Deep learning allows genome-scale prediction of Michaelis constants from structural features.

The Michaelis constant KM describes the affinity of an enzyme for a specific substrate and is a central parameter in studies of enzyme kinetics and cellular physiology. As measurements of KM are often difficult and time-consuming, experimental estimates exist for only a minority of enzyme-substrate combinations even in model organisms. Here, we build and train an organism-independent model that successfully predicts KM values for natural enzyme-substrate combinations using machine and deep learning methods. Predictions are based on a task-specific molecular fingerprint of the substrate, generated using a graph neural network, and on a deep numerical representation of the enzyme's amino acid sequence. We provide genome-scale KM predictions for 47 model organisms, which can be used to approximately relate metabolite concentrations to cellular physiology and to aid in the parameterization of kinetic models of cellular metabolism.

Elimination of rNMPs from mitochondrial DNA has no effect on its stability.

Ribonucleotides (rNMPs) incorporated in the nuclear genome are a well-established threat to genome stability and can result in DNA strand breaks when not removed in a timely manner. However, the presence of a certain level of rNMPs is tolerated in mitochondrial DNA (mtDNA) although aberrant mtDNA rNMP content has been identified in disease models. We investigated the effect of incorporated rNMPs on mtDNA stability over the mouse life span and found that the mtDNA rNMP content increased during early life. The rNMP content of mtDNA varied greatly across different tissues and was defined by the rNTP/dNTP ratio of the tissue. Accordingly, mtDNA rNMPs were nearly absent in SAMHD1-/- mice that have increased dNTP pools. The near absence of rNMPs did not, however, appreciably affect mtDNA copy number or the levels of mtDNA molecules with deletions or strand breaks in aged animals near the end of their life span. The physiological rNMP load therefore does not contribute to the progressive loss of mtDNA quality that occurs as mice age.

Chiral Alcohols from Alkenes and Water: Directed Evolution of a Styrene Hydratase.

Enantioselective synthesis of chiral alcohols through asymmetric addition of water across an unactivated alkene is a highly sought-after transformation and a big challenge in catalysis. Herein we report the identification and directed evolution of a fatty acid hydratase from Marinitoga hydrogenitolerans for the highly enantioselective hydration of styrenes to yield chiral 1-arylethanols. While directed evolution for styrene hydration was performed in the presence of heptanoic acid to mimic fatty acid binding, the engineered enzyme displayed remarkable asymmetric styrene hydration activity in the absence of the small molecule activator. The evolved styrene hydratase provided access to chiral alcohols from simple alkenes and water with high enantioselectivity (>99 : 1 e.r.) and could be applied on a preparative scale.

Discovery of Two Novel Oxidases Using a High-Throughput Activity Screen.

Discovery of novel enzymes is a challenging task, yet a crucial one, due to their increasing relevance as chemical catalysts and biotechnological tools. In our work we present a high-throughput screening approach to discovering novel activities. A screen of 96 putative oxidases with 23 substrates led to the discovery of two new enzymes. The first enzyme, N-acetyl-D-hexosamine oxidase (EC 1.1.3.29) from Ralstonia solanacearum, is a vanillyl alcohol oxidase-like flavoprotein displaying the highest activity with N-acetylglucosamine and N-acetylgalactosamine. Before our discovery of the enzyme, its activity was an orphan one - experimentally characterized but lacking the link to amino acid sequence. The second enzyme, from an uncultured marine euryarchaeota, is a long-chain alcohol oxidase (LCAO, EC 1.1.3.20) active with a range of fatty alcohols, with 1-dodecanol being the preferred substrate. The enzyme displays no sequence similarity to previously characterised LCAOs, and thus is a completely novel representative of a protein with such activity.

Modeling-Assisted Design of Thermostable Benzaldehyde Lyases from Rhodococcus erythropolis for Continuous Production of α-Hydroxy Ketones.

Enantiopure α-hydroxy ketones are important building blocks of active pharmaceutical ingredients (APIs), which can be produced by thiamine-diphosphate-dependent lyases, such as benzaldehyde lyase. Here we report the discovery of a novel thermostable benzaldehyde lyase from Rhodococcus erythropolis R138 (ReBAL). While the overall sequence identity to the only experimentally confirmed benzaldehyde lyase from Pseudomonas fluorescens Biovar I (PfBAL) was only 65 %, comparison of a structural model of ReBAL with the crystal structure of PfBAL revealed only four divergent amino acids in the substrate binding cavity. Based on rational design, we generated two ReBAL variants, which were characterized along with the wild-type enzyme in terms of their substrate spectrum, thermostability and biocatalytic performance in the presence of different co-solvents. We found that the new enzyme variants have a significantly higher thermostability (up to 22 °C increase in T50 ) and a different co-solvent-dependent activity. Using the most stable variant immobilized in packed-bed reactors via the SpyCatcher/SpyTag system, (R)-benzoin was synthesized from benzaldehyde over a period of seven days with a stable space-time-yield of 9.3 mmol ⋅ L-1 ⋅ d-1 . Our work expands the important class of benzaldehyde lyases and therefore contributes to the development of continuous biocatalytic processes for the production of α-hydroxy ketones and APIs.

Suppressors of amyloid-ß toxicity improve recombinant protein production in yeast by reducing oxidative stress and tuning cellular metabolism.

High-level production of recombinant proteins in industrial microorganisms is often limited by the formation of misfolded proteins or protein aggregates, which consequently induce cellular stress responses. We hypothesized that in a yeast Alzheimer's disease (AD) model overexpression of amyloid-ß peptides (Aß42), one of the main peptides relevant for AD pathologies, induces similar phenotypes of cellular stress. Using this humanized AD model, we previously identified suppressors of Aß42 cytotoxicity. Here we hypothesize that these suppressors could be used as metabolic engineering targets to alleviate cellular stress and improve recombinant protein production in the yeast Saccharomyces cerevisiae. Forty-six candidate genes were individually deleted and twenty were individually overexpressed. The positive targets that increased recombinant α-amylase production were further combined leading to an 18.7-fold increased recombinant protein production. These target genes are involved in multiple cellular networks including RNA processing, transcription, ER-mitochondrial complex, and protein unfolding. By using transcriptomics and proteomics analyses, combined with reverse metabolic engineering, we showed that reduced oxidative stress, increased membrane lipid biosynthesis and repressed arginine and sulfur amino acid biosynthesis are significant pathways for increased recombinant protein production. Our findings provide new insights towards developing synthetic yeast cell factories for biosynthesis of valuable proteins.

Experimental and computational investigation of enzyme functional annotations uncovers misannotation in the EC 1.1.3.15 enzyme class.

Only a small fraction of genes deposited to databases have been experimentally characterised. The majority of proteins have their function assigned automatically, which can result in erroneous annotations. The reliability of current annotations in public databases is largely unknown; experimental attempts to validate the accuracy within individual enzyme classes are lacking. In this study we performed an overview of functional annotations to the BRENDA enzyme database. We first applied a high-throughput experimental platform to verify functional annotations to an enzyme class of S-2-hydroxyacid oxidases (EC 1.1.3.15). We chose 122 representative sequences of the class and screened them for their predicted function. Based on the experimental results, predicted domain architecture and similarity to previously characterised S-2-hydroxyacid oxidases, we inferred that at least 78% of sequences in the enzyme class are misannotated. We experimentally confirmed four alternative activities among the misannotated sequences and showed that misannotation in the enzyme class increased over time. Finally, we performed a computational analysis of annotations to all enzyme classes in the BRENDA database, and showed that nearly 18% of all sequences are annotated to an enzyme class while sharing no similarity or domain architecture to experimentally characterised representatives. We showed that even well-studied enzyme classes of industrial relevance are affected by the problem of functional misannotation.

Engineering Saccharomyces cerevisiae for the production and secretion of Affibody molecules.

BACKGROUND: Affibody molecules are synthetic peptides with a variety of therapeutic and diagnostic applications. To date, Affibody molecules have mainly been produced by the bacterial production host Escherichia coli. There is an interest in exploring alternative production hosts to identify potential improvements in terms of yield, ease of production and purification advantages. In this study, we evaluated the feasibility of Saccharomyces cerevisiae as a production chassis for this group of proteins. RESULTS: We examined the production of three different Affibody molecules in S. cerevisiae and found that these Affibody molecules were partially degraded. An albumin-binding domain, which may be attached to the Affibody molecules to increase their half-life, was identified to be a substrate for several S. cerevisiae proteases. We tested the removal of three vacuolar proteases, proteinase A, proteinase B and carboxypeptidase Y. Removal of one of these, proteinase A, resulted in intact secretion of one of the targeted Affibody molecules. Removal of either or both of the two additional proteases, carboxypeptidase Y and proteinase B, resulted in intact secretion of the two remaining Affibody molecules. The produced Affibody molecules were verified to bind their target, human HER3, as potently as the corresponding molecules produced in E. coli in an in vitro surface-plasmon resonance binding assay. Finally, we performed a fed-batch fermentation with one of the engineered protease-deficient S. cerevisiae strains and achieved a protein titer of 530 mg Affibody molecule/L. CONCLUSION: This study shows that engineered S. cerevisiae has a great potential as a production host for recombinant Affibody molecules, reaching a high titer, and for proteins where endotoxin removal could be challenging, the use of S. cerevisiae obviates the need for endotoxin removal from protein produced in E. coli.

DNA polymerase η contributes to genome-wide lagging strand synthesis.

DNA polymerase η (pol η) is best known for its ability to bypass UV-induced thymine-thymine (T-T) dimers and other bulky DNA lesions, but pol η also has other cellular roles. Here, we present evidence that pol η competes with DNA polymerases α and δ for the synthesis of the lagging strand genome-wide, where it also shows a preference for T-T in the DNA template. Moreover, we found that the C-terminus of pol η, which contains a PCNA-Interacting Protein motif is required for pol η to function in lagging strand synthesis. Finally, we provide evidence that a pol η dependent signature is also found to be lagging strand specific in patients with skin cancer. Taken together, these findings provide insight into the physiological role of DNA synthesis by pol η and have implications for our understanding of how our genome is replicated to avoid mutagenesis, genome instability and cancer.

Ribonucleotides incorporated by the yeast mitochondrial DNA polymerase are not repaired.

Incorporation of ribonucleotides into DNA during genome replication is a significant source of genomic instability. The frequency of ribonucleotides in DNA is determined by deoxyribonucleoside triphosphate/ribonucleoside triphosphate (dNTP/rNTP) ratios, by the ability of DNA polymerases to discriminate against ribonucleotides, and by the capacity of repair mechanisms to remove incorporated ribonucleotides. To simultaneously compare how the nuclear and mitochondrial genomes incorporate and remove ribonucleotides, we challenged these processes by changing the balance of cellular dNTPs. Using a collection of yeast strains with altered dNTP pools, we discovered an inverse relationship between the concentration of individual dNTPs and the amount of the corresponding ribonucleotides incorporated in mitochondrial DNA, while in nuclear DNA the ribonucleotide pattern was only altered in the absence of ribonucleotide excision repair. Our analysis uncovers major differences in ribonucleotide repair between the two genomes and provides concrete evidence that yeast mitochondria lack mechanisms for removal of ribonucleotides incorporated by the mtDNA polymerase. Furthermore, as cytosolic dNTP pool imbalances were transmitted equally well into the nucleus and the mitochondria, our results support a view of the cytosolic and mitochondrial dNTP pools in frequent exchange.

Nucleotide pools dictate the identity and frequency of ribonucleotide incorporation in mitochondrial DNA.

Previous work has demonstrated the presence of ribonucleotides in human mitochondrial DNA (mtDNA) and in the present study we use a genome-wide approach to precisely map the location of these. We find that ribonucleotides are distributed evenly between the heavy- and light-strand of mtDNA. The relative levels of incorporated ribonucleotides reflect that DNA polymerase γ discriminates the four ribonucleotides differentially during DNA synthesis. The observed pattern is also dependent on the mitochondrial deoxyribonucleotide (dNTP) pools and disease-causing mutations that change these pools alter both the absolute and relative levels of incorporated ribonucleotides. Our analyses strongly suggest that DNA polymerase γ-dependent incorporation is the main source of ribonucleotides in mtDNA and argues against the existence of a mitochondrial ribonucleotide excision repair pathway in human cells. Furthermore, we clearly demonstrate that when dNTP pools are limiting, ribonucleotides serve as a source of building blocks to maintain DNA replication. Increased levels of embedded ribonucleotides in patient cells with disturbed nucleotide pools may contribute to a pathogenic mechanism that affects mtDNA stability and impair new rounds of mtDNA replication.

3D-Printed Phenacrylate Decarboxylase Flow Reactors for the Chemoenzymatic Synthesis of 4-Hydroxystilbene.

Continuous flow systems for chemical synthesis are becoming a major focus in organic chemistry and there is a growing interest in the integration of biocatalysts due to their high regio- and stereoselectivity. Methods established for 3D bioprinting enable the fast and simple production of agarose-based modules for biocatalytic reactors if thermally stable enzymes are available. We report here on the characterization of four different cofactor-free phenacrylate decarboxylase enzymes suitable for the production of 4-vinylphenol and test their applicability for the encapsulation and direct 3D printing of disk-shaped agarose-based modules that can be used for compartmentalized flow microreactors. Using the most active and stable phenacrylate decarboxylase from Enterobacter spec. in a setup with four parallel reactors and a subsequent palladium(II) acetate-catalysed Heck reaction, 4-hydroxystilbene was synthesized from p-coumaric acid with a total yield of 14.7 % on a milligram scale. We believe that, due to the convenient direct immobilization of any thermostable enzyme and straightforward tuning of the reaction sequence by stacking of modules with different catalytic activities, this simple process will facilitate the establishment and use of cascade reactions and will therefore be of great advantage for many research approaches.

Correlating enzyme annotations with a large set of microbial growth temperatures reveals metabolic adaptations to growth at diverse temperatures.

BACKGROUND: The ambient temperature of all habitats is a key physical property that shapes the biology of microbes inhabiting them. The optimal growth temperature (OGT) of a microbe, is therefore a key piece of data needed to understand evolutionary adaptations manifested in their genome sequence. Unfortunately there is no growth temperature database or easily downloadable dataset encompassing the majority of cultured microorganisms. We are thus limited in interpreting genomic data to identify temperature adaptations in microbes. RESULTS: In this work I significantly contribute to closing this gap by mining data from major culture collection centres to obtain growth temperature data for a nonredundant set of 21,498 microbes. The dataset ( https://doi.org/10.5281/zenodo.1175608 ) contains mainly bacteria and archaea and spans psychrophiles, mesophiles, thermophiles and hyperthermophiles. Using this data a full 43% of all protein entries in the UniProt database can be annotated with the growth temperature of the species from which they originate. I validate the dataset by showing a Pearson correlation of up to 0.89 between growth temperature and mean enzyme optima, a physiological property directly influenced by the growth temperature. Using the temperature dataset I correlate the genomic occurance of enzyme functional annotations with growth temperature. I identify 319 enzyme functions that either increase or decrease in occurrence with temperature. Eight metabolic pathways were statistically enriched for these enzyme functions. Furthermore, I establish a correlation between 33 domains of unknown function (DUFs) with growth temperature in microbes, four of which (DUF438, DUF1524, DUF1957 and DUF3458_C) were significant in both archaea and bacteria. CONCLUSIONS: The growth temperature dataset enables large-scale correlation analysis with enzyme function- and domain-level annotations. Growth-temperature dependent changes in their occurrence highlight potential evolutionary adaptations. A few of the identified changes are previously known, such as the preference for menaquinone biosynthesis through the futalosine pathway in bacteria growing at high temperatures. Others represent important starting points for future studies, such as DUFs where their occurrence change with temperature. The growth temperature dataset should become a valuable community resource and will find additional, important, uses in correlating genomic, transcriptomic, proteomic, metabolomic, phenotypic or taxonomic properties with temperature in future studies.

Directed evolution of a far-red fluorescent rhodopsin.

Microbial rhodopsins are a diverse group of photoactive transmembrane proteins found in all three domains of life. A member of this protein family, Archaerhodopsin-3 (Arch) of halobacterium Halorubrum sodomense, was recently shown to function as a fluorescent indicator of membrane potential when expressed in mammalian neurons. Arch fluorescence, however, is very dim and is not optimal for applications in live-cell imaging. We used directed evolution to identify mutations that dramatically improve the absolute brightness of Arch, as confirmed biochemically and with live-cell imaging (in Escherichia coli and human embryonic kidney 293 cells). In some fluorescent Arch variants, the pK(a) of the protonated Schiff-base linkage to retinal is near neutral pH, a useful feature for voltage-sensing applications. These bright Arch variants enable labeling of biological membranes in the far-red/infrared and exhibit the furthest red-shifted fluorescence emission thus far reported for a fluorescent protein (maximal excitation/emission at ∼ 620 nm/730 nm).

GLYCOLATE OXIDASE3, a Glycolate Oxidase Homolog of Yeast l-Lactate Cytochrome c Oxidoreductase, Supports l-Lactate Oxidation in Roots of Arabidopsis.

In roots of Arabidopsis (Arabidopsis thaliana), l-lactate is generated by the reduction of pyruvate via l-lactate dehydrogenase, but this enzyme does not efficiently catalyze the reverse reaction. Here, we identify the Arabidopsis glycolate oxidase (GOX) paralogs GOX1, GOX2, and GOX3 as putative l-lactate-metabolizing enzymes based on their homology to CYB2, the l-lactate cytochrome c oxidoreductase from the yeast Saccharomyces cerevisiae. We found that GOX3 uses l-lactate with a similar efficiency to glycolate; in contrast, the photorespiratory isoforms GOX1 and GOX2, which share similar enzymatic properties, use glycolate with much higher efficiencies than l-lactate. The key factor making GOX3 more efficient with l-lactate than GOX1 and GOX2 is a 5- to 10-fold lower Km for the substrate. Consequently, only GOX3 can efficiently metabolize l-lactate at low intracellular concentrations. Isotope tracer experiments as well as substrate toxicity tests using GOX3 loss-of-function and overexpressor plants indicate that l-lactate is metabolized in vivo by GOX3. Moreover, GOX3 rescues the lethal growth phenotype of a yeast strain lacking CYB2, which cannot grow on l-lactate as a sole carbon source. GOX3 is predominantly present in roots and mature to aging leaves but is largely absent from young photosynthetic leaves, indicating that it plays a role predominantly in heterotrophic rather than autotrophic tissues, at least under standard growth conditions. In roots of plants grown under normoxic conditions, loss of function of GOX3 induces metabolic rearrangements that mirror wild-type responses under hypoxia. Thus, we identified GOX3 as the enzyme that metabolizes l-lactate to pyruvate in vivo and hypothesize that it may ensure the sustainment of low levels of l-lactate after its formation under normoxia.

The influence of alternative pathways of respiration that utilize branched-chain amino acids following water shortage in Arabidopsis.

During dark-induced senescence isovaleryl-CoA dehydrogenase (IVDH) and D-2-hydroxyglutarate dehydrogenase (D-2HGDH) act as alternate electron donors to the ubiquinol pool via the electron-transfer flavoprotein/electron-transfer flavoprotein:ubiquinone oxidoreductase (ETF/ETFQO) pathway. However, the role of this pathway in response to other stresses still remains unclear. Here, we demonstrated that this alternative pathway is associated with tolerance to drought in Arabidopsis. In comparison with wild type (WT) and lines overexpressing D-2GHDH, loss-of-function etfqo-1, d2hgdh-2 and ivdh-1 mutants displayed compromised respiration rates and were more sensitive to drought. Our results demonstrated that an operational ETF/ETFQO pathway is associated with plants' ability to withstand drought and to recover growth once water becomes replete. Drought-induced metabolic reprogramming resulted in an increase in tricarboxylic acid (TCA) cycle intermediates and total amino acid levels, as well as decreases in protein, starch and nitrate contents. The enhanced levels of the branched-chain amino acids in loss-of-function mutants appear to be related to their increased utilization as substrates for the TCA cycle under water stress. Our results thus show that mitochondrial metabolism is highly active during drought stress responses and provide support for a role of alternative respiratory pathways within this response.

Plants Possess a Cyclic Mitochondrial Metabolic Pathway similar to the Mammalian Metabolic Repair Mechanism Involving Malate Dehydrogenase and l-2-Hydroxyglutarate Dehydrogenase.

Enzymatic side reactions can give rise to the formation of wasteful and toxic products that are removed by metabolite repair pathways. In this work, we identify and characterize a mitochondrial metabolic repair mechanism in Arabidopsis thaliana involving malate dehydrogenase (mMDH) and l-2-hydroxyglutarate dehydrogenase (l-2HGDH). We analyze the kinetic properties of both A. thaliana mMDH isoforms, and show that they produce l-2-hydroxyglutarate (l-2HG) from 2-ketoglutarate (2-KG) at low rates in side reactions. We identify A. thaliana l-2HGDH as a mitochondrial FAD-containing oxidase that converts l-2HG back to 2-KG. Using loss-of-function mutants, we show that the electrons produced in the l-2HGDH reaction are transferred to the mitochondrial electron transport chain through the electron transfer protein (ETF). Thus, plants possess the biochemical components of an l-2HG metabolic repair system identical to that found in mammals. While deficiencies in the metabolism of l-2HG result in fatal disorders in mammals, accumulation of l-2HG in plants does not adversely affect their development under a range of tested conditions. However, orthologs of l-2HGDH are found in all examined genomes of viridiplantae, indicating that the repair reaction we identified makes an essential contribution to plant fitness in as yet unidentified conditions in the wild.

Adaptive mutations in sugar metabolism restore growth on glucose in a pyruvate decarboxylase negative yeast strain.

BACKGROUND: A Saccharomyces cerevisiae strain carrying deletions in all three pyruvate decarboxylase (PDC) genes (also called Pdc negative yeast) represents a non-ethanol producing platform strain for the production of pyruvate derived biochemicals. However, it cannot grow on glucose as the sole carbon source, and requires supplementation of C2 compounds to the medium in order to meet the requirement for cytosolic acetyl-CoA for biosynthesis of fatty acids and ergosterol. RESULTS: In this study, a Pdc negative strain was adaptively evolved for improved growth in glucose medium via serial transfer, resulting in three independently evolved strains, which were able to grow in minimal medium containing glucose as the sole carbon source at the maximum specific rates of 0.138, 0.148, 0.141 h(-1), respectively. Several genetic changes were identified in the evolved Pdc negative strains by genomic DNA sequencing. Among these genetic changes, 4 genes were found to carry point mutations in at least two of the evolved strains: MTH1 encoding a negative regulator of the glucose-sensing signal transduction pathway, HXT2 encoding a hexose transporter, CIT1 encoding a mitochondrial citrate synthase, and RPD3 encoding a histone deacetylase. Reverse engineering of the non-evolved Pdc negative strain through introduction of the MTH1 (81D) allele restored its growth on glucose at a maximum specific rate of 0.053 h(-1) in minimal medium with 2% glucose, and the CIT1 deletion in the reverse engineered strain further increased the maximum specific growth rate to 0.069 h(-1). CONCLUSIONS: In this study, possible evolving mechanisms of Pdc negative strains on glucose were investigated by genome sequencing and reverse engineering. The non-synonymous mutations in MTH1 alleviated the glucose repression by repressing expression of several hexose transporter genes. The non-synonymous mutations in HXT2 and CIT1 may function in the presence of mutated MTH1 alleles and could be related to an altered central carbon metabolism in order to ensure production of cytosolic acetyl-CoA in the Pdc negative strain.

A general model to predict small molecule substrates of enzymes based on machine and deep learning.

For most proteins annotated as enzymes, it is unknown which primary and/or secondary reactions they catalyze. Experimental characterizations of potential substrates are time-consuming and costly. Machine learning predictions could provide an efficient alternative, but are hampered by a lack of information regarding enzyme non-substrates, as available training data comprises mainly positive examples. Here, we present ESP, a general machine-learning model for the prediction of enzyme-substrate pairs with an accuracy of over 91% on independent and diverse test data. ESP can be applied successfully across widely different enzymes and a broad range of metabolites included in the training data, outperforming models designed for individual, well-studied enzyme families. ESP represents enzymes through a modified transformer model, and is trained on data augmented with randomly sampled small molecules assigned as non-substrates. By facilitating easy in silico testing of potential substrates, the ESP web server may support both basic and applied science.