Silica-Biomacromolecule Interactions: Toward a Mechanistic Understanding of Silicification

Abstract

Silica-organic composites are receiving renewed attention for their versatility and environmentally benign compositions. Of particular interest is how macromolecules interact with aqueous silica to produce functional materials that confer remarkable physical properties to living organisms. This Review first examines silicification in organisms and the biomacromolecule properties proposed to modulate these reactions. We then highlight findings from silicification studies organized by major classes of biomacromolecules. Most investigations are qualitative, using disparate experimental and analytical methods and minimally characterized materials. Many findings are contradictory and, altogether, demonstrate that a consistent picture of biomacromolecule-Si interactions has not emerged. However, the collective evidence shows that functional groups, rather than molecular classes, are key to understanding macromolecule controls on mineralization. With recent advances in biopolymer chemistry, there are new opportunities for hypothesis-based studies that use quantitative experimental methods to decipher how macromolecule functional group chemistry and configuration influence thermodynamic and kinetic barriers to silicification. Harnessing the principles of silica-macromolecule interactions holds promise for biocomposites with specialized applications from biomedical and clean energy industries to other material-dependent industries.

Figure 1

Diverse organisms produce biosilica as organic-SiO₂ composites.⁻ Most structures serve protective or structural functions. “n.d.” indicates “not determined”.

Figure 2

Average silica concentration in the ocean shows that the early ocean was near equilibrium with respect to amorphous silica. Silica levels began to decline and then plateaued with the evolution of radiolarians and glass sponges (550–200 Ma). Upon the emergence of diatoms (at ∼75 Ma), silica levels decreased sharply to present-day levels (after Conley et al., 2017).

Figure 3

An understanding of silicification processes holds promise for diverse translational opportunities as illustrated by this “Rosetta Stone” of potential applications.

Figure 4

Nomenclature of silicic acid species that can occur in solution (monomer to oligomer). The Q_n convention refers to the number of Si units attached (through the oxygen) to an adjacent Si atom. Thus, Q_n refers to Si(OSi)_n(OH)_4–n where n equals 0, 1, 2, 3, or 4. Q_n notation is represented by the silicon atom in pink. The Q_n convention is widely used in ²⁹Si NMR.

Figure 5

A simple representation of the common nomenclature for the formation of higher order silica structures in inorganic systems (sols, gels, and aggregates) provides a visualization for discussions herein (after Wilhelm and Kind, 2015).

Figure 6

Hierarchical structures of diatoms including the (A) view of valve and girdle of Endyctia sp.; (B) central part of diatom internal frustule of Endyctia sp.; (C) outer side of valve of Coscinodiscus sp.; (D) inner side of valve of Coscinodiscus sp. Reprinted with permission under a Creative Commons Attribution 4.0 International License from ref (214). Copyright 2021 Springer Nature.

Figure 7

Schematic of diatom frustrule structure and methods for extracting organic molecules. (A) Frustule components and cytoskeleton. Silica is the midgray color surrounding the components, and some proteins are represented by the light and dark gray globules. (B) Detergent treatments remove cytoskeleton and silicalemma and most silicalemma TM proteins. (C) Acid treatment removes all organic material that is external to the silica. Some embedded materials are thought to remain, protected by the silica. (D) Frustules are extracted by both detergent and ammonium fluoride. Most organics are extracted, leaving the AFIM, which includes molecules such as polysaccharides. Reprinted with permission under a Creative Commons Attribution 4.0 International license from ref (34). Copyright 2018 Frontiers Media S.A.

Figure 8

Diatom Silaffin-1A₁ from C. fusiformis(68) shows backbone and post-translational zwitterionic functionalization: anionic phosphate groups (green) and cationic polyamines (nitrogen molecules in pink) (after Kröger et al., 2001).

Figure 9

LCPA structures extracted from diatoms. (A) Free amines from a C. wailesii diatom frustule. LCPAs can be methylated or unmethylated. (B) LCPAs can be bound to a protein via a lysine residue (E. zodiacus and T. pseudonana polyamines shown), and polyamines can be charged or neutral (after Falciatore et al., 2022).

Figure 10

Simplified representation of the diatom silica deposition vesicle (SDV) lumen illustrates the interactions between LCPAs (red cationic chains) or silaffins (red and black zwitterionic moieties) with the phosphorylated serine residues (black anionic chains) of silicalemma-associated proteins (SAPs). Charged chains are suspected to interact with one another within the SDV (after Hildebrand et al., 2018).

Figure 11

Molecular modeling of supramolecular architecture of biosilica (silica in red and yellow) with polyamines (blue, gray, and white) embedded in the 40–80 nm thick silica frustule. Proteins and carbohydrates (represented as purple and green) cover the silica as a 3 nm layer. Reproduced with permission from ref (72). Copyright 2015 John/Wiley & Sons, Inc.

Figure 12

(A) Representation of α-chitin and higher order folding due to intermolecular interactions. Chains are aligned in the same orientation. (B) Representation of β-chitin and higher order folding intermolecular interactions. Chains are aligned in opposing orientations.

Figure 13

Simplified illustration of sponge spicule formation and extrusion from the sclerocyte. The process begins with the uptake of monosilicic acid by the cell. Subsequent condensation occurs in a vesicle before maturation and release as a biosilica spicule (after Müller et al., 2005.

Figure 14

Depiction of hypothesis for silicatein-catalyzed silicification. (A) Hydrolysis of TEOS by silicatein. Ser-25 and His-163 bind via hydrogen bonding, and then, the Ser-25 oxygen attacks electrophilic Si of TEOS. The reaction concertedly extracts serine’s proton and leaves serine bound to TEOS and a water molecule hydrogen bound to histidine. The process is repeated to hydrolyze ethanol from TEOS. (B) Ser-25 and His-163 hydrogen bond before serine’s oxygen attacks monosilicic acid’s electrophilic Si, which concertedly extracts serine’s proton. The process is repeated with a second monosilicic acid molecule, forming a dimer (after Povarova et al., 2018).

Figure 15

Proposed associations of siliplant proteins with silicic acid species. Electrostatic binding between lysine (pink) and phosphates (green) is likely, as are hydrogen bonds formed between silicic acids or silica with phosphate groups (after Adiram-Filiba et al., 2020).

Figure 16

Relative first order rate constants for the transition from trisilicic acid to oligomers in the presence of three proteins. The dissolution rate constant (k_–) is higher than the forward first order rate constant (k₊), slowing the net rate of silicification (30 mM Si) in the presence of the macromolecules tested (after Canabady-Rochelle et al., 2012).

Figure 17

Structural differences between a peptide and a peptoid with examples of side chain similarities.

Figure 18

R5 peptide and the synthesized peptidomimetics used by Torkelson et al. to study silicification. R5 Peptoid is also discussed as toidR5A, and R5 Peptoid-2 is the reverse analogue of toidR5A.

Figure 19

SEM images of silicification products (scale bar = 1 μm) in the presence of 3 mM (top row) or 1 mM (bottom row) of the peptoid toidR5A (left column) or the R5 peptide (right column). Each graph represents distributions of particle sizes based on n = 30 particles. Reproduced from ref (132). Copyright 2024 American Chemical Society.

Figure 20

Studies of phosphate-polyamine-directed silicification at pH 5.5. (A) An increase in the absorbance correlates with an increase in precipitated silica. Concentration of formed silica determined via the beta-silicomolybdate method in the presence of polyamines with sodium acetate and silicic acid (green), polyamines added to premixed silicic acid with sodium phosphate (orange), polyamines, sodium phosphate, and silicic acid mixed at t = 0 (purple) (after Sumper et al. 2003). (B) Larger silica spheres, and increasing nmol of total silica precipitates, form in the presence of polyamines with increasing concentrations of phosphates in the form of silacidin (after Wenzl et al. 2008).

Figure 21

Depiction of how the chitosan concentration and solution pH affect silica formation. At pH 5–6, more of a gel-like structure is formed. Higher chitosan concentrations produce denser composite networks. At pH 6.5–8.5, large particles form in the absence of local chitosan and high local chitosan sterically hinders silica formation producing smaller particles. At pH 9, chitosan phase separates, leading to the unhindered formation of large particles (after Witoon et al., 2012).

Figure 22

(A) Silicification rate experiments using the Molybdenum Blue method: Control without additive (blue), chitin (red), and PAH (green). (B) ²⁹Si NMR spectra collected at 480 min of reaction time show the evolution of Q species in solution. Adapted from ref (162). Copyright 2011 American Chemical Society.

Figure 23

Simplified depiction of chitin–silica interactions. Hydrogen bonds are shown between the silica hydroxy groups and the hydroxy and amide groups on chitin. Reproduced with permission from ref (163). Copyright 2013 Elsevier S.A.

Figure 24

AFM investigation of silica precipitation onto patterned surface with alternating stripes of carboxyl- and amine-functional groups (A) before treatment and (B) after silicification. Most silica is deposited at the interface between carboxyl and amine groups. Conditions for this work are pH 5, σ = 2.14, and T = 25 °C. Reproduced from ref (51). Copyright 2009 American Chemical Society.

Figure 25

Representation of the free energy of nucleus formation per molecule (Δg_s + Δg_b, orange) surface free energy change per molecule (Δg_s, green), and bulk free energy change per molecule (Δg_b, purple) versus critical radius, r_c.

Figure 26

Measurements of silica nucleation induction times estimated per the Makrides-Turner-Slaughter (MTS) model as the natural log of the induction time (τ) versus the reciprocal of supersaturation squared (1/σ²). Fitting the MTS model to the data, the interfacial free energy (thermodynamic barrier) is extracted from the slope, and the kinetic barrier to silicification is determined from the y-intercept. Control experiments are represented by open diamonds, and filled diamonds represent the additive treatments. Organic acids reduce the kinetic barrier to silicification without affecting reaction thermodynamics: (A) Lysine, (B) Aspartic acid, and (C) Citric acid. In contrast, NaCl (D) enhances the rate by decreasing the thermodynamic barrier to nucleation (see also Figure 25) (after Dove et al., 2019).

Figure 27

Free energy barrier to nucleation decreases with increasing supersaturation, as predicted by theory. Experimental measurements show NaCl reduces the thermodynamic barrier to nucleation independent of the organic acid in solution (after Dove et al., 2019).

Figure 28

There are many applications for chitosan–silica composites. The outstanding properties of these sustainable materials hold promise for expanding their usage into new fields as we build a stronger understanding of biosilicification in molecular settings.