Structural and genetic basis for the binding of a mouse monoclonal antibody to Flavobacterium psychrophilum lipopolysaccharide.

A mouse monoclonal antibody (mAb FL100A) previously prepared against Flavobacterium psychrophilum (Fp) CSF259-93 has now been examined for binding to lipopolysaccharides (LPS) of this strain and Fp 950106-1/1. The corresponding O-polysaccharides (O-PS) of these strains are formed by identical trisaccharide repeats composed of l-Rhamnose (l-Rha), 2-acetamido-2-deoxy-l-fucose (l-FucNAc) and 2-acetamido-4-R1-2,4-dideoxy-d-quinovose (d-Qui2NAc4NR1) where R1 represents a dihydroxyhexanamido moiety. The O-PS loci of these strains are also identical except for the gene (wzy1 or wzy2) that encodes the polysaccharide polymerase. Accordingly, adjacent O-PS repeats are joined through d-Qui2NAc4NR1 and l-Rha by wzy2-dependent α(1-2) linkages in Fp CSF259-93 versus wzy1-dependent ß(1-3) linkages in Fp 950106-1/1. mAb FL100A reacted strongly with Fp CSF259-93 O-PS and LPS but weakly or not at all with Fp 950106-1/1 LPS and O-PS. Importantly, it also labelled cell surface blebs on the former but not the latter strain. Additionally, mAb binding was approximately 5-times stronger to homologous Fp CSF259-93 LPS than to LPS from a strain with a different R-group gene. A conformational epitope for mAb FL100A binding was suggested from molecular dynamic simulations of each O-PS. Thus, Fp CSF259-93 O-PS formed a stable well-defined compact helix in which the R1 groups were displayed in a regular pattern on the helix exterior while unreactive Fp 950106-1/1 O-PS adopted a flexible extended linear conformation. Taken together, the findings establish the specificity of mAb FL100A for Wzy2-linked F. psychrophilum O-PS and LPS.

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.

Deidentifying Narrative Assessments to Facilitate Data Sharing in Medical Education.

PROBLEM: Narrative assessments are commonly incorporated into competency-based medical education programs. However, efforts to share competency-based medical education assessment data among programs to support the evaluation and improvement of assessment systems have been limited in part because of security concerns. Deidentifying assessment data mitigates these concerns, but deidentifying narrative assessments is time-consuming, resource intensive, and error prone. The authors developed and tested a tool to automate the deidentification of narrative assessments and facilitate their review. APPROACH: The authors met throughout 2021 and 2022 to iteratively design, test, and refine the deidentification algorithm and data review interface. Preliminary testing of the prototype deidentification algorithm was performed using narrative assessments from the University of Saskatchewan emergency medicine program. The algorithm's accuracy was assessed by the authors using the review interface designed for this purpose. Formal testing included 2 rounds of deidentification and review by members of the authorship team. Both the algorithm and data review interface were refined during the testing process. OUTCOMES: Authors from 3 institutions, including 3 emergency medicine programs, an anesthesia program, and a surgical program, participated in formal testing. In the final round of review, 99.4% of the narrative assessments were fully deidentified (names, nicknames, and pronouns removed). The results were comparable for each institution and specialty. The data review interface was improved with feedback obtained after each round of review and found to be intuitive. NEXT STEPS: This innovation has demonstrated viability evidence of an algorithmic approach to the deidentification of assessment narratives while reinforcing that a small number of errors are likely to persist. Future steps include the refinement of both the algorithm to improve its accuracy and the data review interface to support additional data set formats.

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.

Exploring longitudinal changes in implicit awareness of dementia: An investigation of the emotional Stroop effect in healthy ageing and mild dementia.

The aim of the study was to investigate responses to dementia-relevant words in healthy older people and to investigate changes in response over 20-months in people with early-stage dementia. An emotional Stroop task, using colour-naming dementia-relevant words, was used as an indicator of implicit awareness of dementia. Overall, 24 people with dementia and 24 healthy older people completed an emotional Stroop task (T1). People with dementia completed the same task again after 12 (T2) and 20 (T3) months. For people with dementia emotional Stroop performance was contrasted with ratings of explicit awareness based on a detailed interview at T1 and at T2. For healthy older people and people with dementia response times to dementia-relevant words were significantly longer than those for neutral words. The effect was absent for people with dementia at T3. This decline in the emotional Stroop effect was not associated with cognitive decline as measured by the MMSE. Ratings of explicit awareness showed no significant change over time. There was no association between explicit awareness and implicit awareness. Implicit awareness of the condition is evident in early-stage dementia and can be elicited even where there is reduced explicit awareness. The emotional Stroop effect for dementia-relevant words in people with dementia appears to decline over time, independently of changes in MMSE score, suggesting that implicit awareness fades as time progresses.

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.

Implementing a home-based personalised cognitive rehabilitation intervention for people with mild-to-moderate dementia: GREAT into Practice.

BACKGROUND: Evidence-based rehabilitative interventions, if widely implemented, could equip people with dementia and their families to manage life with the condition and reduce the need for health and care services. The aim of this translational study, building on evidence from the GREAT randomised controlled trial, was to develop a foundation for implementing the GREAT Cognitive Rehabilitation intervention in community-based services for people with mild-to-moderate dementia. METHODS: Key elements of the implementation strategy were identifying and supporting managerial and clinical leadership, conducting collaborative planning and target-setting, training and supporting practitioners, and providing external facilitation. We developed implementation plans with, and trained staff in, 14 organisations. We subsequently worked closely with 11 of these, 10 National Health Service organisations and one private home care provider, to support practitioners to deliver GREAT Cognitive Rehabilitation over a 12-month period. Outcome evaluation examined the perspectives of local steering group members, practitioners and service users, and the reach, effectiveness and cost of the intervention. RESULTS: Implementation was disrupted by the COVID-19 pandemic, but six organisations completed at least six months of intervention delivery. Forty-one practitioners, mainly occupational therapists, provided the intervention, and 54 people with dementia completed a course of GREAT Cognitive Rehabilitation. Goal attainment by people with dementia exceeded levels of improvement seen in the original trial. People with dementia, carers, practitioners and steering group members all evaluated the intervention positively, and economic analysis indicated that the intervention could be provided at modest cost. However, we identified a range of mainly organisational barriers that impeded implementation and limited the potential for sustainability. CONCLUSIONS: GREAT Cognitive Rehabilitation benefits people with dementia, can be delivered effectively at modest cost in routine services, and is viewed positively by people with dementia, family carers and practitioners. To fully realise these benefits and achieve widespread and sustainable implementation, however, requires sufficient resources and a reorientation of service priorities towards preventive and rehabilitative approaches. TRIAL REGISTRATION: National Institute for Health Research (NIHR) Central Portfolio Management System, registration number 38994.

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.

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.

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.

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.