Michael R. Sawaya

Corneal dystrophy is a heterogeneous group of diseases which manifests clinically by progressive corneal opacity and diminishing visual acuity. A group of corneal dystrophies are linked to autosomal dominant mutations in transforming growth factor β–induced protein (TGFBIp) and characterized by extracellular amyloid-positive deposits of unknown molecular structure. Here, we determined the cryogenic-electron microscopy (cryo-EM) structure of amyloid fibrils formed by the TGFBIp FAS1-4 domain with corneal dystrophy–linked mutation V624M. The L569 to N609 fibril core, which includes the Y571-R588 segment enriched in patient corneal deposits, forms symmetrical protofilaments with internal solvent channels. Leveraging this structure, we designed peptide inhibitors intended to bind onto fibril ends to block elongation, targeting the unequal growth of symmetrical protofilaments. Our G1 and H4 inhibitors exhibit concentration-dependent reduction of TGFBIp FAS1-4 aggregation as assessed by Thioflavin T, solubility fractionation, and electron microscopy. Our work illustrates how fibril structures can guide rational inhibitor design and suggests the targeting of protein aggregates as a therapeutic approach for corneal and ocular diseases.

Cellulosomes are large, surface-displayed enzyme complexes that enable anaerobic bacteria to degrade recalcitrant plant polysaccharides, yet cellulosome-expressing bacteria are thought to be rare in the human gut. Here, we show that extensive sequence divergence obscures the detection of many ruminococcal cellulosomes by conventional sequence homology-based methods. Using proteome-scale AlphaFold2 structural predictions, we uncovered a substantially expanded set of putative cellulosome-producing Ruminococcus species, including six previously unrecognized human symbionts. Structure-based clustering identifies several novel cohesin families that retain conserved folds despite extreme sequence divergence and define distinct, phylogenetically conserved cellulosome architectures. The analysis reveals R. callidus and related human symbionts encode elaborate cellulosomes that are invisible to sequence-based annotation. Similarly, R. difficilis , a human gut symbiont, has been found to possess genes for an atypical cohesin-based assembly enriched in amylases and related starch-binding proteins, which may enable this microbe to degrade resistant starches that evade digestion in the upper gastrointestinal tract. Together, these findings reveal that ruminococcal cellulosomes are far more prevalent and diverse than previously appreciated and demonstrate the power of structural proteomics to uncover deeply divergent functional systems in the gut microbiome. IMPORTANCE: Plant cell wall polysaccharides are a major dietary carbon source, yet their degradation relies on rare, highly specialized microbial enzyme assemblies known as cellulosomes, which have long been considered uncommon in the human gut. Using proteome-scale structure prediction combined with experimental validation, we show that cellulosomes are far more widespread and structurally diverse in human-associated Ruminococcus species than previously appreciated. We identify multiple new cohesin families and reveal distinct cellulosome architectures likely adapted to degrade different dietary substrates. Together, these findings redefine the distribution and evolution of cellulosomes in gut microbes and demonstrate the power of structural proteomics to uncover deeply diverged biological systems.

Cellulosomes are large, surface-displayed enzyme complexes that enable anaerobic bacteria to degrade recalcitrant plant polysaccharides, yet cellulosome-expressing bacteria are thought to be rare in the human gut. Here we show that extensive sequence divergence obscures the detection of many ruminococcal cellulosomes by conventional sequence homology-based methods. Using proteome-scale AlphaFold2 structural predictions, we uncovered a substantially expanded set of cellulosome-producing Ruminococcus species, including six previously unrecognized human symbionts. Structure-based clustering identifies several novel cohesin families that retain conserved folds despite extreme sequence divergence and define distinct, phylogenetically conserved cellulosome architectures. The analysis reveals R. callidus and related human symbionts encode elaborate cellulosomes that are invisible to sequence-based annotation. Similarly, R. difficilis , a human gut symbiont, is found to produce an atypical cohesin-based assembly enriched in amylases and related starch-binding proteins that may enable this microbe to degrade resistant starches that evade digestion in the upper gastrointestinal tract. Together, these findings reveal that ruminococcal cellulosomes are far more prevalent and diverse than previously appreciated and demonstrate the power of structural proteomics to uncover deeply divergent functional systems in the gut microbiome. Significance Statement: Plant cell wall polysaccharides are a major dietary carbon source, yet their degradation relies on rare, highly specialized microbial enzyme assemblies known as cellulosomes, which have long appeared uncommon in the human gut. Using proteome-scale structure prediction combined with experimental validation, we show that cellulosomes are far more widespread and structurally diverse in human-associated Ruminococcus species than previously appreciated. We identify multiple new cohesin families and reveal distinct cellulosome architectures likely adapted to degrade different dietary substrates. Together, these findings redefine the distribution and evolution of cellulosomes in gut microbes and demonstrate the power of structural proteomics to uncover deeply diverged biological systems.

Aggregation of the microtubule-binding protein tau is the histopathological hallmark of Alzheimer's disease (AD) and other neurodegenerative diseases, which are collectively known as tauopathies. Tau aggregation in AD patients is correlated with neuron loss, brain atrophy, and cognitive decline, and pro-aggregation tau mutations are sufficient to cause neurodegeneration and dementia in humans and tauopathy model mice. Thus, reversing tau aggregation is a potential therapeutic avenue for AD. In a previous study, we discovered CNS-11, a small molecule that disaggregates AD patient brain-extracted tau fibrils in vitro. In this study, we identify two chemical analogs of CNS-11, named CNS-11D and CNS-11G, that disaggregate AD patient brain-extracted tau fibrils and prevent seeding in a tau aggregation cell culture model. We also demonstrate that 8 weeks of treatment with either CNS-11D or CNS-11G reduces levels of insoluble tau in a mouse model of tauopathy. Our work defines the properties of two small molecules that diminish aggregation of tau in vivo and provides further support for structure-based methods to target tau for treatment of AD.

Herein, we introduce an operationally simple approach for the direct covalent modification of metalloenzymes via Au(III)-mediated S-arylation chemistry. Using a model class of rubredoxin metalloenzymes containing Fe or Ni in the tetrathiolate active site, we show that these biomolecules can be site-selectively tagged with a variety of abiotic functional groups by leveraging a cysteine residue positioned distal to the active site. The bioconjugation proceeds under mild aqueous conditions, rapidly, and in quantitative yields, and most importantly without perturbing the structural or functional integrity of the enzyme, which normally can occur through adventitious demetallation of the active site. Detailed structural studies, including the first reported X-ray crystal structure of a cysteine-arylated metalloprotein, illuminate a clear preference for regioselective arylation at solvent-exposed cysteine residues, offering a blueprint for predictable and programmable bioconjugation in complex biomolecules. This work demonstrates a unique power of “backgroundless” Au(III) arylation chemistry, rendering site-selective bioconjugation of some of the most delicate biomolecules.

The conversion of proteins into insoluble fibrillar aggregates known as amyloid occurs in a wide variety of diseases, e.g., Alzheimer’s disease, amyotrophic lateral sclerosis, systemic transthyretin amyloidosis, and multisystem atrophy. There are more than 60 disease-associated amyloid-forming proteins, and amyloid formation can occur sporadically or can be induced or accelerated by genetic mutations. This Review discusses structural mechanisms by which genetic changes promote amyloid formation and thereby influence disease outcomes. By dividing amyloid-forming proteins into six types according to the genetic mutations they carry and analyzing mutation-induced structural changes in amyloid fibrils, a better understanding of inheritance patterns of amyloid diseases (amyloidoses) can be obtained.

Predicting the amyloid fold and the propensity of peptide segments to adopt amyloid-like structures remain a challenge. However, recent progress has facilitated structure-based prediction of steric zipper propensity and the use of machine learning to accelerate the calculation of predictive models across many scientific areas. Leveraging these advances, we have developed a new approach for rapid proteome-wide assessment of zipper profiles that is informed by four million steric zipper predictions collected over ten years. This collection is used to build a machine learning model capable of rapidly predicting steric zipper propensity, and allowing for the assessment of zippers at both the protein and proteome level. Our predictions show enrichment for zipper forming segments in proteins involved in cell wall reorganization in yeast, highlighting a potential category of interest for experimental characterization. Overall, our predictive model allows for the exploration of amyloid formation across the tree of life and provides a tool for assessment of both novel and designed sequences for zipper density.

With the goal of accelerating the discovery of small molecule–protein complexes, we leverage fast, low-dose, event-based electron counting microcrystal electron diffraction (MicroED) data collection and native mass spectrometry. This approach, which we term electron diffraction with native mass spectrometry (ED-MS), allows assignment of protein target structures bound to ligands with data obtained from crystal slurries soaked with mixtures of known inhibitors and crude biosynthetic reactions. This extends to libraries of printed ligands dispensed directly onto TEM grids for later soaking with microcrystal slurries, and complexes with noncovalent ligands. ED-MS resolves structures of the natural product, epoxide-based cysteine protease inhibitor E-64, and its biosynthetic analogs bound to the model cysteine protease, papain. It further identifies papain binding to its preferred natural products, by showing that two analogs of E-64 outcompete others in binding to papain crystals, and by detecting papain bound to E-64 and an analog from crude biosynthetic reactions, without purification. ED-MS also resolves binding of the CTX-M-14 β-lactamase, a target of active drug development, to the non-β-lactam inhibitor, avibactam, alone or in a cocktail of unrelated compounds. These results illustrate the utility of ED-MS for natural product ligand discovery and for structure-based screening of small molecule binders to macromolecular targets, promising utility for drug discovery.