Non-consecutive enzyme interactions within TCA cycle supramolecular assembly regulate carbon-nitrogen metabolism.

Enzymes of the central metabolism tend to assemble into transient supramolecular complexes. However, the functional significance of the interactions, particularly between enzymes catalyzing non-consecutive reactions, remains unclear. Here, by co-localizing two non-consecutive enzymes of the TCA cycle from Bacillus subtilis, malate dehydrogenase (MDH) and isocitrate dehydrogenase (ICD), in phase separated droplets we show that MDH-ICD interaction leads to enzyme agglomeration with a concomitant enhancement of ICD catalytic rate and an apparent sequestration of its reaction product, 2-oxoglutarate. Theory demonstrates that MDH-mediated clustering of ICD molecules explains the observed phenomena. In vivo analyses reveal that MDH overexpression leads to accumulation of 2-oxoglutarate and reduction of fluxes flowing through both the catabolic and anabolic branches of the carbon-nitrogen intersection occupied by 2-oxoglutarate, resulting in impeded ammonium assimilation and reduced biomass production. Our findings suggest that the MDH-ICD interaction is an important coordinator of carbon-nitrogen metabolism.

Chemotactic Interactions Drive Migration of Membraneless Active Droplets.

In nature, chemotactic interactions are ubiquitous and play a critical role in driving the collective behavior of living organisms. Reproducing these interactions in vitro is still a paramount challenge due to the complexity of mimicking and controlling cellular features, such as tangled metabolic networks, cytosolic macromolecular crowding, and cellular migration, on a microorganism size scale. Here, we generate enzymatically active cell-sized droplets able to move freely, and by following a chemical gradient, able to interact with the surrounding droplets in a collective manner. The enzyme within the droplets generates a pH gradient that extends outside the edge of the droplets. We discovered that the external pH gradient triggers droplet migration and controls its directionality, which is selectively toward the neighboring droplets. Hence, by changing the enzyme activity inside the droplet, we tuned the droplet migration speed. Furthermore, we showed that these cellular-like features can facilitate the reconstitution of a simple and linear protometabolic pathway and increase the final reaction product generation. Our work suggests that simple and stable membraneless droplets can reproduce complex biological phenomena, opening new perspectives as bioinspired materials and synthetic biology tools.

Remote loop evolution reveals a complex biological function for chitinase enzymes beyond the active site.

Loops are small secondary structural elements that play a crucial role in the emergence of new enzyme functions. However, the evolutionary molecular mechanisms how proteins acquire these loop elements and obtain new function is poorly understood. To address this question, we study glycoside hydrolase family 19 (GH19) chitinase-an essential enzyme family for pathogen degradation in plants. By revealing the evolutionary history and loops appearance of GH19 chitinase, we discover that one loop which is remote from the catalytic site, is necessary to acquire the new antifungal activity. We demonstrate that this remote loop directly accesses the fungal cell wall, and surprisingly, it needs to adopt a defined structure supported by long-range intramolecular interactions to perform its function. Our findings prove that nature applies this strategy at the molecular level to achieve a complex biological function while maintaining the original activity in the catalytic pocket, suggesting an alternative way to design new enzyme function.

Nucleoside-Driven Specificity of DNA Methyltransferase.

We have studied the adenosine binding specificities of two bacterial DNA methyltransferases, Taq methyltransferase (M.TaqI), and HhaI methyltransferase (M.HhaI). While they have similar cofactor binding pocket interactions, experimental data showed different specificity for novel S-nucleobase-l-methionine cofactors (SNMs; N=guanosyl, cytidyl, uridyl). Protein dynamics corroborate the experimental data on the cofactor specificities. For M.TaqI the specificity for S-adenosyl-l-methionine (SAM) is governed by the tight binding on the nucleoside part of the cofactor, while for M.HhaI the degree of freedom of the nucleoside chain allows the acceptance of other bases. The experimental data prove catalytically productive methylation by the M.HhaI binding pocket for all the SNMs. Our results suggest a new route for successful design of unnatural SNM analogues for methyltransferases as a tool for cofactor engineering.

Efficient Exploration of Sequence Space by Sequence-Guided Protein Engineering and Design.

The rapid growth of sequence databases over the past two decades means that protein engineers faced with optimizing a protein for any given task will often have immediate access to a vast number of related protein sequences. These sequences encode information about the evolutionary history of the protein and the underlying sequence requirements to produce folded, stable, and functional protein variants. Methods that can take advantage of this information are an increasingly important part of the protein engineering tool kit. In this Perspective, we discuss the utility of sequence data in protein engineering and design, focusing on recent advances in three main areas: the use of ancestral sequence reconstruction as an engineering tool to generate thermostable and multifunctional proteins, the use of sequence data to guide engineering of multipoint mutants by structure-based computational protein design, and the use of unlabeled sequence data for unsupervised and semisupervised machine learning, allowing the generation of diverse and functional protein sequences in unexplored regions of sequence space. Altogether, these methods enable the rapid exploration of sequence space within regions enriched with functional proteins and therefore have great potential for accelerating the engineering of stable, functional, and diverse proteins for industrial and biomedical applications.

Insertions and deletions mediated functional divergence of Rossmann fold enzymes.

Nucleobase-containing coenzymes are hypothesized to be relics of an early RNA-based world that preceded the emergence of proteins. Despite the importance of coenzyme-protein synergisms, their emergence and evolution remain understudied. An excellent target to address this issue is the Rossmann fold, the most catalytically diverse and abundant protein architecture in nature. We investigated two main Rossmann lineages: the nicotinamide adenine dinucleotide phosphate (NAD(P)) and the S-adenosyl methionine (SAM)- binding superfamilies. To identify the evolutionary changes that lead to a coenzyme specificity switch on these superfamilies, we performed structural and sequence-based Hidden Markov model analysis to systematically search for key motifs in their coenzyme-binding pockets. Our analyses revealed that through insertions and deletions (InDels) and a residue substitution, the ancient ß1-loop-α1 coenzyme-binding structure of NAD(P) could be reshaped into the SAM-binding ß1-loop-α1 structure. To experimentally prove this obsevation, we removed three amino acids from the NAD(P)-binding pocket and solved the structure of the resulting mutant, revealing the characteristic loop features of the SAM-binding pocket. To confirm the binding to SAM, we performed isothermal titration calorimetry measurements. Molecular dynamics simulations also corroborated the role of InDels in abolishing NAD binding and acquiring SAM binding. Our results uncovered how nature may have utilized insertions and deletions to optimize the different coenzyme-binding pockets and the distinct functionalities observed for Rossmann superfamilies. This work also proposes a general mechanism by which protein templates could have been recycled through the course of evolution to adopt different coenzymes and confer distinct chemistries.

Mechanisms of protein evolution.

How do proteins evolve? How do changes in sequence mediate changes in protein structure, and in turn in function? This question has multiple angles, ranging from biochemistry and biophysics to evolutionary biology. This review provides a brief integrated view of some key mechanistic aspects of protein evolution. First, we explain how protein evolution is primarily driven by randomly acquired genetic mutations and selection for function, and how these mutations can even give rise to completely new folds. Then, we also comment on how phenotypic protein variability, including promiscuity, transcriptional and translational errors, may also accelerate this process, possibly via "plasticity-first" mechanisms. Finally, we highlight open questions in the field of protein evolution, with respect to the emergence of more sophisticated protein systems such as protein complexes, pathways, and the emergence of pre-LUCA enzymes.

Structural dynamics shape the fitness window of alanine:glyoxylate aminotransferase.

The conformational landscape of a protein is constantly expanded by genetic variations that have a minimal impact on the function(s) while causing subtle effects on protein structure. The wider the conformational space sampled by these variants, the higher the probabilities to adapt to changes in environmental conditions. However, the probability that a single mutation may result in a pathogenic phenotype also increases. Here we present a paradigmatic example of how protein evolution balances structural stability and dynamics to maximize protein adaptability and preserve protein fitness. We took advantage of known genetic variations of human alanine:glyoxylate aminotransferase (AGT1), which is present as a common major allelic form (AGT-Ma) and a minor polymorphic form (AGT-Mi) expressed in 20% of Caucasian population. By integrating crystallographic studies and molecular dynamics simulations, we show that AGT-Ma is endowed with structurally unstable (frustrated) regions, which become disordered in AGT-Mi. An in-depth biochemical characterization of variants from an anticonsensus library, encompassing the frustrated regions, correlates this plasticity to a fitness window defined by AGT-Ma and AGT-Mi. Finally, co-immunoprecipitation analysis suggests that structural frustration in AGT1 could favor additional functions related to protein-protein interactions. These results expand our understanding of protein structural evolution by establishing that naturally occurring genetic variations tip the balance between stability and frustration to maximize the ensemble of conformations falling within a well-defined fitness window, thus expanding the adaptability potential of the protein.

Inter-paralog amino acid inversion events in large phylogenies of duplicated proteins.

Connecting protein sequence to function is becoming increasingly relevant since high-throughput sequencing studies accumulate large amounts of genomic data. In order to go beyond the existing database annotation, it is fundamental to understand the mechanisms underlying functional inheritance and divergence. If the homology relationship between proteins is known, can we determine whether the function diverged? In this work, we analyze different possibilities of protein sequence evolution after gene duplication and identify "inter-paralog inversions", i.e., sites where the relationship between the ancestry and the functional signal is decoupled. The amino acids in these sites are masked from being recognized by other prediction tools. Still, they play a role in functional divergence and could indicate a shift in protein function. We develop a method to specifically recognize inter-paralog amino acid inversions in a phylogeny and test it on real and simulated datasets. In a dataset built from the Epidermal Growth Factor Receptor (EGFR) sequences found in 88 fish species, we identify 19 amino acid sites that went through inversion after gene duplication, mostly located at the ligand-binding extracellular domain. Our work uncovers an outcome of protein duplications with direct implications in protein functional annotation and sequence evolution. The developed method is optimized to work with large protein datasets and can be readily included in a targeted protein analysis pipeline.

Correction to "Substrate Dynamics Contribute to Enzymatic Specificity in Human and Bacterial Methionine Adenosyltransferases".

[This corrects the article DOI: 10.1021/jacsau.1c00464.].

Implications of divergence of methionine adenosyltransferase in archaea.

Methionine adenosyltransferase (MAT) catalyzes the biosynthesis of S-adenosyl methionine from l-methionine and ATP. MAT enzymes are ancient, believed to share a common ancestor, and are highly conserved in all three domains of life. However, the sequences of archaeal MATs show considerable divergence compared with their bacterial and eukaryotic counterparts. Furthermore, the structural significance and functional significance of this sequence divergence are not well understood. In the present study, we employed structural analysis and ancestral sequence reconstruction to investigate archaeal MAT divergence. We observed that the dimer interface containing the active site (which is usually well conserved) diverged considerably between the bacterial/eukaryotic MATs and archaeal MAT. A detailed investigation of the available structures supports the sequence analysis outcome: The protein domains and subdomains of bacterial and eukaryotic MAT are more similar than those of archaea. Finally, we resurrected archaeal MAT ancestors. Interestingly, archaeal MAT ancestors show substrate specificity, which is lost during evolution. This observation supports the hypothesis of a common MAT ancestor for the three domains of life. In conclusion, we have demonstrated that archaeal MAT is an ideal system for studying an enzyme family that evolved differently in one domain compared with others while maintaining the same catalytic activity.

Evolutionary repair reveals an unexpected role of the tRNA modification m1G37 in aminoacylation.

The tRNA modification m1G37, introduced by the tRNA methyltransferase TrmD, is thought to be essential for growth in bacteria because it suppresses translational frameshift errors at proline codons. However, because bacteria can tolerate high levels of mistranslation, it is unclear why loss of m1G37 is not tolerated. Here, we addressed this question through experimental evolution of trmD mutant strains of Escherichia coli. Surprisingly, trmD mutant strains were viable even if the m1G37 modification was completely abolished, and showed rapid recovery of growth rate, mainly via duplication or mutation of the proline-tRNA ligase gene proS. Growth assays and in vitro aminoacylation assays showed that G37-unmodified tRNAPro is aminoacylated less efficiently than m1G37-modified tRNAPro, and that growth of trmD mutant strains can be largely restored by single mutations in proS that restore aminoacylation of G37-unmodified tRNAPro. These results show that inefficient aminoacylation of tRNAPro is the main reason for growth defects observed in trmD mutant strains and that proS may act as a gatekeeper of translational accuracy, preventing the use of error-prone unmodified tRNAPro in translation. Our work shows the utility of experimental evolution for uncovering the hidden functions of essential genes and has implications for the development of antibiotics targeting TrmD.

Sustained enzymatic activity and flow in crowded protein droplets.

Living cells harvest energy from their environments to drive the chemical processes that enable life. We introduce a minimal system that operates at similar protein concentrations, metabolic densities, and length scales as living cells. This approach takes advantage of the tendency of phase-separated protein droplets to strongly partition enzymes, while presenting minimal barriers to transport of small molecules across their interface. By dispersing these microreactors in a reservoir of substrate-loaded buffer, we achieve steady states at metabolic densities that match those of the hungriest microorganisms. We further demonstrate the formation of steady pH gradients, capable of driving microscopic flows. Our approach enables the investigation of the function of diverse enzymes in environments that mimic cytoplasm, and provides a flexible platform for studying the collective behavior of matter driven far from equilibrium.

Binding of single-mutant epidermal growth factor (EGF) ligands alters the stability of the EGF receptor dimer and promotes growth signaling.

The epidermal growth factor receptor (EGFR) is a membrane-anchored tyrosine kinase that is able to selectively respond to multiple extracellular stimuli. Previous studies have indicated that the modularity of this system may be caused by ligand-induced differences in the stability of the receptor dimer. However, this hypothesis has not been explored using single-mutant ligands thus far. Herein, we developed a new approach to identify residues responsible for functional divergence by selecting residues in the epidermal growth factor (EGF) ligand that are conserved among orthologs yet divergent between paralogs. Then, we mutated these residues and assessed the mutants' effects on the receptor using a combination of molecular dynamics (MD) and biochemical techniques. Although the EGF mutants had binding affinities for the EGFR comparable with the WT ligand, the EGF mutants showed differential patterns of receptor phosphorylation and cell growth in multiple cell lines. The MD simulations of the EGF mutants indicated that mutations had long-range effects on the receptor dimer interface. This study shows for the first time that a single mutation in the EGF is sufficient to alter the activation of the EGFR signaling pathway at the cellular level. These results also support that biased ligand-receptor signaling in the tyrosine kinase receptor system can lead to differential downstream outcomes and demonstrate a promising new method to study ligand-receptor interactions.

Substrate Dynamics Contribute to Enzymatic Specificity in Human and Bacterial Methionine Adenosyltransferases.

Protein conformational changes can facilitate the binding of noncognate substrates and underlying promiscuous activities. However, the contribution of substrate conformational dynamics to this process is comparatively poorly understood. Here, we analyze human (hMAT2A) and Escherichia coli (eMAT) methionine adenosyltransferases that have identical active sites but different substrate specificity. In the promiscuous hMAT2A, noncognate substrates bind in a stable conformation to allow catalysis. In contrast, noncognate substrates sample stable productive binding modes less frequently in eMAT owing to altered mobility in the enzyme active site. Different cellular concentrations of substrates likely drove the evolutionary divergence of substrate specificity in these orthologues. The observation of catalytic promiscuity in hMAT2A led to the detection of a new human metabolite, methyl thioguanosine, that is produced at elevated levels in a cancer cell line. This work establishes that identical active sites can result in different substrate specificity owing to the effects of substrate and enzyme dynamics.

Non-enzymatic and highly sensitive lactose detection utilizing graphene field-effect transistors.

Field-effect transistor (FET) biosensors based on low-dimensional materials are capable of highly sensitive and specific label-free detection of various analytes. In this work, a FET biosensor based on graphene decorated with gold nanoparticles (Au NPs) was fabricated for lactose detection in a liquid-gate measurement configuration. This graphene device is functionalized with a carbohydrate recognition domain (CRD) of the human galectin-3 (hGal-3) protein to detect the presence of lactose from the donor effect of lectin - glycan affinity binding on the graphene. Although the detection of lactose is important because of its ubiquitous presence in food and for disease related applications (lactose intolerance condition), in this work we exploit the lectin/carbohydrate interaction to develop a device that in principle could specifically detect very low concentrations of any carbohydrate. The biosensor achieved an effective response to lactose concentrations over a dynamic range from 1 fM to 1 pM (10-15 to 10-12 mol L-1) with a detection limit of 200 aM, a significant enhancement over previous electrochemical graphene devices. The FET sensor response is also specific to lactose at aM concentrations, indicating the potential of a combined lectin and graphene FET (G-FET) sensor to detect carbohydrates at high sensitivity and specificity for disease diagnosis.

Cycloserine enantiomers are reversible inhibitors of human alanine:glyoxylate aminotransferase: implications for Primary Hyperoxaluria type 1.

Peroxisomal alanine:glyoxylate aminotransferase (AGT) is responsible for glyoxylate detoxification in human liver and utilizes pyridoxal 5'-phosphate (PLP) as coenzyme. The deficit of AGT leads to Primary Hyperoxaluria Type I (PH1), a rare disease characterized by calcium oxalate stones deposition in the urinary tract as a consequence of glyoxylate accumulation. Most missense mutations cause AGT misfolding, as in the case of the G41R, which induces aggregation and proteolytic degradation. We have investigated the interaction of wild-type AGT and the pathogenic G41R variant with d-cycloserine (DCS, commercialized as Seromycin), a natural product used as a second-line treatment of multidrug-resistant tuberculosis, and its synthetic enantiomer l-cycloserine (LCS). In contrast with evidences previously reported on other PLP-enzymes, both ligands are AGT reversible inhibitors showing inhibition constants in the micromolar range. While LCS undergoes half-transamination generating a ketimine intermediate and behaves as a classical competitive inhibitor, DCS displays a time-dependent binding mainly generating an oxime intermediate. Using a mammalian cellular model, we found that DCS, but not LCS, is able to promote the correct folding of the G41R variant, as revealed by its increased specific activity and expression as a soluble protein. This effect also translates into an increased glyoxylate detoxification ability of cells expressing the variant upon treatment with DCS. Overall, our findings establish that DCS could play a role as pharmacological chaperone, thus suggesting a new line of intervention against PH1 based on a drug repositioning approach. To a widest extent, this strategy could be applied to other disease-causing mutations leading to AGT misfolding.

Rossmann-Fold Methyltransferases: Taking a "ß-Turn" around Their Cofactor, S-Adenosylmethionine.

Methyltransferases (MTases) are superfamilies of enzymes that catalyze the transfer of a methyl group from S-adenosylmethionine (SAM), a nucleoside-based cofactor, to a wide variety of substrates such as DNA, RNA, proteins, small molecules, and lipids. Depending upon their structural features, the MTases can be further classified into different classes; we consider exclusively the largest class of MTases, the Rossmann-fold MTases. It has been shown that the nucleoside cofactor-binding Rossmann enzymes, particularly the nicotinamide adenine dinucleotide (NAD)-, flavin adenine dinucleotide (FAD)-, and SAM-binding MTases enzymes, share common binding motifs that include a Gly-rich loop region that interacts with the cofactor and a highly conserved acidic residue (Asp/Glu) that interacts with the ribose moiety of the cofactor. Here, we observe that the Gly-rich loop region of the Rossmann MTases adapts a specific type II' ß-turn in the proximity of the cofactor (<4 Å), and it appears to be a key feature of these superfamilies. Additionally, we demonstrate that the conservation of this ß-turn could play a critical role in the enzyme-cofactor interaction, thereby shedding new light on the structural conformation of the Gly-rich loop region from Rossmann MTases.