Does Inter-Residue Hydrogen Bonding in ß-(1→4)-Linked Disaccharides Influence Linkage Conformation in Aqueous Solution?

Two disaccharides, methyl ß-d-galactopyranosyl-(1→4)-α-d-glucopyranoside (1) and methyl ß-d-galactopyranosyl-(1→4)-3-deoxy-α-d-ribo-hexopyranoside (3), were prepared with selective 13C-enrichment to allow measurement of six trans-O-glycosidic J-couplings (2JCOC, 3JCOCH, and 3JCOCC) in each compound. Density functional theory (DFT) was used to parameterize Karplus-like equations that relate these J-couplings to either ϕ or ψ. MA'AT analysis was applied to both linkages to determine mean values of ϕ and ψ in each disaccharide and their associated circular standard deviations (CSDs). Results show that deoxygenation at C3 of 1 has little effect on both the mean values and librational motions of the linkage torsion angles. This finding implies that, if inter-residue hydrogen bonding between O3H and O5' of 1 is present in aqueous solution and persistent, it plays little if any role in dictating preferred linkage conformation. Hydrogen bonding may lower the energy of the preferred linkage geometry but does not determine it to any appreciable extent. Aqueous 1-µs MD simulation supports this conclusion and also indicates greater conformational flexibility in deoxydisaccharide 3 in terms of sampling several, conformationally distinct, higher-energy conformers in solution. The populations of these latter conformers are low (3-14%) and could not be validated by MA'AT analysis. If the MD model is correct, however, C3 deoxygenation does enable conformational sampling over a wider range of ϕ/ψ values, but linkage conformation in the predominant conformer is essentially identical in both 1 and 3.

Position-specific N- and O-glycosylation of the reactive center loop impacts neutrophil elastase-mediated proteolysis of corticosteroid-binding globulin.

Corticosteroid-binding globulin (CBG) delivers anti-inflammatory cortisol to inflamed tissues through proteolysis of an exposed reactive center loop (RCL) by neutrophil elastase (NE). We previously demonstrated that RCL-localized Asn347-linked N-glycans impact NE proteolysis, but a comprehensive structure-function characterization of the RCL glycosylation is still required to better understand CBG glycobiology. Herein, we first performed RCL-centric glycoprofiling of serum-derived CBG to elucidate the Asn347-glycans and then used molecular dynamics simulations to study their impact on NE proteolysis. Importantly, we also identified O-glycosylation (di/sialyl T) across four RCL sites (Thr338/Thr342/Thr345/Ser350) of serum CBG close to the NE-targeted Val344-Thr345 cleavage site. A restricted N- and O-glycan co-occurrence pattern on the RCL involving exclusively Asn347 and Thr338 glycosylation was experimentally observed and supported in silico by modeling of a CBG-GalNAc-transferase (GalNAc-T) complex with various RCL glycans. GalNAc-T2 and GalNAc-T3 abundantly expressed by liver and gall bladder, respectively, showed in vitro a capacity to transfer GalNAc (Tn) to multiple RCL sites suggesting their involvement in RCL O-glycosylation. Recombinant CBG was then used to determine roles of RCL O-glycosylation through longitudinal NE-centric proteolysis experiments, which demonstrated that both sialoglycans (disialyl T) and asialoglycans (T) decorating Thr345 inhibit NE proteolysis. Synthetic RCL O-glycopeptides expanded on these findings by showing that Thr345-Tn and Thr342-Tn confer strong and moderate protection against NE cleavage, respectively. Molecular dynamics substantiated that short Thr345-linked O-glycans abrogate NE interactions. In conclusion, we report on biologically relevant CBG RCL glycosylation events, which improve our understanding of mechanisms governing cortisol delivery to inflamed tissues.

Sensitive and Specific Global Cell Surface N-Glycoproteomics Shows Profound Differences Between Glycosylation Sites and Subcellular Components.

Cell surface glycans are essential for establishing cell communication, adhesion, and migration. However, it remains challenging to obtain cell surface-specific information about glycoconjugate structures. Acquiring this information is essential for unraveling the functional role of glycans and for exploiting them as clinical targets. To specifically analyze the N-glycoprotein forms expressed at the cell surface, we developed a C18 liquid chromatography (LC)-mass spectrometry (MS)-based glycoproteomics method in combination with highly specific cell surface protein labeling and enrichment using a biotin label. The surface-specificity of the method was validated by MS-based proteomics of subcellular component marker proteins. Using the human keratinocytes N/TERT-1 as a model system, we identified and quantified the glycosylation of hundreds of cell surface N-glycosylation sites. This approach allowed us to study the glycoforms present at the functional relevant cell surface, omitting immaturely glycosylated proteins present in the secretory pathway. Interestingly, the different stages of N-glycan processing at individual sites displayed at the cell surface were found to correlate with their accessibility for ER-residing processing enzymes, as investigated through molecular dynamics simulations. Using the new approach, we compared N-glycosylation sites of proteins expressed on the cell surface to their counterparts in a total cell lysate, showing profound differences in glycosylation between the subcellular components and indicating the relevance of the method for future studies in understanding contextual glycan functions.

Mono-phosphorylation at Ser4 of barrier-to-autointegration factor (Banf1) significantly reduces its DNA binding capability by inducing critical changes in its local conformation and DNA binding surface.

Barrier-to-autointegration factor (Banf1) is a small DNA-bridging protein. The binding status of Banf1 to DNA is regulated by its N-terminal phosphorylation and dephosphorylation, which plays a critical role in cell proliferation. Banf1 can be phosphorylated at Ser4 into mono-phosphorylated Banf1, which is further phosphorylated at Thr3 to form di-phosphorylated Banf1. It was observed decades ago that mono-phosphorylated Banf1 cannot bind to DNA. However, the underlying molecular- and atomic-level mechanisms remain unclear. A clear understanding of these mechanisms will aid in interfering with the cell proliferation process for better global health. Herein, we explored the detailed atomic bases of unphosphorylated Banf1-DNA binding and how mono- and di-phosphorylation of Banf1 impair these atomic bases to eliminate its DNA-binding capability, followed by exploring the DNA-binding capability of mono- and di-phosphorylation Banf1, using comprehensive and systematic molecular modelling and molecular dynamics simulations. This work presented in detail the residue-level binding energies, hydrogen bonds and water bridges between Banf1 and DNA, some of which have not been reported. Moreover, we revealed that mono-phosphorylation of Banf1 causes its N-terminal secondary structure changes, which in turn induce significant changes in Banf1's DNA binding surface, thus eliminating its DNA-binding capability. At the atomic level, we also uncovered the alterations in interactions due to the induction of mono-phosphorylation that result in the N-terminal secondary structure changes of Banf1. Additionally, our modelling showed that phosphorylated Banf1 with their dominant N-terminal secondary structures bind to DNA with a significantly lower affinity and the docked binding pose are not stable in MD simulations. These findings help future studies in predicting effect of mutations in Banf1 on its DNA-binding capability and open a novel avenue for the development of therapeutics such as cancer drugs, targeting cell proliferation by inducing conformational changes in Banf1's N-terminal domain.

MA'AT Analysis: Probability Distributions of Molecular Torsion Angles in Solution from NMR Spectroscopy.

ConspectusMonosaccharides adopt multiple conformations in solution, and this structural complexity increases significantly when they are assembled into oligosaccharides and polysaccharides. Characterization of the conformational properties of saccharides in solution by NMR spectroscopy has been hampered by several complicating factors, including difficulty interpreting spectra because of significant signal overlap, population averaging of NMR parameters, and unique properties of the spectra that make accurate measurements of NMR parameters prone to error (e.g., non-first-order effects on J-couplings). Current conformational assignments rely heavily on theoretical calculations, especially molecular dynamics (MD) simulations, to interpret the experimental NMR parameters. While these studies assert that the available experimental data fit the calculated models well, a lack of independent experimental validation of the force fields from which MD models are derived and an inability to test all possible models that might be compatible with the experimental data in an unbiased manner make the approach less than ideal.NMR spin couplings or J-couplings have been used as structure constraints in organic and other types of molecules for more than six decades. The dihedral angle dependence of vicinal (three-bond) 1H-1H spin couplings (3JHH) first described by Karplus led to an explosion of applications for a wide range of conformational problems. Other vicinal J-couplings (e.g., 3JCCOP, 3JHCOP, and 3JCOCH) have been found to exhibit similar dihedral angle dependencies. 3J values have been used to assign the preferred conformation in molecules that are conformationally homogeneous. However, many molecules, particularly those in biological systems, are conformationally flexible, which complicates structural interpretations of J values in solution. Three-state staggered models are often assumed in order to deconvolute the conformationally averaged J values into conformer populations. While widely applied, this approach assumes highly idealized models of molecular torsion angles that are likely to be poor representations of those found in solution. In addition, this treatment often gives negative populations and neglects the presence of librational averaging of molecular torsion angles.Recent work in this research group has focused on the development of a hybrid experimental-computational method, MA'AT analysis, that provides probability distributions of molecular torsion angles in solution that can be superimposed on those obtained by MD. Ensembles of redundant NMR spin couplings, including 3J (vicinal), 2J (geminal), and sometimes 1J (direct) values, are used in conjunction with circular statistics to provide single- and multistate models of these angles. MA'AT analysis provides accurate mean torsion angles and circular standard deviations (CSDs) of each mean angle that describe the librational motion about the angle. Both conformational equilibria and dynamics are revealed by the method. In this Account, the salient features of MA'AT analysis are discussed, including some applications to conformational problems involving saccharides and peptides.

Protein-Ligand CH-π Interactions: Structural Informatics, Energy Function Development, and Docking Implementation.

Here, we develop an empirical energy function based on quantum mechanical data for the interaction between methane and benzene that captures the contribution from CH-π interactions. Such interactions are frequently observed in protein-ligand crystal structures, particularly for carbohydrate ligands, but have been hard to quantify due to the absence of a model for CH-π interactions in typical molecular mechanical force fields or docking scoring functions. The CH-π term was added to the AutoDock Vina (AD VINA) scoring function enabling its performance to be evaluated against a cohort of more than 1600 occurrences in 496 experimental structures of protein-ligand complexes. By employing a conformational grid search algorithm, inclusion of the CH-π term was shown to improve the prediction of the preferred orientation of flexible ligands in protein-binding sites and to enhance the detection of carbohydrate-binding sites that display CH-π interactions. Last but not least, this term was also shown to improve docking performance for the CASF-2016 benchmark set and a carbohydrate set.

The evolution of antibiotic resistance in an incurable and ultimately fatal infection: A retrospective case study.

Background and objectives: The processes by which pathogens evolve within a host dictate the efficacy of treatment strategies designed to slow antibiotic resistance evolution and influence population-wide resistance levels. The aim of this study is to describe the underlying genetic and phenotypic changes leading to antibiotic resistance within a patient who died as resistance evolved to available antibiotics. We assess whether robust patterns of collateral sensitivity and response to combinations existed that might have been leveraged to improve therapy. Methodology: We used whole-genome sequencing of nine isolates taken from this patient over 279 days of a chronic infection with Enterobacter hormaechei, and systematically measured changes in resistance against five of the most relevant drugs considered for treatment. Results: The entirety of the genetic change is consistent with de novo mutations and plasmid loss events, without acquisition of foreign genetic material via horizontal gene transfer. The nine isolates fall into three genetically distinct lineages, with early evolutionary trajectories being supplanted by previously unobserved multi-step evolutionary trajectories. Importantly, although the population evolved resistance to all the antibiotics used to treat the infection, no single isolate was resistant to all antibiotics. Evidence of collateral sensitivity and response to combinations therapy revealed inconsistent patterns across this diversifying population. Conclusions: Translating antibiotic resistance management strategies from theoretical and laboratory data to clinical situations, such as this, will require managing diverse population with unpredictable resistance trajectories.

Cataloging natural sialic acids and other nonulosonic acids (NulOs), and their representation using the Symbol Nomenclature for Glycans.

Nonulosonic acids or non-2-ulosonic acids (NulOs) are an ancient family of 2-ketoaldonic acids (α-ketoaldonic acids) with a 9-carbon backbone. In nature, these monosaccharides occur either in a 3-deoxy form (referred to as "sialic acids") or in a 3,9-dideoxy "sialic-acid-like" form. The former sialic acids are most common in the deuterostome lineage, including vertebrates, and mimicked by some of their pathogens. The latter sialic-acid-like molecules are found in bacteria and archaea. NulOs are often prominently positioned at the outermost tips of cell surface glycans, and have many key roles in evolution, biology and disease. The diversity of stereochemistry and structural modifications among the NulOs contributes to more than 90 sialic acid forms and 50 sialic-acid-like variants described thus far in nature. This paper reports the curation of these diverse naturally occurring NulOs at the NCBI sialic acid page (https://www.ncbi.nlm.nih.gov/glycans/sialic.html) as part of the NCBI-Glycans initiative. This includes external links to relevant Carbohydrate Structure Databases. As the amino and hydroxyl groups of these monosaccharides are extensively derivatized by various substituents in nature, the Symbol Nomenclature For Glycans (SNFG) rules have been expanded to represent this natural diversity. These developments help illustrate the natural diversity of sialic acids and related NulOs, and enable their systematic representation in publications and online resources.

Simplifying the detection and monitoring of protein glycosylation during in vitro glycoengineering.

The majority of mammalian proteins are glycosylated, with the glycans serving to modulate a wide range of biological activities. Variations in protein glycosylation can have dramatic effects on protein stability, immunogenicity, antibody effector function, pharmacological safety and potency, as well as serum half-life. The glycosylation of therapeutic biologicals is a critical quality attribute (CQA) that must be carefully monitored to ensure batch-to-batch consistency. Notably, many factors can affect the composition of the glycans during glycoprotein production, and variations in glycosylation are among the leading causes of pharmaceutical batch rejection. Currently, the characterization of protein glycosylation relies heavily on methods that employ chromatography and/or mass spectrometry, which require a high level of expertise, are time-consuming and costly and, because they are challenging to implement during in-process biologics production or during in vitro glycan modification, are generally performed only post-production. Here we report a simplified approach to assist in monitoring glycosylation features during glycoprotein engineering, that employs flow cytometry using fluorescent microspheres chemically coupled to high-specificity glycan binding reagents. In our GlycoSense method, a range of carbohydrate-sensing microspheres with distinct optical properties may be combined into a multiplex suspension array capable of detecting multiple orthogonal glycosylation features simultaneously, using commonplace instrumentation, without the need for glycan release. The GlycoSense method is not intended to replace more detailed post-production glycan profiling, but instead, to complement them by potentially providing a cost-effective, rapid, yet robust method for use at-line as a process analytic technology (PAT) in a biopharmaceutical workflow or at the research bench. The growing interest in using in vitro glycoengineering to generate glycoproteins with well-defined glycosylation, provides motivation to demonstrate the capabilities of the GlycoSense method, which we apply here to monitor changes in the protein glycosylation pattern (GlycoPrint) during the in vitro enzymatic modification of the glycans in model glycoproteins.

The Gut Microbiome Modulates Body Temperature Both in Sepsis and Health.

Rationale: Among patients with sepsis, variation in temperature trajectories predicts clinical outcomes. In healthy individuals, normal body temperature is variable and has decreased consistently since the 1860s. The biologic underpinnings of this temperature variation in disease and health are unknown. Objectives: To establish and interrogate the role of the gut microbiome in calibrating body temperature. Methods: We performed a series of translational analyses and experiments to determine whether and how variation in gut microbiota explains variation in body temperature in sepsis and in health. We studied patient temperature trajectories using electronic medical record data. We characterized gut microbiota in hospitalized patients using 16S ribosomal RNA gene sequencing. We modeled sepsis using intraperitoneal LPS in mice and modulated the microbiome using antibiotics, germ-free, and gnotobiotic animals. Measurements and Main Results: Consistent with prior work, we identified four temperature trajectories in patients hospitalized with sepsis that predicted clinical outcomes. In a separate cohort of 116 hospitalized patients, we found that the composition of patients' gut microbiota at admission predicted their temperature trajectories. Compared with conventional mice, germ-free mice had reduced temperature loss during experimental sepsis. Among conventional mice, heterogeneity of temperature response in sepsis was strongly explained by variation in gut microbiota. Healthy germ-free and antibiotic-treated mice both had lower basal body temperatures compared with control animals. The Lachnospiraceae family was consistently associated with temperature trajectories in hospitalized patients, experimental sepsis, and antibiotic-treated mice. Conclusions: The gut microbiome is a key modulator of body temperature variation in both health and critical illness and is thus a major, understudied target for modulating physiologic heterogeneity in sepsis.

In critically ill patients, anti-anaerobic antibiotics increase risk of adverse clinical outcomes.

BACKGROUND: Critically ill patients routinely receive antibiotics with activity against anaerobic gut bacteria. However, in other disease states and animal models, gut anaerobes are protective against pneumonia, organ failure and mortality. We therefore designed a translational series of analyses and experiments to determine the effects of anti-anaerobic antibiotics on the risk of adverse clinical outcomes among critically ill patients. METHODS: We conducted a retrospective single-centre cohort study of 3032 critically ill patients, comparing patients who did and did not receive early anti-anaerobic antibiotics. We compared intensive care unit outcomes (ventilator-associated pneumonia (VAP)-free survival, infection-free survival and overall survival) in all patients and changes in gut microbiota in a subcohort of 116 patients. In murine models, we studied the effects of anaerobe depletion in infectious (Klebsiella pneumoniae and Staphylococcus aureus pneumonia) and noninfectious (hyperoxia) injury models. RESULTS: Early administration of anti-anaerobic antibiotics was associated with decreased VAP-free survival (hazard ratio (HR) 1.24, 95% CI 1.06-1.45), infection-free survival (HR 1.22, 95% CI 1.09-1.38) and overall survival (HR 1.14, 95% CI 1.02-1.28). Patients who received anti-anaerobic antibiotics had decreased initial gut bacterial density (p=0.00038), increased microbiome expansion during hospitalisation (p=0.011) and domination by Enterobacteriaceae spp. (p=0.045). Enterobacteriaceae were also enriched among respiratory pathogens in anti-anaerobic-treated patients (p<2.2×10-16). In murine models, treatment with anti-anaerobic antibiotics increased susceptibility to Enterobacteriaceae pneumonia (p<0.05) and increased the lethality of hyperoxia (p=0.0002). CONCLUSIONS: In critically ill patients, early treatment with anti-anaerobic antibiotics is associated with increased mortality. Mechanisms may include enrichment of the gut with respiratory pathogens, but increased mortality is incompletely explained by infections alone. Given consistent clinical and experimental evidence of harm, the widespread use of anti-anaerobic antibiotics should be reconsidered.

Identifying optimal vaccination scenarios to reduce varicella zoster virus transmission and reactivation.

BACKGROUND: Varicella zoster virus (VZV) is one of the eight known human herpesviruses. Initial VZV infection results in chickenpox, while viral reactivation following a period of latency manifests as shingles. Separate vaccines exist to protect against both initial infection and subsequent reactivation. Controversy regarding chickenpox vaccination is contentious with most countries not including the vaccine in their childhood immunization schedule due to the hypothesized negative impact on immune-boosting, where VZV reactivation is suppressed through exogenous boosting of VZV antibodies from exposure to natural chickenpox infections. METHODS: Population-level chickenpox and shingles notifications from Thailand, a country that does not vaccinate against either disease, were previously fitted with mathematical models to estimate rates of VZV transmission and reactivation. Here, multiple chickenpox and shingles vaccination scenarios were simulated and compared to a model lacking any vaccination to analyze the long-term impacts of VZV vaccination. RESULTS: As expected, simulations suggested that an introduction of the chickenpox vaccine, at any coverage level, would reduce chickenpox incidence. However, chickenpox vaccine coverage levels above 35% would increase shingles incidence under realistic estimates of shingles coverage with the current length of protective immunity from the vaccine. A trade-off between chickenpox and shingles vaccination coverage was discovered, where mid-level chickenpox coverage levels were identified as the optimal target to minimize total zoster burden. Only in scenarios where shingles vaccine provided lifelong immunity or coverage exceeded current levels could large reductions in both chickenpox and shingles be achieved. CONCLUSIONS: The complicated nature of VZV makes it impossible to select a single vaccination scenario as universal policy. Strategies focused on reducing both chickenpox and shingles incidence, but prioritizing the latter should maximize efforts towards shingles vaccination, while slowly incorporating chickenpox vaccination. Alternatively, countries may wish to minimize VZV complications of both chickenpox and shingles, which would lead to maximizing vaccine coverage levels across both diseases. Balancing the consequences of vaccination to overall health impacts, including understanding the impact of an altered mean age of infection for both chickenpox and shingles, would need to be considered prior to any vaccine introduction.

Computationally guided conversion of the specificity of E-selectin to mimic that of Siglec-8.

Sulfated glycans have been found to be associated with various diseases and therefore have significant potential in molecular pathology as biomarkers. Although lectins are useful reagents for detecting glycans, there is a paucity of sulfate-recognizing lectins, and those that exist, such as from Maackia amurensis, display mixed specificities. Recombinant lectin engineering offers an emerging tool for creating novel glycan recognition by altering and/or enhancing endogenous specificities. The present study demonstrated the use of computational approaches in the engineering of a mutated form of E-selectin that displayed highly specific recognition of 6'-sulfo-sialyl Lewis X (6'-sulfo-sLex), with negligible binding to its endogenous nonsulfated ligand, sLex. This new specificity mimics that of the unrelated protein Siglec-8, for which 6'-sulfo-sLex is its preferred ligand. Molecular dynamics simulations and energy calculations predicted that two point mutations (E92A/E107A) would be required to stabilize binding to the sulfated oligosaccharide with E-selectin. In addition to eliminating putative repulsions between the negatively charged side chains and the sulfate moiety, the mutations also abolished favorable interactions with the endogenous ligand. Glycan microarray screening of the recombinantly expressed proteins confirmed the predicted specificity change but also identified the introduction of unexpected affinity for the unfucosylated form of 6'-sulfo-sLex (6'-sulfo-sLacNAc). Three key requirements were demonstrated in this case for engineering specificity for sulfated oligosaccharide: 1) removal of unfavorable interactions with the 6'-sulfate, 2) introduction of favorable interactions for the sulfate, and 3) removal of favorable interactions with the endogenous ligand.

Ion Exchange Biomaterials to Capture Daptomycin and Prevent Resistance Evolution in Off-Target Bacterial Populations.

Daptomycin (DAP), a cyclic anionic lipopeptide antibiotic, is among the last resorts to treat multidrug-resistant Gram-positive bacterial infections, caused by vancomycin-resistant Enterococcus faecium or methicillin-resistant Staphylococcus aureus. DAP is administered intravenously, and via biliary excretion, ∼5-10% of the intravenous DAP dose arrives in the gastrointestinal (GI) tract where it drives resistance evolution in the off-target populations of E. faecium bacteria. Previously, we have shown in vivo that the oral administration of cholestyramine, an ion exchange biomaterial (IXB) sorbent, prevents DAP treatment from enriching DAP resistance in the populations of E. faecium shed from mice. Here, we investigate the biomaterial-DAP interfacial interactions to uncover the antibiotic removal mechanisms. The IXB-mediated DAP capture from aqueous media was measured in controlled pH/electrolyte solutions and in the simulated intestinal fluid (SIF) to uncover the molecular and colloidal mechanisms of DAP removal from the GI tract. Our findings show that the IXB electrostatically adsorbs the anionic antibiotic via a time-dependent diffusion-controlled process. Unsteady-state diffusion-adsorption mass balance describes the dynamics of adsorption well, and the maximum removal capacity is beyond the electric charge stoichiometric ratio because of DAP self-assembly. This study may open new opportunities for optimizing cholestyramine adjuvant therapy to prevent DAP resistance, as well as designing novel biomaterials to remove off-target antibiotics from the GI tract.

An orally administered drug prevents selection for antibiotic-resistant bacteria in the gut during daptomycin therapy.

Background and objectives: Previously, we showed proof-of-concept in a mouse model that oral administration of cholestyramine prevented enrichment of daptomycin-resistant Enterococcus faecium in the gastrointestinal (GI) tract during daptomycin therapy. Cholestyramine binds daptomycin in the gut, which removes daptomycin selection pressure and so prevents the enrichment of resistant clones. Here, we investigated two open questions related to this approach: (i) can cholestyramine prevent the enrichment of diverse daptomycin mutations emerging de novo in the gut? and (ii) how does the timing of cholestyramine administration impact its ability to suppress resistance? Methodology: Mice with GI E. faecium were treated with daptomycin with or without cholestyramine, and E. faecium was cultured from feces to measure changes in daptomycin susceptibility. A subset of clones was sequenced to investigate the genomic basis of daptomycin resistance. Results: Cholestyramine prevented the enrichment of diverse resistance mutations that emerged de novo in daptomycin-treated mice. Whole-genome sequencing revealed that resistance emerged through multiple genetic pathways, with most candidate resistance mutations observed in the clsA gene. In addition, we observed that cholestyramine was most effective when administration started prior to the first dose of daptomycin. However, beginning cholestyramine after the first daptomycin dose reduced the frequency of resistant E. faecium compared to not using cholestyramine at all. Conclusions and implications: Cholestyramine prevented the enrichment of diverse daptomycin-resistance mutations in intestinal E. faecium populations during daptomycin treatment, and it is a promising tool for managing the transmission of daptomycin-resistant E. faecium.

O-fucosylation stabilizes the TSR3 motif in thrombospondin-1 by interacting with nearby amino acids and protecting a disulfide bond.

Thrombospondin type-1 repeats (TSRs) are small protein motifs containing six conserved cysteines forming three disulfide bonds that can be modified with an O-linked fucose. Protein O-fucosyltransferase 2 (POFUT2) catalyzes the addition of O-fucose to TSRs containing the appropriate consensus sequence, and the O-fucose modification can be elongated to a Glucose-Fucose disaccharide with the addition of glucose by ß3-glucosyltransferase (B3GLCT). Elimination of Pofut2 in mice results in embryonic lethality in mice, highlighting the biological significance of O-fucose modification on TSRs. Knockout of POFUT2 in HEK293T cells has been shown to cause complete or partial loss of secretion of many proteins containing O-fucosylated TSRs. In addition, POFUT2 is localized to the endoplasmic reticulum (ER) and only modifies folded TSRs, stabilizing their structures. These observations suggest that POFUT2 is involved in an ER quality control mechanism for TSR folding and that B3GLCT also participates in quality control by providing additional stabilization to TSRs. However, the mechanisms by which addition of these sugars result in stabilization are poorly understood. Here, we conducted molecular dynamics (MD) simulations and provide crystallographic and NMR evidence that the Glucose-Fucose disaccharide interacts with specific amino acids in the TSR3 domain in thrombospondin-1 that are within proximity to the O-fucosylation modification site resulting in protection of a nearby disulfide bond. We also show that mutation of these amino acids reduces the stabilizing effect of the sugars in vitro. These data provide mechanistic details regarding the importance of O-fucosylation and how it participates in quality control mechanisms inside the ER.

The bacterial density of clinical rectal swabs is highly variable, correlates with sequencing contamination, and predicts patient risk of extraintestinal infection.

BACKGROUND: In ecology, population density is a key feature of community analysis. Yet in studies of the gut microbiome, bacterial density is rarely reported. Studies of hospitalized patients commonly use rectal swabs for microbiome analysis, yet variation in their bacterial density-and the clinical and methodologic significance of this variation-remains undetermined. We used an ultra-sensitive quantification approach-droplet digital PCR (ddPCR)-to quantify bacterial density in rectal swabs from 118 hospitalized patients. We compared bacterial density with bacterial community composition (via 16S rRNA amplicon sequencing) and clinical data to determine if variation in bacterial density has methodological, clinical, and prognostic significance. RESULTS: Bacterial density in rectal swab specimens was highly variable, spanning five orders of magnitude (1.2 × 104-3.2 × 109 16S rRNA gene copies/sample). Low bacterial density was strongly correlated with the detection of sequencing contamination (Spearman ρ = - 0.95, p < 10-16). Low-density rectal swab communities were dominated by peri-rectal skin bacteria and sequencing contaminants (p < 0.01), suggesting that some variation in bacterial density is explained by sampling variation. Yet bacterial density was also associated with important clinical exposures, conditions, and outcomes. Bacterial density was lower among patients who had received piperacillin-tazobactam (p = 0.017) and increased among patients with multiple medical comorbidities (Charlson score, p = 0.0040) and advanced age (p = 0.043). Bacterial density at the time of hospital admission was independently associated with subsequent extraintestinal infection (p = 0.0028), even when controlled for severity of illness and comorbidities. CONCLUSIONS: The bacterial density of rectal swabs is highly variable, and this variability is of methodological, clinical, and prognostic significance. Microbiome studies using rectal swabs are vulnerable to sequencing contamination and should include appropriate negative sequencing controls. Among hospitalized patients, gut bacterial density is associated with clinical exposures (antibiotics, comorbidities) and independently predicts infection risk. Bacterial density is an important and under-studied feature of gut microbiome community analysis. Video abstract.

SARS-CoV-2 Genomic Surveillance Reveals Little Spread From a Large University Campus to the Surrounding Community.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has had high incidence rates at institutions of higher education (IHE) in the United States, but the transmission dynamics in these settings are poorly understood. It remains unclear to what extent IHE-associated outbreaks have contributed to transmission in nearby communities. METHODS: We implemented high-density prospective genomic surveillance to investigate these dynamics at the University of Michigan and the surrounding community during the Fall 2020 semester (August 16-November 24). We sequenced complete severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from 1659 individuals, including 468 students, representing 20% of cases in students and 25% of total cases in Washtenaw County over the study interval. RESULTS: Phylogenetic analysis identified >200 introductions into the student population, most of which were not related to other student cases. There were 2 prolonged student transmission clusters, of 115 and 73 individuals, that spanned multiple on-campus residences. Remarkably, <5% of nonstudent genomes were descended from student clusters, and viral descendants of student cases were rare during a subsequent wave of infections in the community. CONCLUSIONS: The largest outbreaks among students at the University of Michigan did not significantly contribute to the rise in community cases in Fall 2020. These results provide valuable insights into SARS-CoV-2 transmission dynamics at the regional level.