Biased Amino Acid Composition Research Articles

Epidermal Differentiation Genes of the Common Wall Lizard Encode Proteins with Extremely Biased Amino Acid Contents.

The epidermal differentiation complex (EDC) is a cluster of genes that code for protein components of cornified cells on the skin surface of amniotes. Squamates are the most species-rich clade of reptiles with skin adaptations to many different environments. As the genetic regulation of the skin epidermis and its evolution has been characterized for only a few species so far, we aimed to determine the organization of the EDC in a model species of squamates, the common wall lizard (Podarcis muralis). By comparative genomics, we identified EDC genes of the wall lizard and compared them with homologs in other amniotes. We found that the EDC of the wall lizard has undergone a major rearrangement leading to a unique order of three ancestral EDC segments. Several subfamilies of EDC genes, such as those encoding epidermal differentiation proteins containing PCCC motifs (EDPCCC) and loricrins, have expanded by gene duplications. Most of the EDPCCC proteins have cysteine contents higher than 50%, whereas glycine constitutes more than 50% of the amino acid residues of loricrin 1. The extremely biased amino acid compositions indicate unique structural properties of these EDC proteins. This study demonstrates that cornification proteins of the common wall lizard differ from homologous proteins of other reptiles, illustrating the evolutionary dynamics of diversifying evolution in squamates.

Exploration of O-GlcNAc transferase glycosylation sites reveals a target sequence compositional bias

O-GlcNAc transferase (OGT) is an essential glycosylating enzyme that catalyzes the addition of N-acetylglucosamine to serine or threonine residues of nuclear and cytoplasmic proteins. The enzyme glycosylates a broad range of peptide sequences and the prediction of glycosylation sites has proven challenging. The lack of an experimentally verified set of polypeptide sequences that are not glycosylated by OGT has made prediction of legitimate glycosylation sites more difficult. Here, we tested a number of intrinsically disordered protein regions as substrates of OGT to establish a set of sequences that are not glycosylated by OGT. The negative data set suggests an amino acid compositional bias for OGT targets. This compositional bias was validated by modifying the amino acid composition of the protein fused in sarcoma (FUS) to enhance glycosylation. NMR experiments demonstrate that the tetratricopeptide repeat region of OGT can bind FUS and that glycosylation-promoting mutations enhance binding. These results provide evidence that the tetratricopeptide repeat region recognizes disordered segments of substrates with particular compositions to promote glycosylation, providing insight into the broad specificity of OGT.

Droplets, tails and loops: The role of intrinsic disorder in R-loop biology.

R-loops are non-canonical triple-stranded RNA:DNA hybrid structures that perform critical biological functions. However, dysregulated R-loops can also cause cancer and neurological disorders. Previous high-throughput studies have identified over a thousand proteins involved in recognizing, preventing and resolving R-loops, with many of them containing both folded nucleic acid-binding/processing domains and Intrinsically Disordered Regions (IDRs). Nonetheless, the precise molecular mechanisms by which these proteins regulate R-loop function remain elusive. While investigating the Fragile-X Syndrome Protein (FMRP), we unexpectedly discovered that the C-Terminal IDR of FMRP, which promotes Liquid-Liquid Phase Separation (LLPS) of FMRP, is the predominant R-loop binding site, with the N-terminal domains recognizing the trailing ssRNA overhang. In addition, we have recently shown that FMRP can suppress persistent R-loops that form during transcription, a process that is also enhanced by LLPS via the assembly of membraneless transcription factories. These exciting findings prompted us to undertake a combined in-cellulo/in-silico/in-vitro approach to investigate the mechanisms of R-loop recognition, signaling, and resolution. We observed that, like FMRP, the majority of proteins in the R-loop interactome contains long IDRs that are highly enriched in low complexity sequences with biased amino acid composition. Furthermore, our analysis shows that several proteins in the R-loop interactome are either predicted to or have been experimentally demonstrated to undergo LLPS or are known to be associated with phase separated membraneless organelles. Finally, we have recently demonstrated in vitro that the IDRs of different proteins selected from the R-loop interactome can also directly recognize R-loops and undergo LLPS. Our overall results present a thought-provoking hypothesis that IDRs in the R-loop interactome provide a functional link between R-loop recognition via direct binding and downstream signaling through the assembly of LLPS-mediated membraneless R-loop foci.

Participation of Histones in DNA Damage and Repair within Nucleosome Core Particles: Mechanism and Applications.

DNA is damaged by various endogenous and exogenous sources, leading to a diverse group of reactive intermediates that yield a complex mixture of products. The initially formed products are often metastable and can react to yield lesions that are more biologically deleterious. Mechanistic studies are frequently carried out on free DNA as the substrate. The observations do not necessarily reflect the reaction environment inside human cells where genomic DNA is condensed as chromatin in the nucleus. Chromatin is made up of monomeric structural units called nucleosomes, which are comprised of DNA wrapped around an octameric core of histone proteins (two copies each of histones H2A, H2B, H3, and H4).This account presents a summary of our work in the past decade on the mechanistic studies of DNA damage and repair in reconstituted nucleosome core particles (NCPs). A series of metastable lesions and reactive intermediates, such as abasic sites (AP), N7-methyl-2'-deoxyguanosine (MdG), and 2'-deoxyadenosin-N6-yl radical (dA•), have been independently generated in a site-specific manner in bottom-up-synthesized NCPs. Detailed mechanistic studies on these NCPs revealed that histones actively participate in DNA damage and repair processes in diverse ways. For instance, nucleophilic residues in the flexible histone N-terminal tails, such as Lys and N-terminal α-amine, react with electrophilic DNA damage and reactive intermediates. In some cases, transient intermediates are produced, leading to the promotion or suppression of damage and repair processes. In other examples, reactions with histones yield reversible or stable DNA-protein cross-links (DPCs). Histones also utilize acidic and basic residues, such as histidine and aspartic acid, to catalyze DNA strand cleavage through general acid/base catalysis. Alternatively, a Tyr in histone plays a vital role in nucleosomal DNA damage and repair via radical transfer. Finally, the reactivity discovered during the mechanistic studies has facilitated the development of new reagents and methods with applications in biotechnology.This research has enriched our knowledge of the roles of histone proteins in DNA damage and repair and their contributions to epigenetics and may have significant biological implications. The residues in histone N-terminal tails that react with DNA lesions also play pivotal roles in regulating the structure and function of chromatin, indicating that there may be cross-talk between DNA damage and repair in eukaryotic cells and epigenetic regulation. Also, in view of the biased amino acid composition of histones, these results provide hints about how the proteins have evolved to minimize their deleterious effects but maximize beneficial ones for maintaining genome integrity. Finally, previously unreported DPCs and histone post-translational modifications have been discovered through this research. The effects of these newly identified lesions on the structure and function of chromatin and their fates inside cells remain to be elucidated.

DisEnrich: database of enriched regions in human dark proteome.

Intrinsically disordered proteins (IDPs) are involved in numerous processes crucial for living organisms. Bias in amino acid composition of these proteins determines their unique biophysical and functional features. Distinct intrinsically disordered regions (IDRs) with compositional bias play different important roles in various biological processes. IDRs enriched in particular amino acids in human proteome have not been described consistently. We developed DisEnrich-the database of human proteome IDRs that are significantly enriched in particular amino acids. Each human protein is described using Gene Ontology (GO) function terms, disorder prediction for the full-length sequence using three methods, enriched IDR composition and ranks of human proteins with similar enriched IDRs. Distribution analysis of enriched IDRs among broad functional categories revealed significant overrepresentation of R- and Y-enriched IDRs in metabolic and enzymatic activities and F-enriched IDRs in transport. About 75% of functional categories contain IDPs with IDRs significantly enriched in hydrophobic residues that are important for protein-protein interactions. The database is available at http://prodata.swmed.edu/DisEnrichDB/. Supplementary data are available at Bioinformatics Advances online.

Sequence and Structure-Based Analyses of Human Ankyrin Repeats

Ankyrin is one of the most abundant protein repeat families found across all forms of life. It is found in a variety of multi-domain and single domain proteins in humans with diverse number of repeating units. They are observed to occur in several functionally diverse proteins, such as transcriptional initiators, cell cycle regulators, cytoskeletal organizers, ion transporters, signal transducers, developmental regulators, and toxins, and, consequently, defects in ankyrin repeat proteins have been associated with a number of human diseases. In this study, we have classified the human ankyrin proteins into clusters based on the sequence similarity in their ankyrin repeat domains. We analyzed the amino acid compositional bias and consensus ankyrin motif sequence of the clusters to understand the diversity of the human ankyrin proteins. We carried out network-based structural analysis of human ankyrin proteins across different clusters and showed the association of conserved residues with topologically important residues identified by network centrality measures. The analysis of conserved and structurally important residues helps in understanding their role in structural stability and function of these proteins. In this paper, we also discuss the significance of these conserved residues in disease association across the human ankyrin protein clusters.

Prediction of two novel overlapping ORFs in the genome of SARS-CoV-2

Six candidate overlapping genes have been detected in SARS-CoV-2, yet current methods struggle to detect overlapping genes that recently originated. However, such genes might encode proteins beneficial to the virus, and provide a model system to understand gene birth. To complement existing detection methods, I first demonstrated that selection pressure to avoid stop codons in alternative reading frames is a driving force in the origin and retention of overlapping genes. I then built a detection method, CodScr, based on this selection pressure. Finally, I combined CodScr with methods that detect other properties of overlapping genes, such as a biased nucleotide and amino acid composition. I detected two novel ORFs (ORF-Sh and ORF-Mh), overlapping the spike and membrane genes respectively, which are under selection pressure and may be beneficial to SARS-CoV-2. ORF-Sh and ORF-Mh are present, as ORF uninterrupted by stop codons, in 100% and 95% of the SARS-CoV-2 genomes, respectively.

A Tale of Loops and Tails: The Role of Intrinsically Disordered Protein Regions in R-Loop Recognition and Phase Separation.

R-loops are non-canonical, three-stranded nucleic acid structures composed of a DNA:RNA hybrid, a displaced single-stranded (ss)DNA, and a trailing ssRNA overhang. R-loops perform critical biological functions under both normal and disease conditions. To elucidate their cellular functions, we need to understand the mechanisms underlying R-loop formation, recognition, signaling, and resolution. Previous high-throughput screens identified multiple proteins that bind R-loops, with many of these proteins containing folded nucleic acid processing and binding domains that prevent (e.g., topoisomerases), resolve (e.g., helicases, nucleases), or recognize (e.g., KH, RRMs) R-loops. However, a significant number of these R-loop interacting Enzyme and Reader proteins also contain long stretches of intrinsically disordered regions (IDRs). The precise molecular and structural mechanisms by which the folded domains and IDRs synergize to recognize and process R-loops or modulate R-loop-mediated signaling have not been fully explored. While studying one such modular R-loop Reader, the Fragile X Protein (FMRP), we unexpectedly discovered that the C-terminal IDR (C-IDR) of FMRP is the predominant R-loop binding site, with the three N-terminal KH domains recognizing the trailing ssRNA overhang. Interestingly, the C-IDR of FMRP has recently been shown to undergo spontaneous Liquid-Liquid Phase Separation (LLPS) assembly by itself or in complex with another non-canonical nucleic acid structure, RNA G-quadruplex. Furthermore, we have recently shown that FMRP can suppress persistent R-loops that form during transcription, a process that is also enhanced by LLPS via the assembly of membraneless transcription factories. These exciting findings prompted us to explore the role of IDRs in R-loop processing and signaling proteins through a comprehensive bioinformatics and computational biology study. Here, we evaluated IDR prevalence, sequence composition and LLPS propensity for the known R-loop interactome. We observed that, like FMRP, the majority of the R-loop interactome, especially Readers, contains long IDRs that are highly enriched in low complexity sequences with biased amino acid composition, suggesting that these IDRs could directly interact with R-loops, rather than being “mere flexible linkers” connecting the “functional folded enzyme or binding domains”. Furthermore, our analysis shows that several proteins in the R-loop interactome are either predicted to or have been experimentally demonstrated to undergo LLPS or are known to be associated with phase separated membraneless organelles. Thus, our overall results present a thought-provoking hypothesis that IDRs in the R-loop interactome can provide a functional link between R-loop recognition via direct binding and downstream signaling through the assembly of LLPS-mediated membrane-less R-loop foci. The absence or dysregulation of the function of IDR-enriched R-loop interactors can potentially lead to severe genomic defects, such as the widespread R-loop-mediated DNA double strand breaks that we recently observed in Fragile X patient-derived cells.

The Choice of Search Engine Affects Sequencing Depth and HLA Class I Allele-Specific Peptide Repertoires

Standardization of immunopeptidomics experiments across laboratories is a pressing issue within the field, and currently a variety of different methods for sample preparation and data analysis tools are applied. Here, we compared different software packages to interrogate immunopeptidomics datasets and found that Peaks reproducibly reports substantially more peptide sequences (~30–70%) compared with Maxquant, Comet, and MS-GF+ at a global false discovery rate (FDR) of <1%. We noted that these differences are driven by search space and spectral ranking. Furthermore, we observed differences in the proportion of peptides binding the human leukocyte antigen (HLA) alleles present in the samples, indicating that sequence-related differences affected the performance of each tested engine. Utilizing data from single HLA allele expressing cell lines, we observed significant differences in amino acid frequency among the peptides reported, with a broadly higher representation of hydrophobic amino acids L, I, P, and V reported by Peaks. We validated these results using data generated with a synthetic library of 2000 HLA-associated peptides from four common HLA alleles with distinct anchor residues. Our investigation highlights that search engines create a bias in peptide sequence depth and peptide amino acid composition, and resulting data should be interpreted with caution.

Erratum for Kogay et al., "Selection for Reducing Energy Cost of Protein Production Drives the GC Content and Amino Acid Composition Bias in Gene Transfer Agents".

Vol. 11, no. 4, e01206-20, 2020, [https://doi.org/10.1128/mBio.01206-20][1]. In the originally published version, Fig. S5 in the supplemental material was a duplicate of Table S5. Figure S5 has since been corrected online. [1]: /lookup/doi/10.1128/mBio.01206-20

Selection for Reducing Energy Cost of Protein Production Drives the GC Content and Amino Acid Composition Bias in Gene Transfer Agents.

Gene transfer agents (GTAs) are virus-like elements integrated into bacterial genomes, particularly, those of Alphaproteobacteria The GTAs can be induced under conditions of nutritional stress, incorporate random fragments of bacterial DNA into miniphage particles, lyse the host cells, and infect neighboring bacteria, thus enhancing horizontal gene transfer. We show that GTA genes evolve under conditions of pronounced positive selection for the reduction of the energy cost of protein production as shown by comparison of the amino acid compositions with those of both homologous viral genes and host genes. The energy saving in GTA genes is comparable to or even more pronounced than that in the genes encoding the most abundant, essential bacterial proteins. In cases in which viruses acquire genes from GTAs, the bias in amino acid composition disappears in the course of evolution, showing that reduction of the energy cost of protein production is an important factor of evolution of GTAs but not bacterial viruses. These findings strongly suggest that GTAs represent bacterial adaptations rather than selfish, virus-like elements. Because GTA production kills the host cell and does not propagate the GTA genome, it appears likely that the GTAs are retained in the course of evolution via kin or group selection. Therefore, we hypothesize that GTAs facilitate the survival of bacterial populations under energy-limiting conditions through the spread of metabolic and transport capabilities via horizontal gene transfer and increases in nutrient availability resulting from the altruistic suicide of GTA-producing cells.IMPORTANCE Kin selection and group selection remain controversial topics in evolutionary biology. We argue that these types of selection are likely to operate in bacterial populations by showing that bacterial gene transfer agents (GTAs), but not related viruses, evolve under conditions of positive selection for the reduction of the energy cost of GTA particle production. We hypothesize that GTAs are dedicated devices mediating the survival of bacteria under conditions of nutrient limitation. The benefits conferred by GTAs under nutritional stress conditions appear to include horizontal dissemination of genes that could provide bacteria with enhanced capabilities for nutrient utilization and increases of nutrient availability occurring through the lysis of GTA-producing bacteria.

A High-Throughput Screen for Transcription Activation Domains Reveals Their Sequence Features and Permits Prediction by Deep Learning

Acidic transcription activation domains (ADs) are encoded by a wide range of seemingly unrelated amino acid sequences, making it difficult to recognize features that promote their dynamic behavior, "fuzzy" interactions, and target specificity. We screened a large set of random 30-mer peptides for AD function in yeast and trained a deep neural network (ADpred) on the AD-positive and -negative sequences. ADpred identifies known acidic ADs within transcription factors and accurately predicts the consequences of mutations. Our work reveals that strong acidic ADs contain multiple clusters of hydrophobic residues near acidic side chains, explaining why ADs often have a biased amino acid composition. ADs likely use a binding mechanism similar to avidity where a minimum number of weak dynamic interactions are required between activator and target to generate biologically relevant affinity and invivo function. This mechanism explains the basis for fuzzy binding observed between acidic ADs and targets.

Insect Mouthpart Transcriptome Unveils Extension of Cuticular Protein Repertoire and Complex Organization.

SummaryInsects have developed intriguing cuticles with very specific structures and functions, including microstructures governing their interactions with transmitted microbes, such as in aphid mouthparts harboring virus receptors within such microstructures. Here, we provide the first transcriptome analysis of an insect mouthpart cuticle (“retort organs” [ROs], the stylets' precursors). This analysis defined stylets as a complex composite material. The retort transcriptome also allowed us to propose an algorithmic definition of a new cuticular protein (CP) family with low complexity and biased amino acid composition. Finally, we identified a differentially expressed gene encoding a pyrokinin (PK) neuropeptide precursor and characterizing the mandibular glands. Injection of three predicted synthetic peptides PK1/2/3 into aphids prior to ecdysis caused a molt-specific phenotype with altered head formation. Our study provides the most complete description to date of the potential protein composition of aphid stylets, which should improve the understanding of the transmission of stylet-borne viruses.

Amino acid substitution scoring matrices specific to intrinsically disordered regions in proteins

An amino acid substitution scoring matrix encapsulates the rates at which various amino acid residues in proteins are substituted by other amino acid residues, over time. Database search methods make use of substitution scoring matrices to identify sequences with homologous relationships. However, widely used substitution scoring matrices, such as BLOSUM series, have been developed using aligned blocks that are mostly devoid of disordered regions in proteins. Hence, these substitution-scoring matrices are mostly inappropriate for homology searches involving proteins enriched with disordered regions as the disordered regions have distinct amino acid compositional bias, and therefore expected to have undergone amino acid substitutions that are distinct from those in the ordered regions. We, therefore, developed a novel series of substitution scoring matrices referred to as EDSSMat by exclusively considering the substitution frequencies of amino acids in the disordered regions of the eukaryotic proteins. The newly developed matrices were tested for their ability to detect homologs of proteins enriched with disordered regions by means of SSEARCH tool. The results unequivocally demonstrate that EDSSMat matrices detect more number of homologs than the widely used BLOSUM, PAM and other standard matrices, indicating their utility value for homology searches of intrinsically disordered proteins.

Ragp: Pipeline for mining of plant hydroxyproline-rich glycoproteins with implementation in R.

Hydroxyproline-rich glycoproteins (HRGPs) are one of the most complex families of macromolecules found in plants, due to the diversity of glycans decorating the protein backbone, as well as the heterogeneity of the protein backbones. While this diversity is responsible for a wide array of physiological functions associated with HRGPs, it hinders attempts for homology based identification. Current approaches, based on identifying sequences with characteristic motifs and biased amino acid composition, are limited to prototypical sequences. Ragp is an R package for mining and analysis of HRGPs, with emphasis on arabinogalactan proteins. The ragp filtering pipeline exploits one of the HRGPs key features, the presence of hydroxyprolines which represent glycosylation sites. Main package features include prediction of proline hydroxylation sites, amino acid motif and bias analyses, efficient communication with web servers for prediction of N-terminal signal peptides, glycosylphosphatidylinositol modification sites and disordered regions and the ability to annotate sequences through hmmscan and subsequent GO enrichment, based on predicted Pfam domains. As such, ragp extends R's rich ecosystem for high-throughput sequence data analyses. The ragp R package is available under the MIT Open Source license and is freely available to download from GitHub at: https://github.com/missuse/ragp.

Protein Abundance Biases the Amino Acid Composition of Disordered Regions to Minimize Non-functional Interactions

In eukaryotes, disordered regions cover up to 50% of proteomes and mediate fundamental cellular processes. In contrast to globular domains, where about half of the amino acids are buried in the protein interior, disordered regions show higher solvent accessibility, which makes them prone to engage in non-functional interactions. Such interactions are exacerbated by the law of mass action, prompting the question of how they are minimized in abundant proteins. We find that interaction propensity or “stickiness” of disordered regions negatively correlates with their cellular abundance, both in yeast and human. Strikingly, considering yeast proteins where a large fraction of the sequence is disordered, the correlation between stickiness and abundance reaches R=−0.55. Beyond this global amino-acid composition bias, we identify three rules by which amino-acid composition of disordered regions adjusts with high abundance. First, lysines are preferred over arginines, consistent with the latter amino acid being stickier than the former. Second, compensatory effects exist, whereby a sticky region can be tolerated if it is compensated by a distal non-sticky region. Third, such compensation requires a lower average stickiness at the same abundance when compared to a scenario where stickiness is homogeneous throughout the sequence. We validate these rules experimentally, employing them as different strategies to rescue an otherwise sticky protein fragment from aggregation. Our results highlight that non-functional interactions represent a significant constraint in cellular systems and reveal simple rules by which protein sequences adapt to that constraint. Data from this work are deposited in Figshare, at https://doi.org/10.6084/m9.figshare.8068937.v3.

Sequence Versus Composition: What Prescribes IDP Biophysical Properties?

Intrinsically disordered proteins (IDPs) represent a distinct class of proteins and are distinguished from globular proteins by conformational plasticity, high evolvability and a broad functional repertoire. Some of their properties are reminiscent of early proteins, but their abundance in eukaryotes, functional properties and compositional bias suggest that IDPs appeared at later evolutionary stages. The spectrum of IDP properties and their determinants are still not well defined. This study compares rudimentary physicochemical properties of IDPs and globular proteins using bioinformatic analysis on the level of their native sequences and random sequence permutations, addressing the contributions of composition versus sequence as determinants of the properties. IDPs have, on average, lower predicted secondary structure contents and aggregation propensities and biased amino acid compositions. However, our study shows that IDPs exhibit a broad range of these properties. Induced fold IDPs exhibit very similar compositions and secondary structure/aggregation propensities to globular proteins, and can be distinguished from unfoldable IDPs based on analysis of these sequence properties. While amino acid composition seems to be a major determinant of aggregation and secondary structure propensities, sequence randomization does not result in dramatic changes to these properties, but for both IDPs and globular proteins seems to fine-tune the tradeoff between folding and aggregation.

Low cationicity is important for systemic in vivo efficacy of database-derived peptides against drug-resistant Gram-positive pathogens

As bacterial resistance to traditional antibiotics continues to emerge, new alternatives are urgently needed. Antimicrobial peptides (AMPs) are important candidates. However, how AMPs are designed with in vivo efficacy is poorly understood. Our study was designed to understand structural moieties of cationic peptides that would lead to their successful use as antibacterial agents. In contrast to the common perception, serum binding and peptide stability were not the major reasons for in vivo failure in our studies. Rather, our systematic study of a series of peptides with varying lysines revealed the significance of low cationicity for systemic in vivo efficacy against Gram-positive pathogens. We propose that peptides with biased amino acid compositions are not favored to associate with multiple host factors and are more likely to show in vivo efficacy. Thus, our results uncover a useful design strategy for developing potent peptides against multidrug-resistant pathogens.

Codon selection reduces GC content bias in nucleic acids encoding for intrinsically disordered proteins.

Protein-coding nucleic acids exhibit composition and codon biases between sequences coding for intrinsically disordered regions (IDRs) and those coding for structured regions. IDRs are regions of proteins that are folding self-insufficient and which function without the prerequisite of folded structure. Several authors have investigated composition bias or codon selection in regions encoding for IDRs, primarily in Eukaryota, and concluded that elevated GC content is the result of the biased amino acid composition of IDRs. We substantively extend previous work by examining GC content in regions encoding IDRs, from 44 species in Eukaryota, Archaea, and Bacteria, spanning a wide range of GC content. We confirm that regions coding for IDRs show a significantly elevated GC content, even across all domains of life. Although this is largely attributable to the amino acid composition bias of IDRs, we show that this bias is independent of the overall GC content and, most importantly, we are the first to observe that GC content bias in IDRs is significantly different than expected from IDR amino acid composition alone. We empirically find compensatory codon selection that reduces the observed GC content bias in IDRs. This selection is dependent on the overall GC content of the organism. The codon selection bias manifests as use of infrequent, AT-rich codons in encoding IDRs. Further, we find these relationships to be independent of the intrinsic disorder prediction method used, and independent of estimated translation efficiency. These observations are consistent with the previous work, and we speculate on whether the observed biases are causal or symptomatic of other driving forces.

Solution Ensemble of the C-Terminal Domain from the Transcription Factor Pdx1 Resembles an Excluded Volume Polymer.

The pancreatic and duodenal homeobox 1 (Pdx1) is an essential pancreatic transcription factor. The C-terminal intrinsically disordered domain of Pdx1 (Pdx1-C) has a heavily biased amino acid composition; most notably, 18 of 83 residues are proline, including a hexaproline cluster near the middle of the chain. For these reasons, Pdx1-C is an attractive target for structure characterization, given the availability of suitable methods. To determine the solution ensembles of disordered proteins, we have developed a suite of 13C direct-detect NMR experiments that provide high spectral quality, even in the presence of strong proline enrichment. Here, we have extended our suite of NMR experiments to include four new pulse programs designed to record backbone residual dipolar couplings in a 13C,15N-CON detection format. Using our NMR strategy, in combination with small-angle X-ray scattering measurements and Monte Carlo simulations, we have determined that Pdx1-C is extended in solution, with a radius of gyration and internal scaling similar to that of an excluded volume polymer, and a subtle tendency toward a collapsed structure to the N-terminal side of the hexaproline sequence. This structure leaves Pdx1-C exposed for interactions with trans-regulatory co-factors that contribute with Pdx1 to transcription control in the cell.