Site-specific immobilization of the endosialidase reveals QSOX2 is a novel polysialylated protein.

Polysialic acid (polySia) is a linear polymer of α2,8-linked sialic acid residues that is of fundamental biological interest due to its pivotal roles in the regulation of the nervous, immune, and reproductive systems in healthy human adults. PolySia is also dysregulated in several chronic diseases, including cancers and mental health disorders. However, the mechanisms underpinning polySia biology in health and disease remain largely unknown. The polySia-specific hydrolase, endoneuraminidase NF (EndoN), and the catalytically inactive polySia lectin EndoNDM, have been extensively used for studying polySia. However, EndoN is heat stable and remains associated with cells after washing. When studying polySia in systems with multiple polysialylated species, the residual EndoN that cannot be removed confounds data interpretation. We developed a strategy for site-specific immobilization of EndoN on streptavidin-coated magnetic beads. We showed that immobilizing EndoN allows for effective removal of the enzyme from samples, while retaining hydrolase activity. We used the same strategy to immobilize the polySia lectin EndoNDM, which enabled the enrichment of polysialylated proteins from complex mixtures such as serum for their identification via mass spectrometry. We used this methodology to identify a novel polysialylated protein, QSOX2, which is secreted from the breast cancer cell line MCF-7. This method of site-specific immobilization can be utilized for other enzymes and lectins to yield insight into glycobiology.

Longevity of dental restorations in Sjogren's disease patients using electronic dental and health record data.

BACKGROUND: Decreased salivary secretion is not only a risk factor for carious lesions in Sjögren's disease (SD) but also an indicator of deterioration of teeth with every restorative replacement. This study determined the longevity of direct dental restorations placed in patients with SD using matched electronic dental record (EDR) and electronic health record (EHR) data. METHODS: We conducted a retrospective cohort study using EDR and EHR data of Indiana University School of Dentistry patients who have a SD diagnosis in their EHR. Treatment history of patients during 15 years with SD (cases) and their matched controls with at least one direct dental restoration were retrieved from the EDR. Descriptive statistics summarized the study population characteristics. Cox regression models with random effects analyzed differences between cases and controls for time to direct restoration failure. Further the model explored the effect of covariates such as age, sex, race, dental insurance, medical insurance, medical diagnosis, medication use, preventive dental visits per year, and the number of tooth surfaces on time to restoration failure. RESULTS: At least one completed direct restoration was present for 102 cases and 42 controls resulting in a cohort of 144 patients' EDR and EHR data. The cases were distributed as 21 positives, 57 negatives, and 24 uncertain cases based on clinical findings. The average age was 56, about 93% were females, 54% were White, 74% had no dental insurance, 61% had public medical insurance, < 1 preventive dental visit per year, 94% used medications and 93% had a medical diagnosis that potentially causes dry mouth within the overall study cohort. About 529 direct dental restorations were present in cases with SD and 140 restorations in corresponding controls. Hazard ratios of 2.99 (1.48-6.03; p = 0.002) and 3.30 (1.49-7.31, p-value: 0.003) showed significantly decreased time to restoration failure among cases and positive for SD cases compared to controls, respectively. Except for the number of tooth surfaces, no other covariates had a significant influence on the survival time. CONCLUSION: Considering the rapid failure of dental restorations, appropriate post-treatment assessment, management, and evaluation should be implemented while planning restorative dental procedures among cases with SD. Since survival time is decreased with an increase in the number of surfaces, guidelines for restorative procedures should be formulated specifically for patients with SD.

Feasibility of Utilizing Electronic Dental Record Data and Periodontitis Case Definition to Automate Diagnosis.

Periodontitis is an irreversible disease leading to tooth loss, and 42% U.S. population suffers from periodontitis. Hence, diagnosing, monitoring, and determining its prevalence is critical to develop preventive strategies. However, a nationwide epidemiological study estimating the prevalence reported a concern about the discontinuation of such studies due to cost and ethical reasons. Therefore, this study determined the feasibility of utilizing electronic dental record (EDR) data and periodontitis case definition to automate periodontitis diagnosis. We utilized EDR data from the Indiana University School of Dentistry of 28,908 unique patients. We developed and tested a computer algorithm to diagnose periodontitis using the case definition. We found 44%, 22%, and 1% of patients with moderate, severe, and mild periodontitis, respectively. The algorithm worked with 100% sensitivity, specificity, and accuracy because of the excellent quality of the EDR data. We concluded the feasibility of providing automated periodontitis diagnosis from EDR data to conduct epidemiological studies across the US.

Comparing gingivitis diagnoses by bleeding on probing (BOP) exclusively versus BOP combined with visual signs using large electronic dental records.

The major significance of the 2018 gingivitis classification criteria is utilizing a simple, objective, and reliable clinical sign, bleeding on probing score (BOP%), to diagnose gingivitis. However, studies report variations in gingivitis diagnoses with the potential to under- or over-estimating disease occurrence. This study determined the agreement between gingivitis diagnoses generated using the 2018 criteria (BOP%) versus diagnoses using BOP% and other gingival visual assessments. We conducted a retrospective study of 28,908 patients' electronic dental records (EDR) from January-2009 to December-2014, at the Indiana University School of Dentistry. Computational and natural language processing (NLP) approaches were developed to diagnose gingivitis cases from BOP% and retrieve diagnoses from clinical notes. Subsequently, we determined the agreement between BOP%-generated diagnoses and clinician-recorded diagnoses. A thirty-four percent agreement was present between BOP%-generated diagnoses and clinician-recorded diagnoses for disease status (no gingivitis/gingivitis) and a 9% agreement for the disease extent (localized/generalized gingivitis). The computational program and NLP performed excellently with 99.5% and 98% f-1 measures, respectively. Sixty-six percent of patients diagnosed with gingivitis were reclassified as having healthy gingiva based on the 2018 diagnostic classification. The results indicate potential challenges with clinicians adopting the new diagnostic criterion as they transition to using the BOP% alone and not considering the visual signs of inflammation. Periodic training and calibration could facilitate clinicians' and researchers' adoption of the 2018 diagnostic system. The informatics approaches developed could be utilized to automate diagnostic findings from EDR charting and clinical notes.

The cancer-associated glycan polysialic acid is dysregulated in systemic sclerosis and is associated with fibrosis.

OBJECTIVE: Systemic sclerosis (SSc) is a rare but deadly disease characterized by autoimmunity, vasculopathy, and fibrosis. Fibrotic complications associated with SSc correlate with severe morbidity and mortality. Previous studies in SSc have identified fibroblasts as the primary drivers of fibrosis; however, the mechanism(s) promoting this are not well understood. Aberrant glycosylation, particularly polysialylation (polySia), has been described as a prominent feature of aggressive cancers. Inspired by this observation, we aimed to determine if polySia is dysregulated in various forms of SSc. METHODS: All patients with SSc met the 2013 ACR/EULAR. Patients were sub-classified into limited cutaneous (lSSc, N = 5 or 46 patients for polySia quantification in the dermis or serum; respectively), diffuse cutaneous (dSSc, N = 11 or 18 patients for polySia quantification in the dermis or serum; respectively), or patients with dSSc treated with an autologous stem cell transplantation (post-ASCT, N = 4 patients for quantification in the dermis). Dermal polySia levels were measured via immunofluorescence microscopy in 10 µm dermal sections, quantified in each group (healthy volunteers (HC), lSSc, dSSc, and post-ASCT) and correlated with skin fibrosis (via the modified Rodnan skin score (mRSS)). Similarly, serum polySia was quantified in each group, and correlated with the mRSS. RESULTS: Dermal polySia levels were highest in patients with dSSc (compared to HC < 0.001), and correlated with the degree of fibrosis in all of the groups (P = 0.008). Serum polySia was higher in all SSc groups (p < 0.001) and correlated with the severity of mRSS (p < 0.0001). CONCLUSION: Polysia is more abundant in the skin and sera from patients with SSc and correlates with the degree of skin fibrosis. The aberrant expression of polySia highlights its potential use as a biomarker in patients with progressive forms of SSc. Dysregulated polySia levels in SSc further emphasizes the cancer-like phenotype present in SSc, which may promote fibrosis and immune dysregulation.

Metabolomic rearrangement controls the intrinsic microbial response to temperature changes.

Temperature is one of the key determinants of microbial behavior and survival, whose impact is typically studied under heat- or cold-shock conditions that elicit specific regulation to combat lethal stress. At intermediate temperatures, cellular growth rate varies according to the Arrhenius law of thermodynamics without stress responses, a behavior whose origins have not yet been elucidated. Using single-cell microscopy during temperature perturbations, we show that bacteria exhibit a highly conserved, gradual response to temperature upshifts with a time scale of ~1.5 doublings at the higher temperature, regardless of initial/final temperature or nutrient source. We find that this behavior is coupled to a temperature memory, which we rule out as being neither transcriptional, translational, nor membrane dependent. Instead, we demonstrate that an autocatalytic enzyme network incorporating temperature-sensitive Michaelis-Menten kinetics recapitulates all temperature-shift dynamics through metabolome rearrangement, which encodes a temperature memory and successfully predicts alterations in the upshift response observed under simple-sugar, low-nutrient conditions, and in fungi. This model also provides a mechanistic framework for both Arrhenius-dependent growth and the classical Monod Equation through temperature-dependent metabolite flux.

The sweet side of sex as a biological variable.

Glycobiology as a field holds enormous potential for understanding human health and disease. However, few glycobiology studies adequately address the issue of sex differences in biology, which severely limits the conclusions that can be drawn. Numerous CAZymes, lectins, and other carbohydrate-associated molecules have the potential to be differentially expressed and regulated with sex, leading to differences in O-GlcNAc, N-glycan branching, fucosylation, sialylation, and proteoglycan structure, among others. Expression of proteins involved in glycosylation is influenced through hormones, miRNA, and gene dosage effects. In this review, we discuss the benefits of incorporating sex-based analysis in glycobiology research and the potential drivers of sex differences. We highlight examples of where incorporation of sex-based analysis has led to insights into glycobiology. Finally, we offer suggestions for how to proceed moving forward, even if the experiments are already complete. Properly incorporating sex based analyses into projects will substantially improve the accuracy and reproducibility of studies as well as accelerate the rate of discovery in the glycosciences.

Developing Automated Computer Algorithms to Track Periodontal Disease Change from Longitudinal Electronic Dental Records.

OBJECTIVE: To develop two automated computer algorithms to extract information from clinical notes, and to generate three cohorts of patients (disease improvement, disease progression, and no disease change) to track periodontal disease (PD) change over time using longitudinal electronic dental records (EDR). METHODS: We conducted a retrospective study of 28,908 patients who received a comprehensive oral evaluation between 1 January 2009, and 31 December 2014, at Indiana University School of Dentistry (IUSD) clinics. We utilized various Python libraries, such as Pandas, TensorFlow, and PyTorch, and a natural language tool kit to develop and test computer algorithms. We tested the performance through a manual review process by generating a confusion matrix. We calculated precision, recall, sensitivity, specificity, and accuracy to evaluate the performances of the algorithms. Finally, we evaluated the density of longitudinal EDR data for the following follow-up times: (1) None; (2) Up to 5 years; (3) > 5 and ≤ 10 years; and (4) >10 and ≤ 15 years. RESULTS: Thirty-four percent (n = 9954) of the study cohort had up to five years of follow-up visits, with an average of 2.78 visits with periodontal charting information. For clinician-documented diagnoses from clinical notes, 42% of patients (n = 5562) had at least two PD diagnoses to determine their disease change. In this cohort, with clinician-documented diagnoses, 72% percent of patients (n = 3919) did not have a disease status change between their first and last visits, 669 (13%) patients' disease status progressed, and 589 (11%) patients' disease improved. CONCLUSIONS: This study demonstrated the feasibility of utilizing longitudinal EDR data to track disease changes over 15 years during the observation study period. We provided detailed steps and computer algorithms to clean and preprocess the EDR data and generated three cohorts of patients. This information can now be utilized for studying clinical courses using artificial intelligence and machine learning methods.

Assembly of gut-derived bacterial communities follows "early-bird" resource utilization dynamics.

Diet can impact host health through changes to the gut microbiota, yet we lack mechanistic understanding linking nutrient availability and microbiota composition. Here, we use thousands of microbial communities cultured in vitro from human feces to uncover simple assembly rules and develop a predictive model of community composition upon addition of single nutrients from central carbon metabolism to a complex medium. Community membership was largely determined by the donor feces, whereas relative abundances were determined by the supplemental carbon source. The absolute abundance of most taxa was independent of the supplementing nutrient, due to the ability of fast-growing organisms to quickly exhaust their niche in the complex medium and then exploit and monopolize the supplemental carbon source. Relative abundances of dominant taxa could be predicted from the nutritional preferences and growth dynamics of species in isolation, and exceptions were consistent with strain-level variation in growth capabilities. Our study reveals that community assembly follows simple rules of nutrient utilization dynamics and provides a predictive framework for manipulating gut commensal communities through nutritional perturbations.

Attenuation of Polysialic Acid Biosynthesis in Cells by the Small Molecule Inhibitor 8-Keto-sialic acid.

Sialic acids are key mediators of cell function, particularly with regard to cellular interactions with the surrounding environment. Reagents that modulate the display of specific sialyl glycoforms at the cell surface would be useful biochemical tools and potentially allow for therapeutic intervention in numerous challenging chronic diseases. While multiple strategies are being explored for the control of cell surface sialosides, none that shows high selectivity between sialyltransferases or that targets a specific sialyl glycoform has yet to emerge. Here, we describe a strategy to block the formation of α2,8-linked sialic acid chains (oligo- and polysialic acid) through the use of 8-keto-sialic acid as a chain-terminating metabolic inhibitor that, if incorporated, cannot be elongated. 8-Keto-sialic acid is nontoxic at effective concentrations and serves to block polysialic acid synthesis in cancer cell lines and primary immune cells, with minimal effects on other sialyl glycoforms.

Large differences in carbohydrate degradation and transport potential among lichen fungal symbionts.

Lichen symbioses are thought to be stabilized by the transfer of fixed carbon from a photosynthesizing symbiont to a fungus. In other fungal symbioses, carbohydrate subsidies correlate with reductions in plant cell wall-degrading enzymes, but whether this is true of lichen fungal symbionts (LFSs) is unknown. Here, we predict genes encoding carbohydrate-active enzymes (CAZymes) and sugar transporters in 46 genomes from the Lecanoromycetes, the largest extant clade of LFSs. All LFSs possess a robust CAZyme arsenal including enzymes acting on cellulose and hemicellulose, confirmed by experimental assays. However, the number of genes and predicted functions of CAZymes vary widely, with some fungal symbionts possessing arsenals on par with well-known saprotrophic fungi. These results suggest that stable fungal association with a phototroph does not in itself result in fungal CAZyme loss, and lends support to long-standing hypotheses that some lichens may augment fixed CO2 with carbon from external sources.

Bacterial respiration during stationary phase induces intracellular damage that leads to delayed regrowth.

Bacterial survival is often challenged by nutrient-depleted conditions. Here, we show that Escherichia coli regrowth from prolonged stationary phase is heterogeneous. Some cells rejuvenated immediately, even after extended starvation, but others only restarted growth after a delay or not at all. The proportion of nongrowing cells increased with time spent in stationary phase, rather than time-dependent medium changes. Delayed regrowth was correlated with the dissolution of polar phase-bright foci likely representing damaged protein aggregates, and a deep learning algorithm distinguished cellular fates based on single images. Delayed regrowth initiated after upregulation of chaperones and DNA-repair enzymes, and deletion of a chaperone compromised stationary-phase morphology and increased the nongrowing cell proportion. Mathematical modeling of damage accumulation and division-mediated partitioning quantitatively predicted all rejuvenation statistics. Cells regrew immediately after starving in the absence of respiration. These findings reinforce the importance of intracellular damage control when nutrients are sparse, and repair when nutrients are plentiful.

Quantifying rapid bacterial evolution and transmission within the mouse intestine.

Due to limitations on high-resolution strain tracking, selection dynamics during gut microbiota colonization and transmission between hosts remain mostly mysterious. Here, we introduced hundreds of barcoded Escherichia coli strains into germ-free mice and quantified strain-level dynamics and metagenomic changes. Mutations in genes involved in motility and metabolite utilization are reproducibly selected within days. Even with rapid selection, coprophagy enforced similar barcode distributions across co-housed mice. Whole-genome sequencing of hundreds of isolates revealed linked alleles that demonstrate between-host transmission. A population-genetics model predicts substantial fitness advantages for certain mutants and that migration accounted for ∼10% of the resident microbiota each day. Treatment with ciprofloxacin suggests interplay between selection and transmission. While initial colonization was mostly uniform, in two mice a bottleneck reduced diversity and selected for ciprofloxacin resistance in the absence of drug. These findings highlight the interplay between environmental transmission and rapid, deterministic selection during evolution of the intestinal microbiota.

Three-dimensional biofilm colony growth supports a mutualism involving matrix and nutrient sharing.

Life in a three-dimensional biofilm is typical for many bacteria, yet little is known about how strains interact in this context. Here, we created essential gene CRISPR interference knockdown libraries in biofilm-forming Bacillus subtilis and measured competitive fitness during colony co-culture with wild type. Partial knockdown of some translation-related genes reduced growth rates and led to out-competition. Media composition led some knockdowns to compete differentially as biofilm versus non-biofilm colonies. Cells depleted for the alanine racemase AlrA died in monoculture but survived in a biofilm colony co-culture via nutrient sharing. Rescue was enhanced in biofilm colony co-culture with a matrix-deficient parent due to a mutualism involving nutrient and matrix sharing. We identified several examples of mutualism involving matrix sharing that occurred in three-dimensional biofilm colonies but not when cultured in two dimensions. Thus, growth in a three-dimensional colony can promote genetic diversity through sharing of secreted factors and may drive evolution of mutualistic behavior.

Racing to build a wall: glycoconjugate assembly in Gram-positive and Gram-negative bacteria.

The last two years have seen major advances in understanding the structural basis of bacterial cell envelope glycoconjugate biosynthesis, including capsules, lipopolysaccharide, teichoic acid, cellulose, and peptidoglycan. The recent crystal and cryo-electron microscopy structures of proteins involved in the initial glycosyltransferase steps in the cytoplasm, the transport of large and small lipid-linked glycoconjugates across the inner membrane, the polymerization of glycans in the periplasm, and the export of molecules from the cell have shed light on the mechanisms by which cell envelope glycoconjugates are made. We discuss these recent advances and highlight remaining unanswered questions.

Twelve Principles Trainees, PIs, Departments, and Faculties Can Use to Reduce Bias and Discrimination in STEM.

There is an overwhelming amount of evidence demonstrating that people from marginalized groups, including women, racialized and Indigenous peoples, people with disabilities, immigrants, and LGBTQ+ individuals, continue to face substantial discrimination in STEM, manifested as both overt bias and unconscious bias. These biases result in discrimination against individuals in marginalized groups, and independent biases collectively contribute to a culture that systematically discriminates against people from marginalized groups. Representation from marginalized groups in postsecondary degrees in natural science and engineering has not substantially improved in over a decade. A set of 10 concrete principles are presented that trainees, principle investigators, departments, and faculties can use to enhance the participation and lived experiences of people in marginalized groups in STEM.

Combined effects of soft drinks and nicotine on Streptococcus mutans metabolic activity and biofilm formation.

The purpose of this study was to explore the effects of nicotine on the activity of Streptococcus mutans (S. mutans) in soft drinks. Regular soft drinks contain large proportions of high-fructose corn syrup (HFCS), which increases the activity of S. mutans resulting in high-caries risk compared with sugar-free soft drinks. Nicotine use exhibits a strong correlation with increased S. mutans biofilm formation. The soft drinks chosen were (Coca-Cola Classic, Diet Coke, Coca-Cola Zero Sugar, Caffeine-Free Coca-Cola, Caffeine-Free Diet Coke, Caffeine-Free Coca-Cola Zero Sugar). S. mutans was grown overnight in tryptic soy broth; nicotine was diluted in tryptic soy broth supplemented with 1.0% sucrose followed by soft drinks in dilution of 1:3. Total growth absorbance and biofilm growth were determined by spectrophotometry, absorbance measured to determine biofilm formation, and metabolic activity quantified. One-way ANOVA showed a considerable effect for HFCS and caffeine in the presence of nicotine and their interaction in all measures. Results showed sugar-free caffeinated colas demonstrated significant effect in inhibiting S. mutans biofilm formation and metabolic activity with nicotine. Nicotine-induced S. mutans increased biofilm formation and metabolic activity in the presence of HFCS and caffeine in soft drinks. In conclusion, smokers should consider sugar-free caffeinated versions to minimize the chance of developing dental caries dut to the reduction of biofilm formation.

Limits and Constraints on Mechanisms of Cell-Cycle Regulation Imposed by Cell Size-Homeostasis Measurements.

High-throughput imaging has led to an explosion of observations about cell-size homeostasis across the kingdoms of life. Among bacteria, "adder" behavior-in which a constant size increment appears to be added during each cell cycle-is ubiquitous, while various eukaryotes show other size-homeostasis behaviors. Since interactions between cell-cycle progression and growth ultimately determine such behaviors, we developed a general model of cell-cycle regulation. Our analyses reveal a range of scenarios that are plausible but fail to regulate cell size, indicating that mechanisms of cell-cycle regulation are stringently limited by size-control requirements, and possibly why certain cell-cycle features are strongly conserved. Cell-cycle features can play unintuitive roles in altering size-homeostasis behaviors: noisy regulator production can enhance adder behavior, while Whi5-like inhibitor dilutors respond sensitively to perturbations to G2/M control and noisy G1/S checkpoints. Our model thus provides holistic insights into the mechanistic implications of size-homeostasis experimental measurements.

A new ELISA assay demonstrates sex differences in the concentration of serum polysialic acid.

Male and female immune systems are strikingly different and yet little is known about sex differences in immune glycans, though glycans play central roles in regulating the immune response. Polysialic acid (polySia) occurs on the majority of leukocytes and is a potent immunomodulatory glycan which enables cell migration and serves as an immune checkpoint. Due to widespread influence of polySia on the immune system, we aimed to characterize its levels in serum, its presence on specific proteins, and differences in the amounts of polySia in male and female serum. However, polySia is difficult to quantify and detect on specific proteins, which makes it challenging to elucidate the molecular details of polySia function. We developed a sandwich ELISA that allows for the quantification of polySia as well as specific polysialylated proteins in complex mixtures without any pretreatment or harsh conditions. The assay is quick, linear, and robust under a wide variety of conditions and gave a limit of detection of approximately 0.2 ng polySia per mL of serum. We then quantified polySia and polysialylated CD56 in human and mouse serum. These studies strongly support our hypothesis of differences in glycosylation between the sexes as significantly less polySia was observed in female samples than in male samples.

Biosurfactant-Mediated Membrane Depolarization Maintains Viability during Oxygen Depletion in Bacillus subtilis.

The presence or absence of oxygen in the environment is a strong effector of cellular metabolism and physiology. Like many eukaryotes and some bacteria, Bacillus subtilis primarily utilizes oxygen during respiration to generate ATP. Despite the importance of oxygen for B. subtilis survival, we know little about how populations adapt to shifts in oxygen availability. Here, we find that when oxygen was depleted from stationary phase B. subtilis cultures, ∼90% of cells died while the remaining cells maintained colony-forming ability. We discover that production of the antimicrobial surfactin confers two oxygen-related fitness benefits: it increases aerobic growth yield by increasing oxygen diffusion, and it maintains viability during oxygen depletion by depolarizing the membrane. Strains unable to produce surfactin exhibited an ∼50-fold reduction in viability after oxygen depletion. Surfactin treatment of these cells led to membrane depolarization and reduced ATP production. Chemical and genetic perturbations that alter oxygen consumption or redox state support a model in which surfactin-mediated membrane depolarization maintains viability through slower oxygen consumption and/or a shift to a more reduced metabolic profile. These findings highlight the importance of membrane potential in regulating cell physiology and growth, and demonstrate that antimicrobials that depolarize cell membranes can benefit cells when the terminal electron acceptor in respiration is limiting. This foundational knowledge has deep implications for environmental microbiology, clinical anti-bacterial therapy, and industrial biotechnology.