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At least 595 records · Page 33

Models of the Protocellular Structures, Functions and Evolution

In the absence of extinct or extant record of protocells, the most direct way to test our understanding of the origin of cellular life is to construct laboratory models that capture important features of protocellular systems. Such efforts are currently underway in a collaborative project between NASA-Ames, Harvard medical School and University of California. They are accompanied by computational studies aimed at explaining self-organization of simple molecules into ordered structures. The centerpiece of this project is a method for the in vitro evolution of protein enzymes toward arbitrary catalytic targets. A similar approach has already been developed for nucleic acids: First, a very large population of candidate molecules is generated using a random synthetic approach. Next, the small numbers of molecules that can accomplish the desired task are selected. These molecules are next vastly multiplied using the polymerase chain reaction. A mutagenic approach, in which the sequences of selected molecules are randomly altered, can yield further improvements in performance or alterations of specificities. Unfortunately, the catalytic potential of nucleic acids is rather limited. Proteins are more catalytically capable but cannot be directly amplified. In the new technique, this problem is circumvented by covalently linking each protein of the initial, diverse, pool to the RNA sequence that codes for it. Then, selection is performed on the proteins, but the nucleic acids are replicated. To date, we have obtained "a proof of concept" by evolving simple, novel proteins capable of selectively binding adenosine tri-phosphate (ATP). Our next goal is to create an enzyme that can phosphorylate amino acids and another to catalyze the formation of peptide bonds in the absence of nucleic acid templates. This latter reaction does not take place in contemporary cells. once developed, these enzymes will be encapsulated in liposomes so that they will function in a simulated cellular environment. To provide a continuous energy supply, usually needed to activate the substrates, an energy transduction complex which generates ATP from adenosine diphosphate, inorganic phosphate and light will be used. This system, consisting of two modern proteins, ATP synthase and bacteriorhodopsin, has already been built and shown to work efficiently. By coupling chemical synthesis to such a system, it will be possible to drive chemical reactions by light if only the substrates for these reactions are supplied.

Pohorille, Andrew↗

Structural dissection of sequence recognition and catalytic mechanism of human LINE-1 endonuclease

Abstract Long interspersed nuclear element-1 (L1) is an autonomous non-LTR retrotransposon comprising ∼20% of the human genome. L1 self-propagation causes genomic instability and is strongly associated with aging, cancer and other diseases. The endonuclease domain of L1’s ORFp2 protein (L1-EN) initiates de novo L1 integration by nicking the consensus sequence 5′-TTTTT/AA-3′. In contrast, related nucleases including structurally conserved apurinic/apyrimidinic endonuclease 1 (APE1) are non-sequence specific. To investigate mechanisms underlying sequence recognition and catalysis by L1-EN, we solved crystal structures of L1-EN complexed with DNA substrates. This showed that conformational properties of the preferred sequence drive L1-EN’s sequence-specificity and catalysis. Unlike APE1, L1-EN does not bend the DNA helix, but rather causes ‘compression’ near the cleavage site. This provides multiple advantages for L1-EN’s role in retrotransposition including facilitating use of the nicked poly-T DNA strand as a primer for reverse transcription. We also observed two alternative conformations of the scissile bond phosphate, which allowed us to model distinct conformations for a nucleophilic attack and a transition state that are likely applicable to the entire family of nucleases. This work adds to our mechanistic understanding of L1-EN and related nucleases and should facilitate development of L1-EN inhibitors as potential anticancer and antiaging therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗

Altered Expression of Two Small Secreted Proteins (ssp4 and ssp6) Affects the Degradation of a Natural Lignocellulosic Substrate by Pleurotus ostreatus

Pleurotus ostreatus is a white-rot fungus that can degrade lignin in a preferential manner using a variety of extracellular enzymes, including manganese and versatile peroxidases (encoded by the vp1-3 and mnp1-6 genes, respectively). This fungus also secretes a family of structurally related small secreted proteins (SSPs) encoded by the ssp1-6 genes. Using RNA sequencing (RNA-seq), we determined that ssp4 and ssp6 are the predominant members of this gene family that were expressed by P. ostreatus during the first three weeks of growth on wheat straw. Downregulation of ssp4 in a strain harboring an ssp RNAi construct (KDssp1) was then confirmed, which, along with an increase in ssp6 transcript levels, coincided with reduced lignin degradation and the downregulation of vp2 and mnp1. In contrast, we observed an increase in the expression of genes related to pectin and side-chain hemicellulose degradation, which was accompanied by an increase in extracellular pectin-degrading capacity. Genome-wide comparisons between the KDssp1 and the wild-type strains demonstrated that ssp silencing conferred accumulated changes in gene expression at the advanced cultivation stages in an adaptive rather than an inductive mode of transcriptional response. Based on co-expression networking, crucial gene modules were identified and linked to the ssp knockdown genotype at different cultivation times. Based on these data, as well as previous studies, we propose that P. ostreatus SSPs have potential roles in modulating the lignocellulolytic and pectinolytic systems, as well as a variety of fundamental biological processes related to fungal growth and development.

59 BASIC BIOLOGICAL SCIENCES↗

DIPS-Plus: The enhanced database of interacting protein structures for interface prediction

Abstract In this work, we expand on a dataset recently introduced for protein interface prediction (PIP), the Database of Interacting Protein Structures (DIPS), to present DIPS-Plus, an enhanced, feature-rich dataset of 42,112 complexes for machine learning of protein interfaces. While the original DIPS dataset contains only the Cartesian coordinates for atoms contained in the protein complex along with their types, DIPS-Plus contains multiple residue-level features including surface proximities, half-sphere amino acid compositions, and new profile hidden Markov model (HMM)-based sequence features for each amino acid, providing researchers a curated feature bank for training protein interface prediction methods. We demonstrate through rigorous benchmarks that training an existing state-of-the-art (SOTA) model for PIP on DIPS-Plus yields new SOTA results, surpassing the performance of some of the latest models trained on residue-level and atom-level encodings of protein complexes to date.

59 BASIC BIOLOGICAL SCIENCES↗

PRIME: An evaluation framework for protein representation inference and generalization in viral mutation space

Background Protein language models (PLMs) have revolutionized protein fitness prediction, yet their application to rapidly evolving viral pathogens is often confounded by extreme sequence homology. This homology leads to “data leakage” in standard random validation splits, yielding inflated performance metrics that fail to translate into real-world biosurveillance utility. Results We present Protein Representation Inference for Mutation Evaluation (PRIME), a framework that integrates domain-specific fine-tuning with a rigorous position-stratified validation protocol to evaluate viral threats. Using a dataset of 347,432 SARS-CoV-2 receptor binding domain (RBD) sequences, we demonstrate that while random training data split yields deceptive R 2 values (> 0.90), they fail to generalize to novel mutational sites. By benchmarking models up to 650 M parameters, we show that domain-specific fine-tuning of the ESM-C 600 M model with correctly stratified data provides an initial demonstration of predictive signal for binding affinity and expression at unseen mutational sites of binding affinity and expression on unseen sites (R 2 ~0.23), a significant advancement over base foundation models which exhibit no predictive power (R 2 <0). PRIME’s embedding-based clustering identified 3.03% of bat coronavirus sequences as candidates for further experimental prioritization based on their functional similarity to human-infective strains in embedding space, offering a perspective complementary to traditional phylogenetic methods. Conclusion PRIME establishes a new benchmark for the application of PLMs in pathogen surveillance. Our findings demonstrate that state-of-the-art models and fine-tuning, when paired with stratified validation, provide biologically meaningful insights into pathogen evolution and zoonotic risk.

59 BASIC BIOLOGICAL SCIENCES↗

Zuotin, a putative Z-DNA binding protein in Saccharomyces cerevisiae

A putative Z-DNA binding protein, named zuotin, was purified from a yeast nuclear extract by means of a Z-DNA binding assay using [32P]poly(dG-m5dC) and [32P]oligo(dG-Br5dC)22 in the presence of B-DNA competitor. Poly(dG-Br5dC) in the Z-form competed well for the binding of a zuotin containing fraction, but salmon sperm DNA, poly(dG-dC) and poly(dA-dT) were not effective. Negatively supercoiled plasmid pUC19 did not compete, whereas an otherwise identical plasmid pUC19(CG), which contained a (dG-dC)7 segment in the Z-form was an excellent competitor. A Southwestern blot using [32P]poly(dG-m5dC) as a probe in the presence of MgCl2 identified a protein having a molecular weight of 51 kDa. The 51 kDa zuotin was partially sequenced at the N-terminal and the gene, ZUO1, was cloned, sequenced and expressed in Escherichia coli; the expressed zuotin showed similar Z-DNA binding activity, but with lower affinity than zuotin that had been partially purified from yeast. Zuotin was deduced to have a number of potential phosphorylation sites including two CDC28 (homologous to the human and Schizosaccharomyces pombe cdc2) phosphorylation sites. The hexapeptide motif KYHPDK was found in zuotin as well as in several yeast proteins, DnaJ of E.coli, csp29 and csp32 proteins of Drosophila and the small t and large T antigens of the polyoma virus. A 60 amino acid segment of zuotin has similarity to several histone H1 sequences. Disruption of ZUO1 in yeast resulted in a slow growth phenotype.

NASA Discipline Exobiology↗

CCAAT/enhancer-binding protein delta is a critical regulator of insulin-like growth factor-I gene transcription in osteoblasts

Insulin-like growth factor-I (IGF-I) plays a major role in promoting skeletal growth by stimulating bone cell replication and differentiation. Prostaglandin E2 and other agents that induce cAMP production enhance IGF-I gene transcription in cultured rat osteoblasts through a DNA element termed HS3D, located in the proximal part of the major rat IGF-I promoter. We previously determined that CCAAT/enhancer-binding protein delta (C/EBPdelta) is the key cAMP-stimulated regulator of IGF-I transcription in these cells and showed that it transactivates the rat IGF-I promoter through the HS3D site. We now have defined the physical-chemical properties and functional consequences of the interactions between C/EBPdelta and HS3D. C/EBPdelta, expressed in COS-7 cells or purified as a recombinant protein from Escherichia coli, bound to HS3D with an affinity at least equivalent to that of the albumin D-site, a known high affinity C/EBP binding sequence, and both DNA elements competed equally for C/EBPdelta. C/EBPdelta bound to HS3D as a dimer, with protein-DNA contact points located on guanine residues on both DNA strands within and just adjacent to the core C/EBP half-site, GCAAT, as determined by methylation interference footprinting. C/EBPdelta also formed protein-protein dimers in the absence of interactions with its DNA binding site, as indicated by results of glutaraldehyde cross-linking studies. As established by competition gel-mobility shift experiments, the conserved HS3D sequence from rat, human, and chicken also bound C/EBPdelta with similar affinity. We also found that prostaglandin E2-induced expression of reporter genes containing human IGF-I promoter 1 or four tandem copies of the human HS3D element fused to a minimal promoter and show that these effects were enhanced by a co-transfected C/EBPdelta expression plasmid. Taken together, our results provide evidence that C/EBPdelta is a critical activator of IGF-I gene transcription in osteoblasts and potentially in other cell types and species.

NASA Discipline Musculoskeletal↗

Assessing the potential of deep learning for protein–ligand docking

The effects of ligand binding on protein structures and their in vivo functions carry numerous implications for modern biomedical research and biotechnology development efforts such as drug discovery. Although several deep learning (DL) methods and benchmarks designed for protein–ligand docking have recently been introduced, so far no previous works have systematically studied the behaviour of the latest docking and structure prediction methods within the broadly applicable context of: (1) using predicted (apo) protein structures for docking (for example, for applicability to new proteins); (2) binding multiple (cofactor) ligands concurrently to a given target protein (for example, for enzyme design); and (3) having no previous knowledge of binding pockets (for example, for generalization to unknown pockets). To enable a deeper understanding of the real-world utility of docking methods, we introduce PoseBench, a comprehensive benchmark for broadly applicable protein–ligand docking. PoseBench enables researchers to rigorously and systematically evaluate DL methods for apo-to-holo protein–ligand docking and protein–ligand structure prediction using both primary ligand and multiligand benchmark datasets, the latter of which we introduce to the DL community. Empirically, using PoseBench, we find that: (1) DL cofolding methods generally outperform comparable conventional and DL docking baseline algorithms, but popular methods such as AlphaFold 3 are still challenged by prediction targets with new protein–ligand binding poses; (2) certain DL cofolding methods are highly sensitive to their input multiple sequence alignments, whereas others are not; and (3) DL methods struggle to strike a balance between structural accuracy and chemical specificity when predicting new or multiligand protein targets.

Morehead, Alex [Lawrence Berkeley National Laborat↗

Functional characterization of prokaryotic dark matter: the road so far and what lies ahead

Eight-hundred thousand to one trillion prokaryotic species may inhabit our planet. Yet, fewer than two-hundred thousand prokaryotic species have been described. This uncharted fraction of microbial diversity, and its undisclosed coding potential, is known as the “microbial dark matter” (MDM). Next-generation sequencing has allowed to collect a massive amount of genome sequence data, leading to unprecedented advances in the field of genomics. Still, harnessing new functional information from the genomes of uncultured prokaryotes is often limited by standard classification methods. These methods often rely on sequence similarity searches against reference genomes from cultured species. This hinders the discovery of unique genetic elements that are missing from the cultivated realm. It also contributes to the accumulation of prokaryotic gene products of unknown function among public sequence data repositories, highlighting the need for new approaches for sequencing data analysis and classification. Increasing evidence indicates that these proteins of unknown function might be a treasure trove of biotechnological potential. Here, we outline the challenges, opportunities, and the potential hidden within the functional dark matter (FDM) of prokaryotes. We also discuss the pitfalls surrounding molecular and computational approaches currently used to probe these uncharted waters, and discuss future opportunities for research and applications.

59 BASIC BIOLOGICAL SCIENCES↗

A Dual-Gated Structures for Lossless Ion Manipulations-Ion Mobility Orbitrap Mass Spectrometry Platform for Combined Ultra-High-Resolution Molecular Analysis

High-resolution ion mobility spectrometry-mass spectrometry (HR-IMS-MS) instruments have enormously advanced the ability to characterize complex biological mixtures. Unfortunately, HR-IMS and HR-MS measurements are typically performed independently due to mismatches in analysis time scales. Here we overcome this limitation by using a dual-gated ion injection approach to couple an 11-meter path length structures for lossless ion manipulations (SLIM) module to a Q-Exactive Plus Orbitrap MS. The dual-gate setup was implemented by placing one ion gate before the SLIM module and a second ion gate after. The dual-gated ion injection approach allowed the new SLIM-Orbitrap platform to simultaneously perform an 11-meter SLIM separation, Orbitrap mass analysis using the highest selectable mass resolution setting (up to 140k), and high-energy collision induced dissociation (HCD) in ~25 minutes over an $m/z$ range of ~1500 amu. The SLIM-Orbitrap was initially characterized using a mixture of standard phosphazene cations and demonstrated an average SLIM CCS resolving power (Rp CCS ) of ~218 and SLIM peak capacity of ~156 while simultaneously obtaining high mass resolutions. SLIM-Orbitrap analysis with fragmentation was then performed on mixtures of standard peptides and two reverse peptides (SDGRG 1+ , GRGDS 1+ , Rp CCS = 305) to demonstrate the utility of combined HR-IMS-MS/MS measurements for peptide identification. Our new HR-IMS-MS/MS capability was further demonstrated by analyzing a complex lipid mixture and showcasing SLIM separations on isobaric lipids. In conclusion, this new SLIM-Orbitrap platform demonstrates a critical new capability for proteomics and lipidomics applications, and the high-resolution multimodal data obtainable with this system establishes the foundation for reference-free identification of unknown ion structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

MAL33 drives natural variation in maltose metabolism in Saccharomyces eubayanus

Maltose is one of the most abundant sugars in brewer’s wort, and its efficient utilization is critical for successful fermentation. However, maltose consumption varies naturally among Saccharomyces eubayanus strains isolated from different host trees, such as Quercus and Nothofagus. To identify the genetic determinants underlying these phenotypic differences, we performed bulk segregant analysis (BSA) and quantitative trait loci (QTL) mapping using an F 2 offspring derived from QC18 (Quercus-associated) and CL467.1 (Nothofagus-associated) strains. QTL mapping identified two significant genomic regions on subtelomeric loci of chromosomes V-R and XVI-L, each containing complete MAL loci composed of MAL32 (encoding maltase), MAL31 (transporter), and MAL33 (transcriptional activator) genes. Comparative polymorphism analyses identified mutations in MAL32 and MAL33 of QC18, including frameshift mutations resulting in premature stop codons. Functional validation demonstrated that the heterologous expression of MAL33 ChrV from CL467.1 fully restored maltose utilization in QC18, indicating the functional presence of MAL33 cis-regulatory sequences and MAL32 and MAL31 genes in QC18. While structural protein predictions identified truncation and impaired functionality in the maltose-responsive activation domain of Mal33p from QC18, overexpression of QC18’s own MAL33 ChrV allele also improved maltose metabolism, suggesting dosage-dependent transcriptional limitations rather than complete functional loss. These results indicate that allelic variations in the maltose-responsive activation domain of Mal33p result in differences in maltose consumption between strains. Here, we hypothesized that reduced maltose metabolism in QC18 is an adaptive response to the distinct sugar composition in Quercus robur bark, contrasting with the starch-rich environment of Nothofagus pumilio. These findings highlight subtelomeric MAL gene diversity as a reservoir of genetic variation, representing a key evolutionary mechanism that influences maltose adaptation among natural Saccharomyces isolates.

evolutionary plasticity↗

Transcriptional Control of hgcAB by an ArsR-Like Regulator in Pseudodesulfovibrio mercurii ND132

The hgcAB gene pair encodes mercury (Hg) methylation capability in a diverse group of microorganisms, but its evolution and transcriptional regulation remain unknown. Working from the possibility that the evolutionary function of HgcAB may not be Hg methylation, we test a possible link to arsenic resistance. Using model Hg methylator Pseudodesulfovibrio mercurii ND132, we evaluated transcriptional control of hgcAB by a putative ArsR encoded upstream and cotranscribed with hgcAB. This regulator shares homology with ArsR repressors of arsenic resistance and S-adenosylhomocysteine (SAH)- responsive regulators of methionine biosynthesis but is distinct from other ArsR/SahR proteins in P. mercurii. Using quantitative PCR (qPCR) and RNA sequencing (RNA-seq) transcriptome analyses, we confirmed this ArsR regulates hgcAB transcription and is responsive to arsenic and SAH. Additionally, RNA-seq indicated a possible link between hgcAB activity and arsenic transformations, with significant upregulation of other ArsRregulated arsenic resistance operons alongside hgcAB. Interestingly, wild-type ND132 was less sensitive to As(V) (but not As(III)) than an hgcAB knockout strain, supporting the idea that hgcAB may be linked to arsenic resistance. Arsenic significantly impacted rates of Hg methylation by ND132; however, responses varied with culture conditions. Differences in growth and metabolic activity did not account for arsenic impacts on methylation. While arsenic significantly increased hgcAB expression, hgcAB gene and transcript abundance was not a good predictor of Hg methylation rates. Taken together, these results support the idea that Hg and As cycling are linked in P. mercurii ND132. Our results may hold clues to the evolution of hgcAB and the controls on Hg methylation in nature. This work reveals a link between microbial mercury methylation and arsenic resistance and may hold clues to the evolution of mercury methylation genes (hgcAB). Microbes with hgcAB produce methylmercury, a strong neurotoxin that readily accumulates in the food web. This study addresses a critical gap in our understanding about the environmental factors that control hgcAB expression. We show that hgcAB expression is controlled by an ArsR-like regulator responsive to both arsenic and S-adenosylhomocysteine in our model organism, Pseudodesulfovibrio mercurii ND132. Exposure to arsenic also significantly impacted Pseudodesulfovibrio mercurii ND132 mercury methylation rates. However, expression of hgcAB was not always a good predictor of Hg methylation rates, highlighting the roles of Hg bioavailability and other biochemical mechanisms in methylmercury production. This study improves our understanding of the controls on hgcAB expression, which is needed to better predict environmental methylmercury production

RNA-seq↗

A chromosome-level genome assembly of the Chinese cork oak (Quercus variabilis)

Quercus variabilis (Fagaceae) is an ecologically and economically important deciduous broadleaved tree species native to and widespread in East Asia. It is a valuable woody species and an indicator of local forest health, and occupies a dominant position in forest ecosystems in East Asia. However, genomic resources from Q. variabilis are still lacking. Here, we present a high-quality Q. variabilis genome generated by PacBio HiFi and Hi-C sequencing. The assembled genome size is 787 Mb, with a contig N50 of 26.04 Mb and scaffold N50 of 64.86 Mb, comprising 12 pseudo-chromosomes. The repetitive sequences constitute 67.6% of the genome, of which the majority are long terminal repeats, accounting for 46.62% of the genome. We used ab initio , RNA sequence-based and homology-based predictions to identify protein-coding genes. A total of 32,466 protein-coding genes were identified, of which 95.11% could be functionally annotated. Evolutionary analysis showed that Q. variabilis was more closely related to Q. suber than to Q. lobata or Q. robur. We found no evidence for species-specific whole genome duplications in Quercus after the species had diverged. This study provides the first genome assembly and the first gene annotation data for Q. variabilis. These resources will inform the design of further breeding strategies, and will be valuable in the study of genome editing and comparative genomics in oak species.

Han, Biao↗

Recombinant Collagenlike Proteins

A group of collagenlike recombinant proteins containing high densities of biologically active sites has been invented. The method used to express these proteins is similar to a method of expressing recombinant procollagens and collagens described in U. S. Patent 5,593,859, "Synthesis of human procollagens and collagens in recombinant DNA systems." Customized collagenous proteins are needed for biomedical applications. In particular, fibrillar collagens are attractive for production of matrices needed for tissue engineering and drug delivery. Prior to this invention, there was no way of producing customized collagenous proteins for these and other applications. Heretofore, collagenous proteins have been produced by use of such biological systems as yeasts, bacteria, and transgenic animals and plants. These products are normal collagens that can also be extracted from such sources as tendons, bones, and hides. These products cannot be made to consist only of biologically active, specific amino acid sequences that may be needed for specific applications. Prior to this invention, it had been established that fibrillar collagens consist of domains that are responsible for such processes as interaction with cells, binding of growth factors, and interaction with a number of structural proteins present in the extracellular matrix. A normal collagen consists of a sequence of domains that can be represented by a corresponding sequence of labels, e.g., D1D2D3D4. A collagenlike protein of the present invention contains regions of collagen II that contain multiples of a single domain (e.g., D1D1D1D1 or D4D4D4D4) chosen for its specific biological activity. By virtue of the multiplicity of the chosen domain, the density of sites having that specific biological activity is greater than it is in a normal collagen. A collagenlike protein according to this invention can thus be made to have properties that are necessary for tissue engineering.

Fertala, Andzej↗

DNA Recombinase Proteins, their Function and Structure in the Active Form, a Computational Study

Homologous recombination is a crucial sequence of reactions in all cells for the repair of double strand DNA (dsDNA) breaks. While it was traditionally considered as a means for generating genetic diversity, it is now known to be essential for restart of collapsed replication forks that have met a lesion on the DNA template (Cox et al., 2000). The central stage of this process requires the presence of the DNA recombinase protein, RecA in bacteria, RadA in archaea, or Rad51 in eukaryotes, which leads to an ATP-mediated DNA strand-exchange process. Despite many years of intense study, some aspects of the biochemical mechanism, and structure of the active form of recombinase proteins are not well understood. Our theoretical study is an attempt to shed light on the main structural and mechanistic issues encountered on the RecA of the e-coli, the RecA of the extremely radio resistant Deinococcus Radiodurans (promoting an inverse DNA strand-exchange repair), and the homolog human Rad51. The conformational changes are analyzed for the naked enzymes, and when they are linked to ATP and ADP. The average structures are determined over 2ns time scale of Langevian dynamics using a collision frequency of 1.0 ps(sup -1). The systems are inserted in an octahedron periodic box with a 10 Angstrom buffer of water molecules explicitly described by the TIP3P model. The corresponding binding free energies are calculated in an implicit solvent using the Poisson-Boltzmann solvent accessible surface area, MM-PBSA model. The role of the ATP is not only in stabilizing the interaction RecA-DNA, but its hydrolysis is required to allow the DNA strand-exchange to proceed. Furthermore, we extended our study, using the hybrid QM/MM method, on the mechanism of this chemical process. All the calculations were performed using the commercial code Amber 9.

Carra, Claudio↗

Streamlining heterologous expression of top carbonic anhydrases in Escherichia coli : bioinformatic and experimental approaches

Carbonic anhydrase (CA) enzymes facilitate the reversible hydration of CO 2 to bicarbonate ions and protons. Identifying efficient and robust CAs and expressing them in model host cells, such as Escherichia coli, enables more efficient engineering of these enzymes for industrial CO 2 capture. However, expression of CAs in E. coli is challenging due to the possible formation of insoluble protein aggregates, or inclusion bodies. This makes the production of soluble and active CA protein a prerequisite for downstream applications. In this study, we streamlined the process of CA expression by selecting seven top CA candidates and used two bioinformatic tools to predict their solubility for expression in E. coli. The prediction results place these enzymes in two categories: low and high solubility. Our expression of high solubility score CAs (namely CA5-SspCA, CA6-SazCAtrunc, CA7-PabCA and CA8-PhoCA) led to significantly higher protein yields (5 to 75 mg purified protein per liter) in flask cultures, indicating a strong correlation between the solubility prediction score and protein expression yields. Furthermore, phylogenetic tree analysis demonstrated CA class-specific clustering patterns for protein solubility and production yields. Unexpectedly, we also found that the unique N-terminal, 11-amino acid segment found after the signal sequence (not present in its homologs), was essential for CA6-SazCA activity. Overall, this work demonstrated that protein solubility prediction, phylogenetic tree analysis, and experimental validation are potent tools for identifying top CA candidates and then producing soluble, active forms of these enzymes in E. coli. The comprehensive approaches we report here should be extendable to the expression of other heterogeneous proteins in E. coli.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗