The Alanine World Model for the Development of the Amino Acid Repertoire in Protein Biosynthesis

Evolution of Pyrrolysyl-tRNA Synthetase: From Methanogenesis to Genetic Code Expansion

Over 20 years ago, the pyrrolysine encoding translation system was discovered in specific archaea. Our Review provides an overview of how the once obscure pyrrolysyl-tRNA synthetase (PylRS) tRNA pair, originally responsible for accurately translating enzymes crucial in methanogenic metabolic pathways, laid the foundation for the burgeoning field of genetic code expansion. Our primary focus is the discussion of how to successfully engineer the PylRS to recognize new substrates and exhibit higher in vivo activity. We have compiled a comprehensive list of ncAAs incorporable with the PylRS system. Additionally, we also summarize recent successful applications of the PylRS system in creating innovative therapeutic solutions, such as new antibody-drug conjugates, advancements in vaccine modalities, and the potential production of new antimicrobials.

Proline Analogues

Within the canonical repertoire of the amino acid involved in protein biogenesis, proline plays a unique role as an amino acid presenting a modified backbone rather than a side-chain. Chemical structures that mimic proline but introduce changes into its specific molecular features are defined as proline analogues. This review article summarizes the existing chemical, physicochemical, and biochemical knowledge about this peculiar family of structures. We group proline analogues from the following compounds: substituted prolines, unsaturated and fused structures, ring size homologues, heterocyclic, e.g., pseudoproline, and bridged proline-resembling structures. We overview (1) the occurrence of proline analogues in nature and their chemical synthesis, (2) physicochemical properties including ring conformation and cis/trans amide isomerization, (3) use in commercial drugs such as nirmatrelvir recently approved against COVID-19, (4) peptide and protein synthesis involving proline analogues, (5) specific opportunities created in peptide engineering, and (6) cases of protein engineering with the analogues. The review aims to provide a summary to anyone interested in using proline analogues in systems ranging from specific biochemical setups to complex biological systems.

Secondary Amine Catalysis in Enzyme Design: Broadening Protein Template Diversity through Genetic Code Expansion

Secondary amines, due to their reactivity, can transform protein templates into catalytically active entities, accelerating the development of artificial enzymes. However, existing methods, predominantly reliant on modified ligands or N-terminal prolines, impose significant limitations on template selection. In this study, genetic code expansion was used to break this boundary, enabling secondary amines to be incorporated into alternative proteins and positions of choice. Pyrrolysine analogues carrying different secondary amines could be incorporated into superfolder green fluorescent protein (sfGFP), multidrug-binding LmrR and nucleotide-binding dihydrofolate reductase (DHFR). Notably, the analogue containing a D-proline moiety demonstrated both proteolytic stability and catalytic activity, conferring LmrR and DHFR with the desired transfer hydrogenation activity. While the LmrR variants were confined to the biomimetic 1-benzyl-1,4-dihydronicotinamide (BNAH) as the hydride source, the optimal DHFR variant favorably used the pro-R hydride from NADPH for stereoselective reactions (e.r. up to 92 : 8), highlighting that a switch of protein template could broaden the nucleophile option for catalysis. Owing to the cofactor compatibility, the DHFR-based secondary amine catalysis could be integrated into an enzymatic recycling scheme. This established method shows substantial potential in enzyme design, applicable from studies on enzyme evolution to the development of new biocatalysts.

Metabolomics analysis reveals novel serum metabolite alterations in cancer cachexia

Background

Cachexia is a body wasting syndrome that significantly affects well-being and prognosis of cancer patients, without effective treatment. Serum metabolites take part in pathophysiological processes of cancer cachexia, but apart from altered levels of select serum metabolites, little is known on the global changes of the overall serum metabolome, which represents a functional readout of the whole-body metabolic state. Here, we aimed to comprehensively characterize serum metabolite alterations and analyze associated pathways in cachectic cancer patients to gain new insights that could help instruct strategies for novel interventions of greater clinical benefit.

Methods

Serum was sampled from 120 metastatic cancer patients (stage UICC IV). Patients were grouped as cachectic or non-cachectic according to the criteria for cancer cachexia agreed upon international consensus (main criterium: weight loss adjusted to body mass index). Samples were pooled by cachexia phenotype and assayed using non-targeted gas chromatography-mass spectrometry (GC-MS). Normalized metabolite levels were compared using t-test (p < 0.05, adjusted for false discovery rate) and partial least squares discriminant analysis (PLS-DA). Machine-learning models were applied to identify metabolite signatures for separating cachexia states. Significant metabolites underwent MetaboAnalyst 5.0 pathway analysis.

Results

Comparative analyses included 78 cachectic and 42 non-cachectic patients. Cachectic patients exhibited 19 annotable, significantly elevated (including glucose and fructose) or decreased (mostly amino acids) metabolites associating with aminoacyl-tRNA, glutathione and amino acid metabolism pathways. PLS-DA showed distinct clusters (accuracy: 85.6%), and machine-learning models identified metabolic signatures for separating cachectic states (accuracy: 83.2%; area under ROC: 88.0%). We newly identified altered blood levels of erythronic acid and glucuronic acid in human cancer cachexia, potentially linked to pentose-phosphate and detoxification pathways.

Conclusion

We found both known and yet unknown serum metabolite and metabolic pathway alterations in cachectic cancer patients that collectively support a whole-body metabolic state with impaired detoxification capability, altered glucose and fructose metabolism, and substrate supply for increased and/or distinct metabolic needs of cachexia-associated tumors. These findings together imply vulnerabilities, dependencies and targets for novel interventions that have potential to make a significant impact on future research in an important field of cancer patient care.

Multilocus functional characterization of indigenous and exotic inbreds for dgat1-2, fatb, ge2 and wri1a genes affecting kernel oil and fatty acid profile in maize

Demand for maize oil is progressively increasing due to its diverse industrial applications, aside from its primary role in human nutrition and animal feed. Oil content and composition are two crucial determinants of maize oil in the international market. As kernel oil in maize is a complex quantitative trait, improving this trait presents a challenge for plant breeders and biotechnologists. Here, we characterized a set of 292 diverse maize inbreds of both indigenous and exotic origin by exploiting functional polymorphism of the dgat1-2, fatb, ge2, and wri1a genes governing kernel oil in maize. Genotyping using gene-based functional markers revealed a lower frequencies of dgat1-2 (0.15) and fatb (0.12) mutant alleles and a higher frequencies of wild-type alleles (Dgat1-2: 0.85; fatB: 0.88). The favorable wri1a allele was conserved across genotypes, while its wild-type allele (WRI1a) was not detected. In contrast, none of the genotypes possessed the ge2 favorable allele. The frequency of favorable alleles of both dgat1-2 and fatb decreased to 0.03 when considered together. Furthermore, pairwise protein-protein interactions among target gene products were conducted to understand the effect of one protein on another and their responses to kernel oil through functional enrichments. Thus, the identified maize genotypes with dgat1-2, fatb, and wri1a favourable alleles, along with insights gained through the protein-protein association network, serve as prominent and unique genetic resources for high-oil maize breeding programs. This is the first comprehensive report on the functional characterization of diverse genotypes at the molecular and protein levels.

Protein structure prediction with in-cell photo-crosslinking mass spectrometry and deep learning

While AlphaFold2 can predict accurate protein structures from the primary sequence, challenges remain for proteins that undergo conformational changes or for which few homologous sequences are known. Here we introduce AlphaLink, a modified version of the AlphaFold2 algorithm that incorporates experimental distance restraint information into its network architecture. By employing sparse experimental contacts as anchor points, AlphaLink improves on the performance of AlphaFold2 in predicting challenging targets. We confirm this experimentally by using the noncanonical amino acid photo-leucine to obtain information on residue-residue contacts inside cells by crosslinking mass spectrometry. The program can predict distinct conformations of proteins on the basis of the distance restraints provided, demonstrating the value of experimental data in driving protein structure prediction. The noise-tolerant framework for integrating data in protein structure prediction presented here opens a path to accurate characterization of protein structures from in-cell data.

Determination of Vibrational Modes of l-Alanine Single Crystals by a Combination of Terahertz Spectroscopy Measurements and Density Functional Calculations

Density-functional theory may be used to predict both the frequency and the dipole moment of the fundamental oscillations of molecular crystals. Suitably polarized photons at those frequencies excite such oscillations. Thus, in principle, terahertz spectroscopy may confirm the calculated fundamental modes of amino acids. However, reports to date have multiple shortcomings: (a) material of uncertain purity and morphology and diluted in a binder material is employed; (b) consequently, vibrations along all crystal axes are excited simultaneously; (c) data are restricted to room temperature, where resonances are broad and the background dominant; and (d) comparison with theory has been unsatisfactory (in part because the theory assumes zero temperature). Here, we overcome all four obstacles, in reporting detailed low-temperature polarized THz spectra of single-crystal l-alanine, assigning vibrational modes using density-functional theory, and comparing the calculated dipole moment vector direction to the electric field polarization of the measured spectra. Our direct and detailed comparison of theory with experiment corrects previous mode assignments for l-alanine, and reveals unreported modes, previously obscured by closely spaced spectral absorptions. The fundamental modes are thereby determined.

Engineering membrane architecture for biotechnological applications

Cellular membranes, predominantly described as a dynamic bilayer, are composed of different lipids, transmembrane proteins, and carbohydrates. Most research on biological membranes focuses on the identification, characterization, and mechanistic aspects of their different components. These studies provide a fundamental understanding of membrane structure, function, and dynamics, establishing a basis for the development of membrane engineering strategies. To date, approaches in this field concentrate on membrane adaptation to harsh conditions during industrial fermentation, which can be caused by temperature, osmotic, or organic solvent stress. With advances in the field of metabolic engineering and synthetic biology, recent breakthroughs include proof of concept microbial production of essential medicines, such as cannabinoids and vinblastine. However, long pathways, low yields, and host adaptation continue to pose challenges to the efficient scale up production of many important compounds. The lipid bilayer is profoundly linked to the activity of heterologous membrane-bound enzymes and transport of metabolites. Therefore, strategies for improving enzyme performance, facilitating pathway reconstruction, and enabling storage of products to increase the yields directly involve cellular membranes. At the forefront of membrane engineering research are re-emerging approaches in lipid research and synthetic biology that manipulate membrane size and composition and target lipid profiles across species. This review summarizes engineering strategies applied to cellular membranes and discusses the challenges and future perspectives, particularly with regards to their applications in host engineering and bioproduction.

Screening for Primordial RNA–Peptide Interactions Using High-Density Peptide Arrays

RNA–peptide interactions are an important factor in the origin of the modern mechanism of translation and the genetic code. Despite great progress in the bioinformatics of RNA–peptide interactions due to the rapid growth in the number of known RNA–protein complexes, there is no comprehensive experimental method to take into account the influence of individual amino acids on non-covalent RNA–peptide bonds. First, we designed the combinatorial libraries of primordial peptides according to the combinatorial fusion rules based on Watson–Crick mutations. Next, we used high-density peptide arrays to investigate the interaction of primordial peptides with their cognate homo-oligonucleotides. We calculated the interaction scores of individual peptide fragments and evaluated the influence of the peptide length and its composition on the strength of RNA binding. The analysis shows that the amino acids phenylalanine, tyrosine, and proline contribute significantly to the strong binding between peptides and homo-oligonucleotides, while the sum charge of the peptide does not have a significant effect. We discuss the physicochemical implications of the combinatorial fusion cascade, a hypothesis that follows from the amino acid partition used in the work.

On the Evolutionary History of the Twenty Encoded Amino Acids

α-Amino acids are essential molecular constituents of life, twenty of which are privileged because they are encoded by the ribosomal machinery. The question remains open as to why this number and why this 20 in particular, an almost philosophical question that cannot be conclusively resolved. They are closely related to the evolution of the genetic code and whether nucleic acids, amino acids, and peptides appeared simultaneously and were available under prebiotic conditions when the first self-sufficient complex molecular system emerged on Earth. This report focuses on prebiotic and metabolic aspects of amino acids and proteins starting with meteorites, followed by their formation, including peptides, under plausible prebiotic conditions, and the major biosynthetic pathways in the various kingdoms of life. Coenzymes play a key role in the present analysis in that amino acid metabolism is linked to glycolysis and different variants of the tricarboxylic acid cycle (TCA, rTCA, and the incomplete horseshoe version) as well as the biosynthesis of the most important coenzymes. Thus, the report opens additional perspectives and facets on the molecular evolution of primary metabolism.

Evolutionary Origin and Functional Diversification of Aminotransferases

Aminotransferases (ATs) are pyridoxal 5′-phosphate–dependent enzymes that catalyze the transamination reactions between amino acid donor and keto acid acceptor substrates. Modern AT enzymes constitute ∼2% of all classified enzymatic activities, play central roles in nitrogen metabolism, and generate multitude of primary and secondary metabolites. ATs likely diverged into four distinct AT classes before the appearance of the last universal common ancestor and further expanded to a large and diverse enzyme family. Although the AT family underwent an extensive functional specialization, many AT enzymes retained considerable substrate promiscuity and multifunctionality because of their inherent mechanistic, structural, and functional constraints. This review summarizes the evolutionary history, diverse metabolic roles, reaction mechanisms, and structure–function relationships of the AT family enzymes, with a special emphasis on their substrate promiscuity and multifunctionality. Comprehensive characterization of AT substrate specificity is still needed to reveal their true metabolic functions in interconnecting various branches of the nitrogen metabolic network in different organisms.

Efficient Oligomerization of Aromatic Amino Acids Induced by Gaps in Four-Helix Bundles of DNA or RNA

The formation of peptides from amino acids is one of the processes associated with life. Because of the dominant role of translation in extant biology, peptide‐forming processes that are RNA induced are of particular interest. We have previously reported the formation of phosphoramidate‐linked peptido RNAs as the products of spontaneous condensation reactions between ribonucleotides and free amino acids in aqueous solution. We now asked whether four‐helix bundle (4HB) DNA or RNA folding motifs with a single‐ or double‐nucleotide gap next to a 5’‐phosphate can act as reaction sites for phosphoramidate formation. For glycine, this was found to be the case, whereas phenylalanine and tryptophan showed accelerated formation of peptides without a covalent link to the nucleic acid. Free peptides with up to 11 tryptophan or phenylalanine residues were found in precipitates forming in the presence of gap‐containing DNA or RNA 4HBs. Control experiments using motifs with just a nick or primer alone did not have the same effect. Because folded structures with a gap in a double helix are likely products of hybridization of strands formed in statistically controlled oligomerization reactions, our results are interesting in the context of prebiotic scenarios. Independent of a putative role in evolution, our findings suggest that for some aromatic amino acids an RNA‐induced pathway for oligomerization exists that does not have a discernable link to translation.

Genome Evolution from Random Ligation of RNAs of Autocatalytic Sets

The evolutionary origin of the genome remains elusive. Here, I hypothesize that its first iteration, the protogenome, was a multi-ribozyme RNA. It evolved, likely within liposomes (the protocells) forming in dry-wet cycling environments, through the random fusion of ribozymes by a ligase and was amplified by a polymerase. The protogenome thereby linked, in one molecule, the information required to seed the protometabolism (a combination of RNA-based autocatalytic sets) in newly forming protocells. If this combination of autocatalytic sets was evolutionarily advantageous, the protogenome would have amplified in a population of multiplying protocells. It likely was a quasispecies with redundant information, e.g., multiple copies of one ribozyme. As such, new functionalities could evolve, including a genetic code. Once one or more components of the protometabolism were templated by the protogenome (e.g., when a ribozyme was replaced by a protein enzyme), and/or addiction modules evolved, the protometabolism became dependent on the protogenome. Along with increasing fidelity of the RNA polymerase, the protogenome could grow, e.g., by incorporating additional ribozyme domains. Finally, the protogenome could have evolved into a DNA genome with increased stability and storage capacity. I will provide suggestions for experiments to test some aspects of this hypothesis, such as evaluating the ability of ribozyme RNA polymerases to generate random ligation products and testing the catalytic activity of linked ribozyme domains.

The Combinatorial Fusion Cascade to Generate the Standard Genetic Code

Combinatorial fusion cascade was proposed as a transition stage between prebiotic chemistry and early forms of life. The combinatorial fusion cascade consists of three stages: eight initial complimentary pairs of amino acids, four protocodes, and the standard genetic code. The initial complimentary pairs and the protocodes are divided into dominant and recessive entities. The transitions between these stages obey the same combinatorial fusion rules for all amino acids. The combinatorial fusion cascade mathematically describes the codon assignments in the standard genetic code. It explains the availability of amino acids with the even and odd numbers of codons, the appearance of stop codons, inclusion of novel canonical amino acids, exceptional high numbers of codons for amino acids arginine, leucine, and serine, and the temporal order of amino acid inclusion into the genetic code. The temporal order of amino acids within the cascade is congruent with the consensus temporal order previously derived from the similarities between the available hypotheses. The control over the combinatorial fusion cascades would open the road for a novel technology to develop artificial microorganisms.

Biochemistry of fluoroprolines: the prospect of making fluorine a bioelement

Due to the heterocyclic structure and distinct conformational profile, proline is unique in the repertoire of the 20 amino acids coded into proteins. Here, we summarize the biochemical work on the replacement of proline with (4R)- and (4S)-fluoroproline as well as 4,4-difluoroproline in proteins done mainly in the last two decades. We first recapitulate the complex position and biochemical fate of proline in the biochemistry of a cell, discuss the physicochemical properties of fluoroprolines, and overview the attempts to use these amino acids as proline replacements in studies of protein production and folding. Fluorinated proline replacements are able to elevate the protein expression speed and yields and improve the thermodynamic and kinetic folding profiles of individual proteins. In this context, fluoroprolines can be viewed as useful tools in the biotechnological toolbox. As a prospect, we envision that proteome-wide proline-to-fluoroproline substitutions could be possible. We suggest a hypothetical scenario for the use of laboratory evolutionary methods with fluoroprolines as a suitable vehicle to introduce fluorine into living cells. This approach may enable creation of synthetic cells endowed with artificial biodiversity, containing fluorine as a bioelement.

Courses Based on iGEM/BIOMOD Competitions Are the Ideal Format for Research-Based Learning of Xenobiology

Synthetic biology and especially xenobiology, as emerging new fields of science, have reached an intellectual and experimental maturity that makes them suitable for integration into the university curricula of chemical and biological disciplines. Novel scientific fields that include laboratory work are perfect playgrounds for developing highly motivating research-based teaching modules. We believe that research-based learning enriched by digital tools is the best approach for teaching new emerging essentials of academic education. This is especially true when the scientific field as such is still not canonized with text books and best-practice examples. Our experience shows that iGEM/BIOMOD competitions represent an excellent basis for designing research-based courses in xenobiology. Therefore, we present a report on "iGEM-Synthetic Biology" offered at the Technische Universität Berlin as an example.