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Biology subjects

Altman, M. O.

Publications and source records attributed to Altman, M. O..

3 recordsLinked to original sources

Glycocalyx crowding with synthetic mucin mimetics strengthens interactions between soluble and virus-associated lectins and cell surface glycan receptors

Membrane-associated mucins protect epithelial cell surfaces against pathogenic threats by serving as non-productive decoys that capture infectious agents and clear them from the cell surface and by erecting a physical barrier that restricts their access to target receptors on host cells. However, the mechanisms through which mucins function are still poorly defined due to a limited repertoire of tools available for tailoring their structure and composition in living cells with molecular precision. Using synthetic glycopolymer mimetics of mucins, we modeled the mucosal glycocalyx on red blood cells (RBC) and evaluated its influence on lectin (SNA) and virus (H1N1) adhesion to endogenous sialic acid receptors. The glycocalyx inhibited the rate of SNA and H1N1 adhesion in a size- and density-dependent manner, consistent with current view of the mucins as providing a protective shield against pathogens. Counterintuitively, increasing density of the mucin mimetics enhanced the retention of bound lectins and viruses. Careful characterization of SNA behavior at the RBC surface using a range of biophysical and imaging techniques revealed lectin-induced crowding and reorganization of the glycocalyx with concomitant enhancement in lectin clustering, presumably through the formation of a more extensive glycan receptor patch at the cell surface. Our findings indicate that glycan-targeting pathogens may exploit the biophysical and biomechanical properties of mucins to overcome the mucosal glycocalyx barrier. SignificanceLike other animal hosts, humans are constantly challenged by pathogens. This has led to an evolution of physical barriers coating all mucosal tissues, which are most vulnerable to infection. An important part of this defense is a dense brush of large proteins, called mucins, which are heavily decorated with sugars and keep pathogens at bay. Deciphering how pathogens overcome the mucin barrier is necessary to understand early stages of infection and to develop more effective treatments. By artificially installing the mucin-like shield on the surfaces of cells using synthetic sugar-bearing polymers, we have discovered a new physical mechanism by which proteins and viruses can exploit this barrier to more strongly adhere to their targets.

microbiology↗

Mucin-mimetic glycan arrays integrating machine learning for analyzing receptor pattern recognition by influenza A viruses

Influenza A viruses (IAVs) exploit host glycans in airway epithelial mucosa to gain entry and initiate infection. Rapid detection of changes in IAV specificity towards host glycan classes can provide early indication of virus transmissibility and infection potential. IAVs use hemagglutinins (HA) to bind sialic acids linked to larger glycan structures and a switch in HA specificity from 2,3-to 2,6-linked sialoglycans is considered a prerequisite for viral transmission from birds to humans. While the changes in HA structure associated with the evolution of binding phenotype have been mapped, the influence of glycan receptor presentation on IAV specificity remains obscured. Here, we describe a glycan array platform which uses synthetic mimetics of mucin glycoproteins to model how receptor presentation in the mucinous glycocalyx, including glycan type and valency of the glycoconjugates and their surface density, impact IAV binding. We found that H1N1 virus produced in embryonated chicken eggs, which recognizes both receptor types, exclusively engaged mucin-mimetics carrying 2,3-linked sialic acids in their soluble form. The virus was able utilize both receptor structures when the probes were immobilized on the array; however, increasing density in the mucin-mimetic brush diminished viral adhesion. Propagation in mammalian cells produced a change in receptor pattern recognition by the virus, without altering its HA affinity, toward improved binding of 2,6-sialylated mucin mimetics and reduced sensitivity to surface crowding of the probes. Application of a support vector machine (SVM) learning algorithm as part of the glycan array binding analysis efficiently characterized this shift in binding preference and may prove useful to study the evolution of viral responses to a new host.

microbiology↗

Hemagglutinin Glycan Clock Guides Human Influenza A Virus Evolution

Adaptive immunity to influenza A virus is limited by frequent mutations in the immunodominant head of hemagglutinin (HA). Over the last century, the upward trend in HA-head glycosylation indicates glycan addition can increase fitness, but its role in viral evolution remains unclear. Here, we report glycan evolution follows a clock-like rhythm, pacing the timeline, trajectory, and replacement of HA. Following pandemic introduction, glycans are added to HA at 4- to 6-year intervals, until a functional glycan limit is reached, after which, at 9- to 12-year intervals, glycans are either swapped between different sites, or the HA is replaced by a novel pandemic virus. Using this, we predicted the appearance of the newest glycan on pH1N1 HA. Phylogeographic reconstruction suggests these highly fit strains originated in the Middle East, before rapidly replacing all strains globally. Going forward, we can use this simple algorithm to forecast future glycan evolution and identify seasons with higher pandemic potential.

microbiology↗