How synonymous mutations alter enzyme structure and function over long timescales

Mut-Map: Comprehensive Computational Pipeline for Structural Mapping and Analysis of Cancer-Associated Mutations

Understanding the functional impact of genetic mutations on protein structures is essential for advancing cancer research and developing targeted therapies. The main challenge lies in accurately mapping these mutations to protein structures and analysing their effects on protein function. To address this, Mut-Map (https://genemutation.org/) is a comprehensive computational pipeline designed to integrate mutation data from the Catalogue Of Somatic Mutations In Cancer database with protein structural data from the Protein Data Bank and AlphaFold models. The pipeline begins by taking a UniProt ID and proceeds through mapping corresponding Protein Data Bank structures, renumbering residues, and assessing disorder percentages. It then overlays mutation data, categorizes mutations based on structural context, and visualizes them using advanced tools like MolStar. This approach allows for a detailed analysis of how mutations may disrupt protein function by affecting key regions such as DNA interfaces, ligand-binding sites, and dimer interactions. To validate the pipeline, a case study on the TP53 gene, a critical tumour suppressor often mutated in cancers, was conducted. The analysis highlighted the most frequent mutations occurring at the DNA-binding interface, providing insights into their potential role in cancer progression. Mut-Map offers a powerful resource for elucidating the structural implications of cancer-associated mutations, paving the way for more targeted therapeutic strategies and advancing our understanding of protein structure-function relationships.

Translation Rates and Protein Folding

The mRNA coding sequence defines not only the amino acid sequence of the protein, but also the speed at which the ribosomes move along the mRNA while making the protein. The non-uniform local kinetics - denoted as translational rhythm - is similar among mRNAs coding for related protein folds. Deviations from this conserved rhythm can result in protein misfolding. In this review we summarize the experimental evidence demonstrating how local translation rates affect cotranslational protein folding, with the focus on the synonymous codons and patches of charged residues in the nascent peptide as best-studied examples. Alterations in nascent protein conformations due to disturbed translational rhythm can persist off the ribosome, as demonstrated by the effects of synonymous codon variants of several disease-related proteins. Charged amino acid patches in nascent chains also modulate translation and cotranslational protein folding, and can abrogate translation when placed at the N-terminus of the nascent peptide. During cotranslational folding, incomplete nascent chains navigate through a unique conformational landscape in which earlier intermediate states become inaccessible as the nascent peptide grows. Precisely tuned local translation rates, as well as interactions with the ribosome, guide the folding pathway towards the native structure, whereas deviations from the natural translation rhythm may favor pathways leading to trapped misfolded states. Deciphering the 'folding code' of the mRNA will contribute to understanding the diseases caused by protein misfolding and to rational protein design.

Development of a new affinity maturation protocol for the construction of an internalizing anti-nucleolin antibody library

Over the last decades, monoclonal antibodies have substantially improved the treatment of several conditions. The continuous search for novel therapeutic targets and improvements in antibody's structure, demands for a constant optimization of their development. In this regard, modulation of an antibody's affinity to its target has been largely explored and culminated in the discovery and optimization of a variety of molecules. It involves the creation of antibody libraries and selection against the target of interest. In this work, we aimed at developing a novel protocol to be used for the affinity maturation of an antibody previously developed by our group. An antibody library was constructed using an in vivo random mutagenesis approach that, to our knowledge, has not been used before for antibody development. Then, a cell-based phage display selection protocol was designed to allow the fast and simple screening of antibody clones capable of being internalized by target cells. Next generation sequencing coupled with computer analysis provided an extensive characterization of the created library and post-selection pool, that can be used as a guide for future antibody development. With a single selection step, an enrichment in the mutated antibody library, given by a decrease in almost 50% in sequence diversity, was achieved, and structural information useful in the study of the antibody-target interaction in the future was obtained.

Quantifying negative selection on synonymous variants

Widespread adoption of DNA sequencing has resulted in large numbers of genetic variants, whose contribution to disease is not easily determined. Although many types of variation are known to disrupt cellular processes in predictable ways, for some categories of variants, the effects may not be directly detectable. A particular example is synonymous variants, that is, those single-nucleotide variants that create a codon substitution, such that the produced amino acid sequence is unaffected. Contrary to the original theory suggesting that synonymous variants are benign, there is a growing volume of research showing that, despite their "silent" mechanism of action, some synonymous variation may be deleterious. Here, we studied the extent of the negative selective pressure acting on different classes of synonymous variants by analyzing the relative enrichment of synonymous singleton variants in the human exomes provided by gnomAD. Using a modification of the mutability-adjusted proportion of singletons (MAPS) metric as a measure of purifying selection, we found that some classes of synonymous variants are subject to stronger negative selection than others. For instance, variants that reduce codon optimality undergo stronger selection than optimality-increasing variants. Besides, selection affects synonymous variants implicated in splice-site-loss or splice-site-gain events. To understand what drives this negative selection, we tested a number of predictors in the aim to explain the variability in the selection scores. Our findings provide insights into the effects of synonymous variants at the population level, highlighting the specifics of the role that these variants play in health and disease.

It is theoretically possible to avoid misfolding into non-covalent lasso entanglements using small molecule drugs

A novel class of protein misfolding characterized by either the formation of non-native noncovalent lasso entanglements in the misfolded structure or loss of native entanglements has been predicted to exist and found circumstantial support through biochemical assays and limited-proteolysis mass spectrometry data. Here, we examine whether it is possible to design small molecule compounds that can bind to specific folding intermediates and thereby avoid these misfolded states in computer simulations under idealized conditions (perfect drug-binding specificity, zero promiscuity, and a smooth energy landscape). Studying two proteins, type III chloramphenicol acetyltransferase (CAT-III) and D-alanyl-D-alanine ligase B (DDLB), that were previously suggested to form soluble misfolded states through a mechanism involving a failure-to-form of native entanglements, we explore two different drug design strategies using coarse-grained structure-based models. The first strategy, in which the native entanglement is stabilized by drug binding, failed to decrease misfolding because it formed an alternative entanglement at a nearby region. The second strategy, in which a small molecule was designed to bind to a non-native tertiary structure and thereby destabilize the native entanglement, succeeded in decreasing misfolding and increasing the native state population. This strategy worked because destabilizing the entanglement loop provided more time for the threading segment to position itself correctly to be wrapped by the loop to form the native entanglement. Further, we computationally identified several FDA-approved drugs with the potential to bind these intermediate states and rescue misfolding in these proteins. This study suggests it is possible for small molecule drugs to prevent protein misfolding of this type.

Specific codons control cellular resources and fitness

As cellular engineering progresses from simply overexpressing proteins to imparting complex phenotypes through multigene expression, judicious appropriation of cellular resources is essential. Since codon use is degenerate and biased, codons may control cellular resources at a translational level. We investigate how partitioning transfer RNA (tRNA) resources by incorporating dissimilar codon usage can drastically alter interdependence of expression level and burden on the host. By isolating the effect of individual codons' use during translation elongation while eliminating confounding factors, we show that codon choice can trans-regulate fitness of the host and expression of other heterologous or native genes. We correlate specific codon usage patterns with host fitness and derive a coding scheme for multigene expression called the Codon Health Index (CHI, χ). This empirically derived coding scheme (χ) enables the design of multigene expression systems that avoid catastrophic cellular burden and is robust across several proteins and conditions.

Oxidative stress resistance prompts pyrroloquinoline quinone biosynthesis in Hyphomicrobium denitrificans H4-45

Pyrroloquinoline quinone (PQQ) is a natural antioxidant with diverse applications in food and pharmaceutical industries. A lot of effort has been devoted toward the discovery of PQQ high-producing microbial species and characterization of biosynthesis, but it is still challenging to achieve a high PQQ yield. In this study, a combined strategy of random mutagenesis and adaptive laboratory evolution (ALE) with fermentation optimization was applied to improve PQQ production in Hyphomicrobium denitrificans H4-45. A mutant strain AE-9 was obtained after nearly 400 generations of UV-LiCl mutagenesis, followed by an ALE process, which was conducted with a consecutive increase of oxidative stress generated by kanamycin, sodium sulfide, and potassium tellurite. In the flask culture condition, the PQQ production in mutant strain AE-9 had an 80.4% increase, and the cell density increased by 14.9% when compared with that of the initial strain H4-45. Moreover, batch and fed-batch fermentation processes were optimized to further improve PQQ production by pH control strategy, methanol and H2O2 feed flow, and segmented fermentation process. Finally, the highest PQQ production and productivity of the mutant strain AE-9 reached 307 mg/L and 4.26 mg/L/h in a 3.7-L bioreactor, respectively. Whole genome sequencing analysis showed that genetic mutations in the ftfL gene and thiC gene might contribute to improving PQQ production by enhancing methanol consumption and cell growth in the AE-9 strain. Our study provided a systematic strategy to obtain a PQQ high-producing mutant strain and achieve high production of PQQ in fermentation. These practical methods could be applicable to improve the production of other antioxidant compounds with uncleared regulation mechanisms. KEY POINTS: • Improvement of PQQ production by UV-LiCl mutagenesis combined with adaptive laboratory evolution (ALE) and fermentation optimization. • A consecutive increase of oxidative stress could be used as the antagonistic factor for ALE to enhance PQQ production. • Mutations in the ftfL gene and thiC gene indicated that PQQ production might be increased by enhancing methanol consumption and cell growth.

How the ribosome shapes cotranslational protein folding

During protein synthesis, the growing nascent peptide chain moves inside the polypeptide exit tunnel of the ribosome from the peptidyl transferase center towards the exit port where it emerges into the cytoplasm. The ribosome defines the unique energy landscape of the pioneering round of protein folding. The spatial confinement and the interactions of the nascent peptide with the tunnel walls facilitate formation of secondary structures, such as α-helices. The vectorial nature of protein folding inside the tunnel favors local intra- and inter-molecular interactions, thereby inducing cotranslational folding intermediates that do not form upon protein refolding in solution. Tertiary structures start to fold in the lower part of the tunnel, where interactions with the ribosome destabilize native protein folds. The present review summarizes the recent progress in understanding the driving forces of nascent protein folding inside the tunnel and at the surface of the ribosome.

Comparative analysis of codon usage patterns of Plasmodium helical interspersed subtelomeric (PHIST) proteins

Background

Plasmodium falciparum is a protozoan parasite that causes the most severe form of malaria in humans worldwide, which is predominantly found in sub-Saharan Africa, where it is responsible for the majority of malaria-related deaths. Plasmodium helical interspersed subtelomeric (PHIST) proteins are a family of proteins, with a conserved PHIST domain, which are typically located at the subtelomeric regions of the Plasmodium falciparum chromosomes and play crucial roles in the interaction between the parasite and its human host, such as cytoadherence, immune evasion, and host cell remodeling. However, the specific utilization of synonymous codons by PHIST proteins in Plasmodium falciparum is still unknown.

Methods

Codon usage bias (CUB) refers to the unequal usage of synonymous codons during translation, resulting in over- or underrepresentation of certain nucleotide patterns. This imbalance in CUB can impact various cellular processes, including protein expression levels and genetic variation. To investigate this, the CUB of 88 PHIST protein coding sequences (CDSs) from 5 subgroups were analyzed in this study.

Results

The results showed that both codon base composition and relative synonymous codon usage (RSCU) analysis identified a higher occurrence of AT-ended codons (AGA and UUA) in PHIST proteins of Plasmodium falciparum. The average effective number of codons (ENC) for these PHIST proteins was 36.69, indicating a weak codon preference among them, as it was greater than 35. Additionally, the correlation analysis among codon base composition (GC1, GC2, GC3, GCs), codon adaptation index (CAI), codon bias index (CBI), frequency of optimal codons (FOP), ENC, general average hydropathicity (GRAVY), aromaticity (AROMO), length of synonymous codons (L_sym), and length of amino acids (L_aa) revealed the influence of base composition and codon usage indices on codon usage bias, with GC1 having a significant impact in this study. Furthermore, the neutrality plot analysis, PR2-bias plot analysis, and ENC-GC3 plot analysis provided additional evidence that natural selection plays a crucial role in determining codon bias in PHIST proteins.

Conclusion

In conclusion, this study has enhanced our understanding of the characteristics of codon usage and genetic evolution in PHIST proteins, thereby providing data foundation for further research on antimalarial drugs or vaccines.

Analysis of codon usage bias of thioredoxin in apicomplexan protozoa

BACKGROUND

Apicomplexan protozoa are a diverse group of obligate intracellular parasites causing many diseases that affect humans and animals, such as malaria, toxoplasmosis, and cryptosporidiosis. Apicomplexan protozoa possess unique thioredoxins (Trxs) that have been shown to regulate various cellular processes including metabolic redox regulation, parasite survival, and host immune evasion. However, it is still unknown how synonymous codons are used by apicomplexan protozoa Trxs.

METHODS

Codon usage bias (CUB) is the unequal usage of synonymous codons during translation which leads to the over- or underrepresentation of certain nucleotide patterns. This imbalance in CUB can impact a variety of cellular processes including protein expression levels and genetic variation. This study analyzed the CUB of 32 Trx coding sequences (CDS) from 11 apicomplexan protozoa.

RESULTS

The results showed that both codon base composition and relative synonymous codon usage (RSCU) analysis revealed that AT-ended codons were more frequently used in Cryptosporidium spp. and Plasmodium spp., while the Eimeria spp., Babesia spp., Hammondia hammondi, Neospora caninum, and Toxoplasma gondii tended to end in G/C. The average effective number of codon (ENC) value of these apicomplexan protozoa is 46.59, which is > 35, indicating a weak codon preference among apicomplexan protozoa Trxs. Furthermore, the correlation analysis among codon base composition (GC1, GC2, GC3, GCs), codon adaptation index (CAI), codon bias index (CBI), frequency of optimal codons (FOP), ENC, general average hydropathicity (GRAVY), aromaticity (AROMO), length of synonymous codons (L_sym), and length of amino acids (L_aa) indicated the influence of base composition and codon usage indices on CUB. Additionally, the neutrality plot analysis, PR2-bias plot analysis, and ENC-GC3 plot analysis further demonstrated that natural selection plays an important role in apicomplexan protozoa Trxs codon bias.

CONCLUSIONS

In conclusion, this study increased the understanding of codon usage characteristics and genetic evolution of apicomplexan protozoa Trxs, which expanded new ideas for vaccine and drug research.

Machine Learning-Guided Protein Engineering

Recent progress in engineering highly promising biocatalysts has increasingly involved machine learning methods. These methods leverage existing experimental and simulation data to aid in the discovery and annotation of promising enzymes, as well as in suggesting beneficial mutations for improving known targets. The field of machine learning for protein engineering is gathering steam, driven by recent success stories and notable progress in other areas. It already encompasses ambitious tasks such as understanding and predicting protein structure and function, catalytic efficiency, enantioselectivity, protein dynamics, stability, solubility, aggregation, and more. Nonetheless, the field is still evolving, with many challenges to overcome and questions to address. In this Perspective, we provide an overview of ongoing trends in this domain, highlight recent case studies, and examine the current limitations of machine learning-based methods. We emphasize the crucial importance of thorough experimental validation of emerging models before their use for rational protein design. We present our opinions on the fundamental problems and outline the potential directions for future research.

Folding kinetics of an entangled protein

The possibility of the protein backbone adopting lasso-like entangled motifs has attracted increasing attention. After discovering the surprising abundance of natively entangled protein domain structures, it was shown that misfolded entangled subpopulations might become thermosensitive or escape the homeostasis network just after translation. To investigate the role of entanglement in shaping folding kinetics, we introduce a novel indicator and analyze simulations of a coarse-grained, structure-based model for two small single-domain proteins. The model recapitulates the well-known two-state folding mechanism of a non-entangled SH3 domain. However, despite its small size, a natively entangled antifreeze RD1 protein displays a rich refolding behavior, populating two distinct kinetic intermediates: a short-lived, entangled, near-unfolded state and a longer-lived, non-entangled, near-native state. The former directs refolding along a fast pathway, whereas the latter is a kinetic trap, consistently with known experimental evidence of two different characteristic times. Upon trapping, the natively entangled loop folds without being threaded by the N-terminal residues. After trapping, the native entangled structure emerges by either backtracking to the unfolded state or threading through the already formed but not yet entangled loop. Along the fast pathway, trapping does not occur because the native contacts at the closure of the lasso-like loop fold after those involved in the N-terminal thread, confirming previous predictions. Despite this, entanglement may appear already in unfolded configurations. Remarkably, a longer-lived, near-native intermediate, with non-native entanglement properties, recalls what was observed in cotranslational folding.

Protein conformational ensembles in function: roles and mechanisms

The sequence-structure-function paradigm has dominated twentieth century molecular biology. The paradigm tacitly stipulated that for each sequence there exists a single, well-organized protein structure. Yet, to sustain cell life, function requires (i) that there be more than a single structure, (ii) that there be switching between the structures, and (iii) that the structures be incompletely organized. These fundamental tenets called for an updated sequence-conformational ensemble-function paradigm. The powerful energy landscape idea, which is the foundation of modernized molecular biology, imported the conformational ensemble framework from physics and chemistry. This framework embraces the recognition that proteins are dynamic and are always interconverting between conformational states with varying energies. The more stable the conformation the more populated it is. The changes in the populations of the states are required for cell life. As an example, in vivo, under physiological conditions, wild type kinases commonly populate their more stable "closed", inactive, conformations. However, there are minor populations of the "open", ligand-free states. Upon their stabilization, e.g., by high affinity interactions or mutations, their ensembles shift to occupy the active states. Here we discuss the role of conformational propensities in function. We provide multiple examples of diverse systems, including protein kinases, lipid kinases, and Ras GTPases, discuss diverse conformational mechanisms, and provide a broad outlook on protein ensembles in the cell. We propose that the number of molecules in the active state (inactive for repressors), determine protein function, and that the dynamic, relative conformational propensities, rather than the rigid structures, are the hallmark of cell life.

Identification of the lipodepsipeptide selethramide encoded in a giant nonribosomal peptide synthetase from a Burkholderia bacterium

Bacterial natural products have found many important industrial applications. Yet traditional discovery pipelines often prioritize individual natural product families despite the presence of multiple natural product biosynthetic gene clusters in each bacterial genome. Systematic characterization of talented strains is a means to expand the known natural product space. Here, we report genomics, epigenomics, and metabolomics studies of Burkholderia sp. FERM BP-3421, a soil isolate and known producer of antitumor spliceostatins. Its genome is composed of two chromosomes and two plasmids encoding at least 29 natural product families. Metabolomics studies showed that FERM BP-3421 also produces antifungal aminopyrrolnitrin and approved anticancer romidepsin. From the orphan metabolome features, we connected a lipopeptide of 1,928 Da to an 18-module nonribosomal peptide synthetase encoded as a single gene in chromosome 1. Isolation and structure elucidation led to the identification of selethramide which contains a repeating pattern of serine and leucine and is cyclized at the side chain oxygen of the one threonine residue at position 13. A (R)-3-hydroxybutyric acid moiety decorates the N-terminal serine. Initial attempts to obtain deletion mutants to probe the role of selethramide failed. After acquiring epigenome (methylome) data for FERM BP-3421, we employed a mimicry by methylation strategy that improved DNA transfer efficiency. Mutants defective in selethramide biosynthesis showed reduced surfactant activity and impaired swarming motility that could be chemically complemented with selethramide. This work unveils a lipopeptide that promotes surface motility, establishes improved DNA transfer efficiency, and sets the stage for continued natural product identification from a prolific strain.

Strategies to identify and edit improvements in synthetic genome segments episomally

Genome engineering projects often utilize bacterial artificial chromosomes (BACs) to carry multi-kilobase DNA segments at low copy number. However, all stages of whole-genome engineering have the potential to impose mutations on the synthetic genome that can reduce or eliminate the fitness of the final strain. Here, we describe improvements to a multiplex automated genome engineering (MAGE) protocol to improve recombineering frequency and multiplexability. This protocol was applied to recoding an Escherichia coli strain to replace seven codons with synonymous alternatives genome wide. Ten 44 402-47 179 bp de novo synthesized DNA segments contained in a BAC from the recoded strain were unable to complement deletion of the corresponding 33-61 wild-type genes using a single antibiotic resistance marker. Next-generation sequencing (NGS) was used to identify 1-7 non-recoding mutations in essential genes per segment, and MAGE in turn proved a useful strategy to repair these mutations on the recoded segment contained in the BAC when both the recoded and wild-type copies of the mutated genes had to exist by necessity during the repair process. Finally, two web-based tools were used to predict the impact of a subset of non-recoding missense mutations on strain fitness using protein structure and function calls.

Informatic Capabilities of Translation and Its Implications for the Origins of Life

The ability to encode and convert heritable information into molecular function is a defining feature of life as we know it. The conversion of information into molecular function is performed by the translation process, in which triplets of nucleotides in a nucleic acid polymer (mRNA) encode specific amino acids in a protein polymer that folds into a three-dimensional structure. The folded protein then performs one or more molecular activities, often as one part of a complex and coordinated physiological network. Prebiotic systems, lacking the ability to explicitly translate information between genotype and phenotype, would have depended upon either chemosynthetic pathways to generate its components-constraining its complexity and evolvability- or on the ambivalence of RNA as both carrier of information and of catalytic functions-a possibility which is still supported by a very limited set of catalytic RNAs. Thus, the emergence of translation during early evolutionary history may have allowed life to unmoor from the setting of its origin. The origin of translation machinery also represents an entirely novel and distinct threshold of behavior for which there is no abiotic counterpart-it could be the only known example of computing that emerged naturally at the chemical level. Here we describe translation machinery's decoding system as the basis of cellular translation's information-processing capabilities, and the four operation types that find parallels in computer systems engineering that this biological machinery exhibits.

Resistance exercise stress: theoretical mechanisms for growth hormone processing and release from the anterior pituitary somatotroph

Heavy resistance exercise (HRE) is the most effective method for inducing muscular hypertrophy and stimulating anabolic hormones, including growth hormone, into the blood. In this review, we explore possible mechanisms within the GH secretory pathway of the pituitary somatotroph, which are likely to modulate the flow of hormone synthesis and packaging as it is processed prior to exocytosis. Special emphasis is placed on the secretory granule and its possible role as a signaling hub. We also review data that summarize how HRE affects the quality and quantity of the secreted hormone. Finally, these pathway mechanisms are considered in the context of heterogeneity of the somatotroph population in the anterior pituitary.

Effect of mRNA/tRNA mutations on translation speed: Implications for human diseases

Recent discoveries establish tRNAs as central regulators of mRNA translation dynamics, and therefore cotranslational folding and function of the encoded protein. The tRNA pool, whose composition and abundance change in a cell- and tissue-dependent manner, is the main factor which determines mRNA translation velocity. In this review, we discuss a group of pathogenic mutations, in the coding sequences of either protein-coding genes or in tRNA genes, that alter mRNA translation dynamics. We also summarize advances in tRNA biology that have uncovered how variations in tRNA levels on account of genetic mutations affect protein folding and function, and thereby contribute to phenotypic diversity in clinical manifestations.

Performance upgrade of a microbial explosives' sensor strain by screening a high throughput saturation library of a transcriptional regulator

We present a methodology for a high-throughput screening (HTS) of transcription factor libraries, based on bacterial cells and GFP fluorescence. The method is demonstrated on the Escherichia coli LysR-type transcriptional regulator YhaJ, a key element in 2,4-dinitrotuluene (DNT) detection by bacterial explosives' sensor strains. Enhancing the performance characteristics of the YhaJ transcription factor is essential for future standoff detection of buried landmines. However, conventional directed evolution methods for modifying YhaJ are limited in scope, due to the vast sequence space and the absence of efficient screening methods to select optimal transcription factor mutants. To overcome this limitation, we have constructed a focused saturation library of ca. 6.4 × 107 yhaJ variants, and have screened over 70 % of its sequence space using fluorescence-activated cell sorting (FACS). Through this screening process, we have identified YhaJ mutants exhibiting superior fluorescence responses to DNT, which were then effectively transformed into a bioluminescence-based DNT detection system. The best modified DNT reporter strain demonstrated a 7-fold lower DNT detection threshold, a 45-fold increased signal intensity, and a 40 % shorter response time compared to the parental bioreporter. The FACS-based HTS approach presented here may hold a potential for future molecular enhancement of other sensing and catalytic bioreactions.

How soluble misfolded proteins bypass chaperones at the molecular level

Subpopulations of soluble, misfolded proteins can bypass chaperones within cells. The extent of this phenomenon and how it happens at the molecular level are unknown. Through a meta-analysis of the experimental literature we find that in all quantitative protein refolding studies there is always a subpopulation of soluble but misfolded protein that does not fold in the presence of one or more chaperones, and can take days or longer to do so. Thus, some misfolded subpopulations commonly bypass chaperones. Using multi-scale simulation models we observe that the misfolded structures that bypass various chaperones can do so because their structures are highly native like, leading to a situation where chaperones do not distinguish between the folded and near-native-misfolded states. More broadly, these results provide a mechanism by which long-time scale changes in protein structure and function can persist in cells because some misfolded states can bypass components of the proteostasis machinery.

Is Posttranslational Folding More Efficient Than Refolding from a Denatured State: A Computational Study

The folding of proteins into their native conformation is a complex process that has been extensively studied over the past half-century. The ribosome, the molecular machine responsible for protein synthesis, is known to interact with nascent proteins, adding further complexity to the protein folding landscape. Consequently, it is unclear whether the folding pathways of proteins are conserved on and off the ribosome. The main question remains: to what extent does the ribosome help proteins fold? To address this question, we used coarse-grained molecular dynamics simulations to compare the mechanisms by which the proteins dihydrofolate reductase, type III chloramphenicol acetyltransferase, and d-alanine-d-alanine ligase B fold during and after vectorial synthesis on the ribosome to folding from the full-length unfolded state in bulk solution. Our results reveal that the influence of the ribosome on protein folding mechanisms varies depending on the size and complexity of the protein. Specifically, for a small protein with a simple fold, the ribosome facilitates efficient folding by helping the nascent protein avoid misfolded conformations. However, for larger and more complex proteins, the ribosome does not promote folding and may contribute to the formation of intermediate misfolded states cotranslationally. These misfolded states persist posttranslationally and do not convert to the native state during the 6 μs runtime of our coarse-grain simulations. Overall, our study highlights the complex interplay between the ribosome and protein folding and provides insight into the mechanisms of protein folding on and off the ribosome.

The mRNA mobileome: challenges and opportunities for deciphering signals from the noise

Organismal communication entails encoding a message that is sent over space or time to a recipient cell, where that message is decoded to activate a downstream response. Defining what qualifies as a functional signal is essential for understanding intercellular communication. In this review, we delve into what is known and unknown in the field of long-distance messenger RNA (mRNA) movement and draw inspiration from the field of information theory to provide a perspective on what defines a functional signaling molecule. Although numerous studies support the long-distance movement of hundreds to thousands of mRNAs through the plant vascular system, only a small handful of these transcripts have been associated with signaling functions. Deciphering whether mobile mRNAs generally serve a role in plant communication has been challenging, due to our current lack of understanding regarding the factors that influence mRNA mobility. Further insight into unsolved questions regarding the nature of mobile mRNAs could provide an understanding of the signaling potential of these macromolecules.

Entangled Motifs in Membrane Protein Structures

Entangled motifs are found in one-third of protein domain structures, a reference set that contains mostly globular proteins. Their properties suggest a connection with co-translational folding. Here, we wish to investigate the presence and properties of entangled motifs in membrane protein structures. From existing databases, we build a non-redundant data set of membrane protein domains, annotated with the monotopic/transmembrane and peripheral/integral labels. We evaluate the presence of entangled motifs using the Gaussian entanglement indicator. We find that entangled motifs appear in one-fifth of transmembrane and one-fourth of monotopic proteins. Surprisingly, the main features of the distribution of the values of the entanglement indicator are similar to the reference case of general proteins. The distribution is conserved across different organisms. Differences with respect to the reference set emerge when considering the chirality of entangled motifs. Although the same chirality bias is found for single-winding motifs in both membrane and reference proteins, the bias is reversed, strikingly, for double-winding motifs only in the reference set. We speculate that these observations can be rationalized in terms of the constraints exerted on the nascent chain by the co-translational bio-genesis machinery, which is different for membrane and globular proteins.

In silico methods for predicting functional synonymous variants

Single nucleotide variants (SNVs) contribute to human genomic diversity. Synonymous SNVs are previously considered to be "silent," but mounting evidence has revealed that these variants can cause RNA and protein changes and are implicated in over 85 human diseases and cancers. Recent improvements in computational platforms have led to the development of numerous machine-learning tools, which can be used to advance synonymous SNV research. In this review, we discuss tools that should be used to investigate synonymous variants. We provide supportive examples from seminal studies that demonstrate how these tools have driven new discoveries of functional synonymous SNVs.

Bacterial natural product discovery by heterologous expression

Natural products have found important applications in the pharmaceutical and agricultural sectors. In bacteria, the genes that encode the biosynthesis of natural products are often colocalized in the genome, forming biosynthetic gene clusters. It has been predicted that only 3% of natural products encoded in bacterial genomes have been discovered thus far, in part because gene clusters may be poorly expressed under laboratory conditions. Heterologous expression can help convert bioinformatics predictions into products. However, challenges remain, such as gene cluster prioritization, cloning of the complete gene cluster, high level expression, product identification, and isolation of products in practical yields. Here we reviewed the literature from the past 5 years (January 2018 to June 2023) to identify studies that discovered natural products by heterologous expression. From the 50 studies identified, we present analyses of the rationale for gene cluster prioritization, cloning methods, biosynthetic class, source taxa, and host choice. Combined, the 50 studies led to the discovery of 63 new families of natural products, supporting heterologous expression as a promising way to access novel chemistry. However, the success rate of natural product detection varied from 11% to 32% based on four large-scale studies that were part of the reviewed literature. The low success rate makes it apparent that much remains to be improved. The potential reasons for failure and points to be considered to improve the chances of success are discussed.

ONE-SENTENCE SUMMARY

At least 63 new families of bacterial natural products were discovered using heterologous expression in the last 5 years, supporting heterologous expression as a promising way to access novel chemistry; however, the success rate is low (11-32%) making it apparent that much remains to be improved-we discuss the potential reasons for failure and points to be considered to improve the chances of success. BioRender was used to generate the graphical abstract figure.

Do Noncoding and Coding Sites in Angiosperm Chloroplast DNA Have Different Mutation Processes?

Fourfold degenerate sites within coding regions and intergenic sites have both been used as estimates of neutral evolution. In chloroplast DNA, the pattern of substitution at intergenic sites is strongly dependent on the composition of the surrounding hexanucleotide composed of the three base pairs on each side, which suggests that the mutation process is highly context-dependent in this genome. This study examines the context-dependency of substitutions at fourfold degenerate sites in protein-coding regions and compares the pattern to what has been observed at intergenic sites. Overall, there is strong similarity between the two types of sites, but there are some intriguing differences. One of these is that substitutions of G and C are significantly higher at fourfold degenerate sites across a range of contexts. In fact, A → T and T → A substitutions are the only substitution types that occur at a lower rate at fourfold degenerate sites. The data are not consistent with selective constraints being responsible for the difference in substitution patterns between intergenic and fourfold degenerate sites. Rather, it is suggested that the difference may be a result of different epigenetic modifications that result in slightly different mutation patterns in coding and intergenic DNA.

Engineering Ag43 Signal Peptides with Bacterial Display and Selection

Protein display, secretion, and export in prokaryotes are essential for utilizing microbial systems as engineered living materials, medicines, biocatalysts, and protein factories. To select for improved signal peptides for Escherichia coli protein display, we utilized error-prone polymerase chain reaction (epPCR) coupled with single-cell sorting and microplate titer to generate, select, and detect improved Ag43 signal peptides. Through just three rounds of mutagenesis and selection using green fluorescence from the 56 kDa sfGFP-beta-lactamase, we isolated clones that modestly increased surface display from 1.4- to 3-fold as detected by the microplate plate-reader and native SDS-PAGE assays. To establish that the functional protein was displayed extracellularly, we trypsinized the bacterial cells to release the surface displayed proteins for analysis. This workflow demonstrated a fast and high-throughput method leveraging epPCR and single-cell sorting to augment bacterial surface display rapidly that could be applied to other bacterial proteins.