Slow release of a synthetic auxin induces formation of adventitious roots in recalcitrant woody plants.

Clonal propagation of plants by induction of adventitious roots (ARs) from stem cuttings is a requisite step in breeding programs. A major barrier exists for propagating valuable plants that naturally have low capacity to form ARs. Due to the central role of auxin in organogenesis, indole-3-butyric acid is often used as part of commercial rooting mixtures, yet many recalcitrant plants do not form ARs in response to this treatment. Here we describe the synthesis and screening of a focused library of synthetic auxin conjugates in Eucalyptus grandis cuttings and identify 4-chlorophenoxyacetic acid-L-tryptophan-OMe as a competent enhancer of adventitious rooting in a number of recalcitrant woody plants, including apple and argan. Comprehensive metabolic and functional analyses reveal that this activity is engendered by prolonged auxin signaling due to initial fast uptake and slow release and clearance of the free auxin 4-chlorophenoxyacetic acid. This work highlights the utility of a slow-release strategy for bioactive compounds for more effective plant growth regulation.

What can AlphaFold do for antimicrobial amyloids?

Amyloids, protein, and peptide assemblies in various organisms are crucial in physiological and pathological processes. Their intricate structures, however, present significant challenges, limiting our understanding of their functions, regulatory mechanisms, and potential applications in biomedicine and technology. This study evaluated the AlphaFold2 ColabFold method's structure predictions for antimicrobial amyloids, using eight antimicrobial peptides (AMPs), including those with experimentally determined structures and AMPs known for their distinct amyloidogenic morphological features. Additionally, two well-known human amyloids, amyloid-ß and islet amyloid polypeptide, were included in the analysis due to their disease relevance, short sequences, and antimicrobial properties. Amyloids typically exhibit tightly mated ß-strand sheets forming a cross-ß configuration. However, certain amphipathic α-helical subunits can also form amyloid fibrils adopting a cross-α structure. Some AMPs in the study exhibited a combination of cross-α and cross-ß amyloid fibrils, adding complexity to structure prediction. The results showed that the AlphaFold2 ColabFold models favored α-helical structures in the tested amyloids, successfully predicting the presence of α-helical mated sheets and a hydrophobic core resembling the cross-α configuration. This implies that the AI-based algorithms prefer assemblies of the monomeric state, which was frequently predicted as helical, or capture an α-helical membrane-active form of toxic peptides, which is triggered upon interaction with lipid membranes.

Computational analysis of long-range allosteric communications in CFTR.

Malfunction of the CFTR protein results in cystic fibrosis, one of the most common hereditary diseases. CFTR functions as an anion channel, the gating of which is controlled by long-range allosteric communications. Allostery also has direct bearings on CF treatment: the most effective CFTR drugs modulate its activity allosterically. Herein, we integrated Gaussian network model, transfer entropy, and anisotropic normal mode-Langevin dynamics and investigated the allosteric communications network of CFTR. The results are in remarkable agreement with experimental observations and mutational analysis and provide extensive novel insight. We identified residues that serve as pivotal allosteric sources and transducers, many of which correspond to disease-causing mutations. We find that in the ATP-free form, dynamic fluctuations of the residues that comprise the ATP-binding sites facilitate the initial binding of the nucleotide. Subsequent binding of ATP then brings to the fore and focuses on dynamic fluctuations that were present in a latent and diffuse form in the absence of ATP. We demonstrate that drugs that potentiate CFTR's conductance do so not by directly acting on the gating residues, but rather by mimicking the allosteric signal sent by the ATP-binding sites. We have also uncovered a previously undiscovered allosteric 'hotspot' located proximal to the docking site of the phosphorylated regulatory (R) domain, thereby establishing a molecular foundation for its phosphorylation-dependent excitatory role. This study unveils the molecular underpinnings of allosteric connectivity within CFTR and highlights a novel allosteric 'hotspot' that could serve as a promising target for the development of novel therapeutic interventions.

EvoRator2: Predicting Site-specific Amino Acid Substitutions Based on Protein Structural Information Using Deep Learning.

Multiple sequence alignments (MSAs) are the workhorse of molecular evolution and structural biology research. From MSAs, the amino acids that are tolerated at each site during protein evolution can be inferred. However, little is known regarding the repertoire of tolerated amino acids in proteins when only a few or no sequence homologs are available, such as orphan and de novo designed proteins. Here we present EvoRator2, a deep-learning algorithm trained on over 15,000 protein structures that can predict which amino acids are tolerated at any given site, based exclusively on protein structural information mined from atomic coordinate files. We show that EvoRator2 obtained satisfying results for the prediction of position-weighted scoring matrices (PSSM). We further show that EvoRator2 obtained near state-of-the-art performance on proteins with high quality structures in predicting the effect of mutations in deep mutation scanning (DMS) experiments and that for certain DMS targets, EvoRator2 outperformed state-of-the-art methods. We also show that by combining EvoRator2's predictions with those obtained by a state-of-the-art deep-learning method that accounts for the information in the MSA, the prediction of the effect of mutation in DMS experiments was improved in terms of both accuracy and stability. EvoRator2 is designed to predict which amino-acid substitutions are tolerated in such proteins without many homologous sequences, including orphan or de novo designed proteins. We implemented our approach in the EvoRator web server (https://evorator.tau.ac.il).

Cation/proton antiporters: novel structure-driven pharmaceutical opportunities.

Cation/proton antiporters (CPAs) regulate cells' salt concentration and pH. Their malfunction is associated with a range of human pathologies, yet only a handful of CPA-targeting therapeutics are presently in clinical development. Here, we discuss how recently published mammalian protein structures and emerging computational technologies may help to bridge this gap.

Identification and Analysis of Fungal-Specific Regions in the Aspergillus fumigatus Cu Exporter CrpA That Are Essential for Cu Resistance but Not for Virulence.

The opportunistic fungus Aspergillus fumigatus is the primary invasive mold pathogen in humans, and is responsible for an estimated 200,000 yearly deaths worldwide. Most fatalities occur in immunocompromised patients who lack the cellular and humoral defenses necessary to halt the pathogen's advance, primarily in the lungs. One of the cellular responses used by macrophages to counteract fungal infection is the accumulation of high phagolysosomal Cu levels to destroy ingested pathogens. A. fumigatus responds by activating high expression levels of crpA, which encodes a Cu+ P-type ATPase that actively transports excess Cu from the cytoplasm to the extracellular environment. In this study, we used a bioinformatics approach to identify two fungal-unique regions in CrpA that we studied by deletion/replacement, subcellular localization, Cu sensitivity in vitro, killing by mouse alveolar macrophages, and virulence in a mouse model of invasive pulmonary aspergillosis. Deletion of CrpA fungal-unique amino acids 1-211 containing two N-terminal Cu-binding sites, moderately increased Cu-sensitivity but did not affect expression or localization to the endoplasmic reticulum (ER) and cell surface. Replacement of CrpA fungal-unique amino acids 542-556 consisting of an intracellular loop between the second and third transmembrane helices resulted in ER retention of the protein and strongly increased Cu-sensitivity. Deleting CrpA N-terminal amino acids 1-211 or replacing amino acids 542-556 also increased sensitivity to killing by mouse alveolar macrophages. Surprisingly, the two mutations did not affect virulence in a mouse model of infection, suggesting that even weak Cu-efflux activity by mutated CrpA preserves fungal virulence.

Using evolutionary data to make sense of macromolecules with a "face-lifted" ConSurf.

The ConSurf web-sever for the analysis of proteins, RNA, and DNA provides a quick and accurate estimate of the per-site evolutionary rate among homologues. The analysis reveals functionally important regions, such as catalytic and ligand-binding sites, which often evolve slowly. Since the last report in 2016, ConSurf has been improved in multiple ways. It now has a user-friendly interface that makes it easier to perform the analysis and to visualize the results. Evolutionary rates are calculated based on a set of homologous sequences, collected using hidden Markov model-based search tools, recently embedded in the pipeline. Using these, and following the removal of redundancy, ConSurf assembles a representative set of effective homologues for protein and nucleic acid queries to enable informative analysis of the evolutionary patterns. The analysis is particularly insightful when the evolutionary rates are mapped on the macromolecule structure. In this respect, the availability of AlphaFold model structures of essentially all UniProt proteins makes ConSurf particularly relevant to the research community. The UniProt ID of a query protein with an available AlphaFold model can now be used to start a calculation. Another important improvement is the Python re-implementation of the entire computational pipeline, making it easier to maintain. This Python pipeline is now available for download as a standalone version. We demonstrate some of ConSurf's key capabilities by the analysis of caveolin-1, the main protein of membrane invaginations called caveolae.

Ultrasensitive chemiluminescent neuraminidase probe for rapid screening and identification of small-molecules with antiviral activity against influenza A virus in mammalian cells.

Influenza A virus is the most virulent influenza subtype and is associated with large-scale global pandemics characterized by high levels of morbidity and mortality. Developing simple and sensitive molecular methods for detecting influenza viruses is critical. Neuraminidase, an exo-glycosidase displayed on the surface of influenza virions, is responsible for the release of the virions and their spread in the infected host. Here, we present a new phenoxy-dioxetane chemiluminescent probe (CLNA) that can directly detect neuraminidase activity. The probe exhibits an effective turn-on response upon reaction with neuraminidase and produces a strong emission signal at 515 nm with an extremely high signal-to-noise ratio. Comparison measurements of our new probe with previously reported analogous neuraminidase optical probes showed superior detection capability in terms of response time and sensitivity. Thus, as far as we know, our probe is the most sensitive neuraminidase probe known to date. The chemiluminescence turn-on response produced by our neuraminidase probe enables rapid screening for small molecules that inhibit viral replication through different mechanisms as validated directly in influenza A-infected mammalian cells using the known inhibitors oseltamivir and amantadine. We expect that our new chemiluminescent neuraminidase probe will prove useful for various applications requiring neuraminidase detection including drug discovery assays against various influenza virus strains in mammalian cells.

Allosteric links between the hydrophilic N-terminus and transmembrane core of human Na+ /H+ antiporter NHA2.

The human Na+ /H+ antiporter NHA2 (SLC9B2) transports Na+ or Li+ across the plasma membrane in exchange for protons, and is implicated in various pathologies. It is a 537 amino acids protein with an 82 residues long hydrophilic cytoplasmic N-terminus followed by a transmembrane part comprising 14 transmembrane helices. We optimized the functional expression of HsNHA2 in the plasma membrane of a salt-sensitive Saccharomyces cerevisiae strain and characterized in vivo a set of mutated or truncated versions of HsNHA2 in terms of their substrate specificity, transport activity, localization, and protein stability. We identified a highly conserved proline 246, located in the core of the protein, as being crucial for ion selectivity. The replacement of P246 with serine or threonine resulted in antiporters with altered substrate specificity that were not only highly active at acidic pH 4.0 (like the native antiporter), but also at neutral pH. P246T/S versions also exhibited increased resistance to the HsNHA2-specific inhibitor phloretin. We experimentally proved that a putative salt bridge between E215 and R432 is important for antiporter function, but also structural integrity. Truncations of the first 50-70 residues of the N-terminus doubled the transport activity of HsNHA2, while changes in the charge at positions E47, E56, K57, or K58 decreased the antiporter's transport activity. Thus, the hydrophilic N-terminal part of the protein appears to allosterically auto-inhibit cation transport of HsNHA2. Our data also show this in vivo approach to be useful for a rapid screening of SNP's effect on HsNHA2 activity.

Similar protein segments shared between domains of different evolutionary lineages.

The emergence of novel proteins, beyond these that can be readily made by duplication and recombination of preexisting domains, is elusive. De novo emergence from random sequences is unlikely because the vast majority of random chains would not even fold, let alone function. An alternative explanation is that novel proteins emerge by duplication and fusion of pre-existing polypeptide segments. In this case, traces of such ancient events may remain within contemporary proteins in the form of reused segments. Together with the late Dan Tawfik, we detected such similar segments, far shorter than intact protein domains, which are found in different environments. The detection of these, "bridging themes," was based on a unique search strategy, where in addition to searching for similarity of shared fragments, so-called "themes," we also explicitly searched for cases in which the sequence segments before and after the theme are dissimilar (both in sequence and structure). Here, using a similar strategy, we further expanded the search and discovered almost 500 additional "bridging themes," linking domains that are often from ancient folds. The themes, of 20 residues or more (average 53), do not retain their structure despite sharing 37% sequence identity on average. Indeed, conformation flexibility may confer an evolutionary advantage, in that it fits in multiple environments. We elaborate on two interesting themes, shared between Rossmann/Trefoil-Plexin-like domains and a ß-propeller-like domain. FOR A BROAD AUDIENCE: A fundamental question in molecular evolution is how protein domains emerged. Similar segments shared between domains of seemingly distinct origins, may offer clues, as these may be remnants of the evolutionary process through which these domains emerged. However, finding such cases is difficult. Here, we expand the set of such cases which we curated previously, adding segments shared between domains that are considered ancient.

Homologues not needed: Structure prediction from a protein language model.

Accurate protein structure predictors use clusters of homologues, which disregard sequence specific effects. In this issue of Structure, Weißenow and colleagues report a deep learning-based tool, EMBER2, that efficiently predicts the distances in a protein structure from its amino acid sequence only. This approach should enable the analysis of mutation effects.

EvoRator: Prediction of Residue-level Evolutionary Rates from Protein Structures Using Machine Learning.

Measuring evolutionary rates at the residue level is indispensable for gaining structural and functional insights into proteins. State-of-the-art tools for estimating rates take as input a large set of homologous proteins, a probabilistic model of evolution and a phylogenetic tree. However, a gap exists when only few or no homologous proteins can be found, e.g., orphan proteins. In addition, such tools do not take the three-dimensional (3D) structure of the protein into account. The association between the 3D structure and site-specific rates can be learned using machine-learning regression tools from a cohort of proteins for which both the structure and a large set of homologs exist. Here we present EvoRator, a user-friendly web server that implements a machine-learning regression algorithm to predict site-specific evolutionary rates from protein structures. We show that EvoRator outperforms predictions obtained using traditional physicochemical features, such as relative solvent accessibility and weighted contact number. We also demonstrate the application of EvoRator in three common scenarios that arise in protein evolution research: (1) orphan proteins for which no (or few) homologs exist; (2) When homologous sequences exist, our algorithm contrasts structure-based estimates of the evolutionary rates and the phylogeny-based estimates. This allows detecting sites that are likely conserved due to functional rather than structural constraints; (3) Algorithms that only rely on homologous sequence often fail to accurately measure the evolutionary rates of positions in gapped sequence alignments, which frequently occurs as a result of a clade-specific insertion. Our algorithm makes use of training data and known 3D structure of such gapped positions to predict their evolutionary rates. EvoRator is freely available for all users at: https://evorator.tau.ac.il/.

The copper-linked Escherichia coli AZY operon: Structure, metal binding, and a possible physiological role in copper delivery.

The Escherichia coli yobA-yebZ-yebY (AZY) operon encodes the proteins YobA, YebZ, and YebY. YobA and YebZ are homologs of the CopC periplasmic copper-binding protein and the CopD putative copper importer, respectively, whereas YebY belongs to the uncharacterized Domain of Unknown Function 2511 family. Despite numerous studies of E. coli copper homeostasis and the existence of the AZY operon in a range of bacteria, the operon's proteins and their functional roles have not been explored. In this study, we present the first biochemical and functional studies of the AZY proteins. Biochemical characterization and structural modeling indicate that YobA binds a single Cu2+ ion with high affinity. Bioinformatics analysis shows that YebY is widespread and encoded either in AZY operons or in other genetic contexts unrelated to copper homeostasis. We also determined the 1.8 Å resolution crystal structure of E. coli YebY, which closely resembles that of the lantibiotic self-resistance protein MlbQ. Two strictly conserved cysteine residues form a disulfide bond, consistent with the observed periplasmic localization of YebY. Upon treatment with reductants, YebY binds Cu+ and Cu2+ with low affinity, as demonstrated by metal-binding analysis and tryptophan fluorescence. Finally, genetic manipulations show that the AZY operon is not involved in copper tolerance or antioxidant defense. Instead, YebY and YobA are required for the activity of the copper-related NADH dehydrogenase II. These results are consistent with a potential role of the AZY operon in copper delivery to membrane proteins.

Dimeric and high-resolution structures of Chlamydomonas Photosystem I from a temperature-sensitive Photosystem II mutant.

Water molecules play a pivotal functional role in photosynthesis, primarily as the substrate for Photosystem II (PSII). However, their importance and contribution to Photosystem I (PSI) activity remains obscure. Using a high-resolution cryogenic electron microscopy (cryo-EM) PSI structure from a Chlamydomonas reinhardtii temperature-sensitive photoautotrophic PSII mutant (TSP4), a conserved network of water molecules - dating back to cyanobacteria - was uncovered, mainly in the vicinity of the electron transport chain (ETC). The high-resolution structure illustrated that the water molecules served as a ligand in every chlorophyll that was missing a fifth magnesium coordination in the PSI core and in the light-harvesting complexes (LHC). The asymmetric distribution of the water molecules near the ETC branches modulated their electrostatic landscape, distinctly in the space between the quinones and FX. The data also disclosed the first observation of eukaryotic PSI oligomerisation through a low-resolution PSI dimer that was comprised of PSI-10LHC and PSI-8LHC.

The Sigma-1 receptor is an ER-localized type II membrane protein.

The Sigma-1 receptor (S1R) is a transmembrane protein with important roles in cellular homeostasis in normal physiology and in disease. Especially in neurodegenerative diseases, S1R activation has been shown to provide neuroprotection by modulating calcium signaling, mitochondrial function and reducing endoplasmic reticulum (ER) stress. S1R missense mutations are one of the causes of the neurodegenerative Amyotrophic Lateral Sclerosis and distal hereditary motor neuronopathies. Although the S1R has been studied intensively, basic aspects remain controversial, such as S1R topology and whether it reaches the plasma membrane. To address these questions, we have undertaken several approaches. C-terminal tagging with a small biotin-acceptor peptide and BirA biotinylation in cells suggested a type II membrane orientation (cytosolic N-terminus). However, N-terminal tagging gave an equal probability for both possible orientations. This might explain conflicting reports in the literature, as tags may affect the protein topology. Therefore, we studied untagged S1R using a protease protection assay and a glycosylation mapping approach, introducing N-glycosylation sites. Both methods provided unambiguous results showing that the S1R is a type II membrane protein with a short cytosolic N-terminal tail. Assessments of glycan processing, surface fluorescence-activated cell sorting, and cell surface biotinylation indicated ER retention, with insignificant exit to the plasma membrane, in the absence or presence of S1R agonists or of ER stress. These findings may have important implications for S1R-based therapeutic approaches.

Using ConSurf to Detect Functionally Important Regions in RNA.

The ConSurf web server (https://consurf.tau.ac.il/) for using evolutionary data to detect functional regions is useful for analyzing proteins. The analysis is based on the premise that functional regions, which may for example facilitate ligand binding and catalysis, often evolve slowly. The analysis requires finding enough effective, i.e., non-redundant, sufficiently remote homologs. Indeed, the ConSurf pipeline, which is based on state-of-the-art protein sequence databases and analysis tools, is highly valuable for protein analysis. ConSurf also allows evolutionary analysis of RNA, but the analysis often fails due to insufficient data, particularly the inability of the current pipeline to detect enough effective RNA homologs. This is because the RNA search tools and databases offered are not as good as those used for protein analysis. Fortunately, ConSurf also allows importing external collections of homologs in the form of a multiple sequence alignment (MSA). Leveraging this, here we describe various protocols for constructing MSAs for successful ConSurf analysis of RNA queries. We report the level of success of these protocols on an exemplary set comprising a dozen RNA molecules of diverse structure and function. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Standard ConSurf evolutionary conservation analysis of an RNA query. Basic Protocol 2: ConSurf evolutionary conservation analysis of an RNA query with external MSA. Support Protocol 1: Construction of an MSA for an RNA query using other online servers. Support Protocol 2: Construction of an MSA for an RNA query using nHMMER locally.

Titratable transmembrane residues and a hydrophobic plug are essential for manganese import via the Bacillus anthracis ABC transporter MntBC-A.

All extant life forms require trace transition metals (e.g., Fe2/3+, Cu1/2+, and Mn2+) to survive. However, as these are environmentally scarce, organisms have evolved sophisticated metal uptake machineries. In bacteria, high-affinity import of transition metals is predominantly mediated by ABC transporters. During bacterial infection, sequestration of metal by the host further limits the availability of these ions, and accordingly, bacterial ABC transporters (importers) of metals are key virulence determinants. However, the structure-function relationships of these metal transporters have not been fully elucidated. Here, we used metal-sensitivity assays, advanced structural modeling, and enzymatic assays to study the ABC transporter MntBC-A, a virulence determinant of the bacterial human pathogen Bacillus anthracis. We find that despite its broad metal-recognition profile, MntBC-A imports only manganese, whereas zinc can function as a high-affinity inhibitor of MntBC-A. Computational analysis shows that the transmembrane metal permeation pathway is lined with six titratable residues that can coordinate the positively charged metal, and mutagenesis studies show that they are essential for manganese transport. Modeling suggests that access to these titratable residues is blocked by a ladder of hydrophobic residues, and ATP-driven conformational changes open and close this hydrophobic seal to permit metal binding and release. The conservation of this arrangement of titratable and hydrophobic residues among ABC transporters of transition metals suggests a common mechanism. These findings advance our understanding of transmembrane metal recognition and permeation and may aid the design and development of novel antibacterial agents.

Integrative Structural Biology in the Era of Accurate Structure Prediction.

Characterizing the three-dimensional structure of macromolecules is central to understanding their function. Traditionally, structures of proteins and their complexes have been determined using experimental techniques such as X-ray crystallography, NMR, or cryo-electron microscopy-applied individually or in an integrative manner. Meanwhile, however, computational methods for protein structure prediction have been improving their accuracy, gradually, then suddenly, with the breakthrough advance by AlphaFold2, whose models of monomeric proteins are often as accurate as experimental structures. This breakthrough foreshadows a new era of computational methods that can build accurate models for most monomeric proteins. Here, we envision how such accurate modeling methods can combine with experimental structural biology techniques, enhancing integrative structural biology. We highlight the challenges that arise when considering multiple structural conformations, protein complexes, and polymorphic assemblies. These challenges will motivate further developments, both in modeling programs and in methods to solve experimental structures, towards better and quicker investigation of structure-function relationships.

Gram-negative outer-membrane proteins with multiple ß-barrel domains.

Outer-membrane beta barrels (OMBBs) are found in the outer membrane of gram-negative bacteria and eukaryotic organelles. OMBBs fold as antiparallel ß-sheets that close onto themselves, forming pores that traverse the membrane. Currently known structures include only one barrel, of 8 to 36 strands, per chain. The lack of multi-OMBB chains is surprising, as most OMBBs form oligomers, and some function only in this state. Using a combination of sensitive sequence comparison methods and coevolutionary analysis tools, we identify many proteins combining multiple beta barrels within a single chain; combinations that include eight-stranded barrels prevail. These multibarrels seem to be the result of independent, lineage-specific fusion and amplification events. The absence of multibarrels that are universally conserved in bacteria with an outer membrane, coupled with their frequent de novo genesis, suggests that their functions are not essential but rather beneficial in specific environments. Adjacent barrels of complementary function within the same chain may allow for functions beyond those of the individual barrels.