching proteins adopt only one stable structure, missing their functionally critical alternative folds. Why these algorithms predict a single fold is unclear, but all of them infer protein structure from coevolved amino acid pairs. Here, we hypothesize that coevolutionary signatures are being missed. Suspecting that single-fold variants could be masking these signatures, we developed an approach, called Alternative Contact Enhancement (ACE), to search both highly diverse protein superfamilies-composed of single-fold and fold-switching variants-and protein subfamilies with more fold-switching variants. ACE successfully revealed coevolution of amino acid pairs uniquely corresponding to both conformations of 56/56 fold-switching proteins from distinct families. Then, we used ACE-derived contacts to (1) predict two experimentally consistent conformations of a candidate protein with unsolved structure and (2) develop a blind prediction pipeline for fold-switching proteins. The discovery of widespread dual-fold coevolution indicates that fold-switching sequences have been preserved by natural selection, implying that their functionalities provide evolutionary advantage and paving the way for predictions of diverse protein structures from single sequences.

Fluid protein fold space and its implications.

Fold-switching proteins, which remodel their secondary and tertiary structures in response to cellular stimuli, suggest a new view of protein fold space. For decades, experimental evidence has indicated that protein fold space is discrete: dissimilar folds are encoded by dissimilar amino acid sequences. Challenging this assumption, fold-switching proteins interconnect discrete groups of dissimilar protein folds, making protein fold space fluid. Three recent observations support the concept of fluid fold space: (1) some amino acid sequences interconvert between folds with distinct secondary structures, (2) some naturally occurring sequences have switched folds by stepwise mutation, and (3) fold switching is evolutionarily selected and likely confers advantage. These observations indicate that minor amino acid sequence modifications can transform protein structure and function. Consequently, proteomic structural and functional diversity may be expanded by alternative splicing, small nucleotide polymorphisms, post-translational modifications, and modified translation rates.

Identification of a covert evolutionary pathway between two protein folds.

Although homologous protein sequences are expected to adopt similar structures, some amino acid substitutions can interconvert α-helices and ß-sheets. Such fold switching may have occurred over evolutionary history, but supporting evidence has been limited by the: (1) abundance and diversity of sequenced genes, (2) quantity of experimentally determined protein structures, and (3) assumptions underlying the statistical methods used to infer homology. Here, we overcome these barriers by applying multiple statistical methods to a family of ~600,000 bacterial response regulator proteins. We find that their homologous DNA-binding subunits assume divergent structures: helix-turn-helix versus α-helix + ß-sheet (winged helix). Phylogenetic analyses, ancestral sequence reconstruction, and AlphaFold2 models indicate that amino acid substitutions facilitated a switch from helix-turn-helix into winged helix. This structural transformation likely expanded DNA-binding specificity. Our approach uncovers an evolutionary pathway between two protein folds and provides a methodology to identify secondary structure switching in other protein families.

Previous Incarceration, Health Insurance, and the Affordable Care Act in the U.S.

INTRODUCTION: This study examines the association between prior incarceration and health insurance status and whether living in a state adopting the Affordable Care Act (ACA) Medicaid expansion moderates this relationship. METHODS: Data are from the National Longitudinal Study of Adolescent to Adult Health (Wave I [1993-1994], Wave IV [2008], and Wave V [2016-2018]; N=8,965). Multiple logistic regression with multiplicative interaction terms were performed to assess the relationship between previous incarceration and ACA Medicaid expansion on (1) being insured and (2) being on public health insurance. Analyses were performed in 2023. RESULTS: Findings demonstrate a positive and statistically significant interaction in the association between previous incarceration and living in a state with ACA Medicaid expansion on having public health insurance (OR=2.402; 95% CI=1.257, 4.588). CONCLUSIONS: The ACA Medicaid expansion was associated with a greater likelihood of public health insurance coverage for formerly incarcerated persons in the U.S. These findings suggest that Medicaid expansion could be critical in improving health insurance coverage among formerly incarcerated individuals who are a population that is more likely to be uninsured.

Tales of the unexpected.

A single event can completely change the direction of a career in science; four researchers share their stories.

Evolutionary selection of proteins with two folds.

Although most globular proteins fold into a single stable structure 1 , an increasing number have been shown to remodel their secondary and tertiary structures in response to cellular stimuli 2 . State-of-the-art algorithms 3-5 predict that these fold-switching proteins assume only one stable structure 6,7 , missing their functionally critical alternative folds. Why these algorithms predict a single fold is unclear, but all of them infer protein structure from coevolved amino acid pairs. Here, we hypothesize that coevolutionary signatures are being missed. Suspecting that over-represented single-fold sequences may be masking these signatures, we developed an approach to search both highly diverse protein superfamilies-composed of single-fold and fold-switching variants-and protein subfamilies with more fold-switching variants. This approach successfully revealed coevolution of amino acid pairs uniquely corresponding to both conformations of 56/58 fold-switching proteins from distinct families. Then, using a set of coevolved amino acid pairs predicted by our approach, we successfully biased AlphaFold2 5 to predict two experimentally consistent conformations of a candidate protein with unsolved structure. The discovery of widespread dual-fold coevolution indicates that fold-switching sequences have been preserved by natural selection, implying that their functionalities provide evolutionary advantage and paving the way for predictions of diverse protein structures from single sequences.

Distinguishing features of fold-switching proteins.

Though many folded proteins assume one stable structure that performs one function, a small-but-increasing number remodel their secondary and tertiary structures and change their functions in response to cellular stimuli. These fold-switching proteins regulate biological processes and are associated with autoimmune dysfunction, severe acute respiratory syndrome coronavirus-2 infection, and more. Despite their biological importance, it is difficult to computationally predict fold switching. With the aim of advancing computational prediction and experimental characterization of fold switchers, this review discusses several features that distinguish fold-switching proteins from their single-fold and intrinsically disordered counterparts. First, the isolated structures of fold switchers are less stable and more heterogeneous than single folders but more stable and less heterogeneous than intrinsically disordered proteins (IDPs). Second, the sequences of single fold, fold switching, and intrinsically disordered proteins can evolve at distinct rates. Third, proteins from these three classes are best predicted using different computational techniques. Finally, late-breaking results suggest that single folders, fold switchers, and IDPs have distinct patterns of residue-residue coevolution. The review closes by discussing high-throughput and medium-throughput experimental approaches that might be used to identify new fold-switching proteins.

"I got so much on my plate": Understanding care discontinuity for HIV and HCV among formerly incarcerated persons.

OBJECTIVE: To explore barriers to care continuity among formerly incarcerated persons with HIV and/or hepatitis C. DATA SOURCES AND STUDY SETTING: We draw on data from semi-structured interviews conducted in 2018-2019 with 30 formerly incarcerated persons and 10 care providers. Data were collected across two clinics in Baltimore, Maryland, and Washington, D.C. STUDY DESIGN: We recruited participants using a combination of nonprobability sampling techniques. Participants completed closed-ended questionnaires and took part in semi-structured interviews related to treatment barriers and incentives. DATA COLLECTION/EXTRACTION METHODS: Interviews were transcribed using Express Scribe software and transcriptions were open coded using NVivo 12 software. An iterative process was used to relate and build upon emergent themes in interviews. PRINCIPAL FINDINGS: Our study illuminates both internal and external barriers to care continuity. The most common external barriers were system navigation and housing instability. Internal barriers consisted of overlapping issues related to mental health, substance use, and feelings of shame and/or denial. CONCLUSION: An overarching theme is that formerly incarcerated persons with HIV and/or HCV are grappling with numerous challenges that can threaten their health and health care. These barriers are cumulative, intersecting, and reciprocal.

AlphaFold2 has more to learn about protein energy landscapes.

Recent work suggests that AlphaFold2 (AF2)-a deep learning-based model that can accurately infer protein structure from sequence-may discern important features of folded protein energy landscapes, defined by the diversity and frequency of different conformations in the folded state. Here, we test the limits of its predictive power on fold-switching proteins, which assume two structures with regions of distinct secondary and/or tertiary structure. Using several implementations of AF2, including two published enhanced sampling approaches, we generated >280,000 models of 93 fold-switching proteins whose experimentally determined conformations were likely in AF2's training set. Combining all models, AF2 predicted fold switching with a modest success rate of ~25%, indicating that it does not readily sample both experimentally characterized conformations of most fold switchers. Further, AF2's confidence metrics selected against models consistent with experimentally determined fold-switching conformations in favor of inconsistent models. Accordingly, these confidence metrics-though suggested to evaluate protein energetics reliably-did not discriminate between low and high energy states of fold-switching proteins. We then evaluated AF2's performance on seven fold-switching proteins outside of its training set, generating >159,000 models in total. Fold switching was accurately predicted in one of seven targets with moderate confidence. Further, AF2 demonstrated no ability to predict alternative conformations of two newly discovered targets without homologs in the set of 93 fold switchers. These results indicate that AF2 has more to learn about the underlying energetics of protein ensembles and highlight the need for further developments of methods that readily predict multiple protein conformations.

Using Wearable Cameras to Investigate Health-Related Daily Life Experiences: A Literature Review of Precautions and Risks in Empirical Studies.

Automated, wearable cameras can benefit health-related research by capturing accurate and objective information about individuals' daily experiences. However, wearable cameras present unique privacy- and confidentiality-related risks due to the possibility of the images capturing identifying or sensitive information from participants and third parties. Although best practice guidelines for ethical research with wearable cameras have been published, limited information exists on the risks of studies using wearable cameras. The aim of this literature review was to survey risks related to using wearable cameras, and precautions taken to reduce those risks, as reported in empirical research. Forty-five publications, comprising 36 independent studies, were reviewed, and findings revealed that participants' primary concerns with using wearable cameras included physical inconvenience and discomfort in certain situations (e.g., public settings). None of the studies reviewed reported any serious adverse events. Although it is possible that reported findings do not include all risks experienced by participants in research with wearable cameras, our findings suggest a low level of risk to participants. However, it is important that investigators adopt recommended precautions, which can promote autonomy and reduce risks, including participant discomfort.

Many dissimilar NusG protein domains switch between α-helix and ß-sheet folds.

Folded proteins are assumed to be built upon fixed scaffolds of secondary structure, α-helices and ß-sheets. Experimentally determined structures of >58,000 non-redundant proteins support this assumption, though it has recently been challenged by ~100 fold-switching proteins. Though ostensibly rare, these proteins raise the question of how many uncharacterized proteins have shapeshifting-rather than fixed-secondary structures. Here, we use a comparative sequence-based approach to predict fold switching in the universally conserved NusG transcription factor family, one member of which has a 50-residue regulatory subunit experimentally shown to switch between α-helical and ß-sheet folds. Our approach predicts that 24% of sequences in this family undergo similar α-helix ⇌ ß-sheet transitions. While these predictions cannot be reproduced by other state-of-the-art computational methods, they are confirmed by circular dichroism and nuclear magnetic resonance spectroscopy for 10 out of 10 sequence-diverse variants. This work suggests that fold switching may be a pervasive mechanism of transcriptional regulation in all kingdoms of life.

Measuring Ostracism-Induced Changes in Consumption of Palatable Food: Feasibility of a Novel Behavioral Task.

Purpose: Ostracism is a highly aversive interpersonal experience. Previous research suggests that it can increase consumption of highly palatable food in some individuals, but decrease it in others. Thus, we developed the Cyberball-Milkshake Task (CMT), to facilitate research investigating individual differences in ostracism's effects on consumption of highly palatable food. We present data on feasibility for the CMT in a sample of young adult women. Materials and Methods: Participants were 22 women, 18-30 years old, reporting very low or very high levels of emotional eating at screening. Participants performed the CMT, which consisted of 12 trials. Each trial included: playing a round of Cyberball (a computerized game of catch with fictitious "other participants" programmed to either include or exclude the participant); viewing a chocolate image; and then consuming a participant-determined amount of milkshake. Participants subsequently played an additional inclusion and exclusion round of Cyberball, each immediately followed by questionnaires assessing current mood and recent Cyberball experience. Results: Cyberball exclusion (vs. inclusion) was associated with large, significant increases in reported ostracism and threats to self-esteem; exclusion's effects on affect were in the expected direction (e.g., increased negative affect), but generally small and non-significant. Milkshake intake was measurable for 95% of participants, on 96% of trials. Intake decreased quadratically across trials, with a steep negative slope for low trial numbers that decreased to the point of being flat for the highest trial numbers. Discussion: The CMT is a generally feasible approach to investigating ostracism's effects on consumption of highly palatable food. The feasibility (and validity) of the CMT may benefit from modification (e.g., fewer trials and longer rounds of Cyberball). Future research should examine whether performance on a modified version of the CMT predicts real-world behavior in a larger sample.

Case Report: Septic Pericarditis With Achromobacter xyloxidans in an Immunosuppressed Dog.

A 5-year-old female spayed French Bulldog presented for anorexia and increased respiratory rate. On presentation, she was dyspneic with stridor and increased bronchovesicular sounds. Point-of-care ultrasound identified pericardial effusion. Thoracic radiographs identified pleural effusion, a wide cranial mediastinum, and multifocal unstructured interstitial pulmonary opacities. Bloodwork revealed a moderate leukocytosis characterized by a mature neutrophilia with a left shift, hypoalbuminemia, mildly increased alkaline phosphatase activity, and moderate hypokalemia. Thoracic CT findings revealed moderate pericardial and bilateral pleural effusion, mediastinal effusion, and moderate cranial mediastinal lymphadenopathy. Diagnostic thoracocentesis and pericardiocentesis revealed septic exudates with bacilli. Two days later, a median sternotomy and pericardiectomy were performed. Aerobic cultures of the effusions grew Achromobacter xylosoxidans ss deitrificans. The patient was treated with Amoxicillin-clavulanate and enrofloxacin for 12 weeks and clinically fully recovered. Achromobacter xylosoxidans has not been reported as a cause of purulent pericarditis and pyothorax in a dog. Uniquely, this patient is suspected of developing this infection secondary to immunosuppression.