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Hyaluronan (HA), the essential [-3-GlcNAc-1-β-4-GlcA-1-β-]n matrix polysaccharide in vertebrates and molecular camouflage coating in select pathogens, is polymerized by “HA synthase” (HAS) enzymes. The first HAS identified three decades ago opened the window for new insights and biotechnological tools. This review discusses current understanding of HA biosynthesis, its biotechnological utility, and addresses some misconceptions in the literature.

HASs are fascinating enzymes that polymerize two different UDP-activated sugars via different glycosidic linkages. Therefore, these catalysts were the first examples to break the “one enzyme/one sugar transferred” dogma. Three distinct types of these bifunctional glycosyltransferases (GTs) with disparate architectures and reaction modes are known. Based on biochemical and structural work, we present an updated classification system. Class I membrane-integrated HASs employ a processive chain elongation mechanism and secrete HA across the plasma membrane. This complex operation is accomplished by functionally integrating a cytosolic catalytic domain with a channel-forming transmembrane region. Class I enzymes, containing a single GT family-2 (GT-2) module that adds both monosaccharide units to the nascent chain, are further subdivided into two groups that construct the polymer with opposite molecular directionalities: Class I-R and I-NR elongate the HA polysaccharide at either the reducing or the non-reducing end, respectively. In contrast, Class II HASs are membrane-associated peripheral synthases with a non-processive, non-reducing end elongation mechanism using two independent GT-2 modules (one for each type of monosaccharide) and require a separate secretion system for HA export. We discuss recent mechanistic insights into HA biosynthesis that promise biotechnological benefits and exciting engineering approaches.

 

We propose a design paradigm for multistate machines where transitions from one state to another are organized by bifurcations of multiple equilibria of the energy landscape describing the collective interactions of the machine components. This design paradigm is attractive since, near bifurcations, small variations in a few control parameters can result in large changes to the system’s state providing an emergent lever mechanism. Further, the topological configuration of transitions between states near such bifurcations ensures robust operation, making the machine less sensitive to fabrication errors and noise. To design such machines, we develop and implement a new efficient algorithm that searches for interactions between the machine components that give rise to energy landscapes with these bifurcation structures. We demonstrate a proof of concept for this approach by designing magnetoelastic machines whose motions are primarily guided by their magnetic energy landscapes and show that by operating near bifurcations we can achieve multiple transition pathways between states. This proof of concept demonstration illustrates the power of this approach, which could be especially useful for soft robotics and at the microscale where typical macroscale designs are difficult to implement.

 

Poor oral health is associated with cardiovascular disease and dementia. Potential pathways include sepsis from oral bacteria, systemic inflammation, and nutritional deficiencies. However, in post-industrialized populations, links between oral health and chronic disease may be confounded because the lower socioeconomic exposome (poor diet, pollution, and low physical activity) often entails insufficient dental care. We assessed tooth loss, caries, and damaged teeth, in relation to cardiovascular and brain aging among the Tsimane, a subsistence population living a relatively traditional forager-horticulturalist lifestyle with poor dental health, but minimal cardiovascular disease and dementia. Dental health was assessed by a physician in 739 participants aged 40–92 years with cardiac and brain health measured by chest computed tomography (CT; n = 728) and brain CT (n = 605). A subset of 356 individuals aged 60+ were also assessed for dementia and mild cognitive impairment (n = 33 impaired). Tooth loss was highly prevalent, with 2.2 teeth lost per decade and a 2-fold greater loss in women. The number of teeth with exposed pulp was associated with higher inflammation, as measured by cytokine levels and white blood cell counts, and lower body mass index. Coronary artery calcium and thoracic aortic calcium were not associated with tooth loss or damaged teeth. However, aortic valve calcification and brain tissue loss were higher in those who had more teeth with exposed pulp. Overall, these results suggest that dental health is associated with indicators of chronic diseases in the absence of typical confounds, even in a population with low cardiovascular and dementia risk factors.

 

We analyzed a population-based cohort ( N = 10,922) to investigate the onset and stability of racial and ethnic disparities in advanced (i.e., above the 90 th percentile) science and mathematics achievement during elementary school as well as the antecedent, opportunity, and propensity factors that explained these disparities. About 13% to 16% of White students versus 3% to 4% of Black or Hispanic students displayed advanced science or mathematics achievement during kindergarten. The antecedent factor of family socioeconomic status and the propensity factors of student science, mathematics, and reading achievement by kindergarten consistently explained whether students displayed advanced science or mathematics achievement during first, second, third, fourth, or fifth grade. These and additional factors substantially or fully explained initially observed disparities between Black or Hispanic and White students in advanced science or mathematics achievement during elementary school. Economic and educational policies designed to increase racial and ethnic representation in STEM course taking, degree completion, and workforce participation may need to begin by elementary school. 

Biological systems convert chemical energy into mechanical work by using protein catalysts that assume kinetically controlled conformational states. Synthetic chemomechanical systems using chemical catalysis have been reported, but they are slow, require high temperatures to operate, or indirectly perform work by harnessing reaction products in liquids (e.g., heat or protons). Here, we introduce a bioinspired chemical strategy for gas-phase chemomechanical transduction that sequences the elementary steps of catalytic reactions on ultrathin (<10 nm) platinum sheets to generate surface stresses that directly drive microactuation (bending radii of 700 nm) at ambient conditions (T = 20 °C; P total = 1 atm). When fueled by hydrogen gas and either oxygen or ozone gas, we show how kinetically controlled surface states of the catalyst can be exploited to achieve fast actuation (600 ms/cycle) at 20 °C. We also show that the approach can integrate photochemically controlled reactions and can be used to drive the reconfiguration of microhinges and complex origami- and kirigami-based microstructures. 

We present in situ calorimetry, thermal conductivity, and thermal diffusivity measurements of materials using temperature-sensing optical wireless integrated circuits (OWiCs). These microscopic and untethered optical sensors eliminate input wires and reduce parasitic effects. Each OWiC has a mass of ∼100 ng, a 100-μm-scale footprint, and a thermal response time of microseconds. We demonstrate that they can measure the thermal properties of nearly any material, from aerogels to metals, on samples as small as 100 ng and over thermal diffusivities covering four orders of magnitude. They also function over a broad temperature range, and we present proof-of-concept measurements of the thermodynamic phase transitions in both liquid crystal 5CB and gadolinium.