Proteomic signatures: amino acid and oligopeptide compositions differentiate among phyla

Tracing the birth and intrinsic disorder of loops and domains in protein evolution

Protein loops and structural domains are building blocks of molecular structure. They hold evolutionary memory and are largely responsible for the many functions and processes that drive the living world. Here, we briefly review two decades of phylogenomic data-driven research focusing on the emergence and evolution of these elemental architects of protein structure. Phylogenetic trees of domains reconstructed from the proteomes of organisms belonging to all three superkingdoms and viruses were used to build chronological timelines describing the origin of each domain and its embedded loops at different levels of structural abstraction. These timelines consistently recovered six distinct evolutionary phases and a most parsimonious evolutionary progression of cellular life. The timelines also traced the birth of domain structures from loops, which allowed to model their growth ab initio with AlphaFold2. Accretion decreased the disorder of the growing molecules, suggesting disorder is molecular size-dependent. A phylogenomic survey of disorder revealed that loops and domains evolved differently. Loops were highly disordered, disorder increased early in evolution, and ordered and moderate disordered structures were derived. Gradual replacement of loops with α-helix and β-strand bracing structures over time paved the way for the dominance of more disordered loop types. In contrast, ancient domains were ordered, with disorder evolving as a benefit acquired later in evolution. These evolutionary patterns explain inverse correlations between disorder and sequence length of loops and domains. Our findings provide a deep evolutionary view of the link between structure, disorder, flexibility, and function.

On Protein Loops, Prior Molecular States and Common Ancestors of Life

The principle of continuity demands the existence of prior molecular states and common ancestors responsible for extant macromolecular structure. Here, we focus on the emergence and evolution of loop prototypes - the elemental architects of protein domain structure. Phylogenomic reconstruction spanning superkingdoms and viruses generated an evolutionary chronology of prototypes with six distinct evolutionary phases defining a most parsimonious evolutionary progression of cellular life. Each phase was marked by strategic prototype accumulation shaping the structures and functions of common ancestors. The last universal common ancestor (LUCA) of cells and viruses and the last universal cellular ancestor (LUCellA) defined stem lines that were structurally and functionally complex. The evolutionary saga highlighted transformative forces. LUCA lacked biosynthetic ribosomal machinery, while the pivotal LUCellA lacked essential DNA biosynthesis and modern transcription. Early proteins therefore relied on RNA for genetic information storage but appeared initially decoupled from it, hinting at transformative shifts of genetic processing. Urancestral loop types suggest advanced folding designs were present at an early evolutionary stage. An exploration of loop geometric properties revealed gradual replacement of prototypes with α-helix and β-strand bracing structures over time, paving the way for the dominance of other loop types. AlphFold2-generated atomic models of prototype accretion described patterns of fold emergence. Our findings favor a ‛processual' model of evolving stem lines aligned with Woese's vision of a communal world. This model prompts discussing the 'problem of ancestors' and the challenges that lie ahead for research in taxonomy, evolution and complexity.

Nanosecond Transient IR Spectroscopy of Halorhodopsin in Living Cells

The ability to track minute changes of a single amino acid residue in a cellular environment is causing a paradigm shift in the attempt to fully understand the responses of biomolecules that are highly sensitive to their environment. Detecting early protein dynamics in living cells is crucial to understanding their mechanisms, such as those of photosynthetic proteins. Here, we elucidate the light response of the microbial chloride pump NmHR from the marine bacterium Nonlabens marinus, located in the membrane of living Escherichia coli cells, using nanosecond time-resolved UV/vis and IR absorption spectroscopy over the time range from nanoseconds to seconds. Transient structural changes of the retinal cofactor and the surrounding apoprotein are recorded using light-induced time-resolved UV/vis and IR difference spectroscopy. Of particular note, we have resolved the kinetics of the transient deprotonation of a single cysteine residue during the photocycle of NmHR out of the manifold of molecular vibrations of the cells. These findings are of high general relevance, given the successful development of optogenetic tools from photoreceptors to interfere with enzymatic and neuronal pathways in living organisms using light pulses as a noninvasive trigger.

In Silico and In Vitro Evaluation of the Molecular Mimicry of the SARS-CoV-2 Spike Protein by Common Short Constituent Sequences (cSCSs) in the Human Proteome: Toward Safer Epitope Design for Vaccine Development

Spike protein sequences in SARS-CoV-2 have been employed for vaccine epitopes, but many short constituent sequences (SCSs) in the spike protein are present in the human proteome, suggesting that some anti-spike antibodies induced by infection or vaccination may be autoantibodies against human proteins. To evaluate this possibility of "molecular mimicry" in silico and in vitro, we exhaustively identified common SCSs (cSCSs) found both in spike and human proteins bioinformatically. The commonality of SCSs between the two systems seemed to be coincidental, and only some cSCSs were likely to be relevant to potential self-epitopes based on three-dimensional information. Among three antibodies raised against cSCS-containing spike peptides, only the antibody against EPLDVL showed high affinity for the spike protein and reacted with an EPLDVL-containing peptide from the human unc-80 homolog protein. Western blot analysis revealed that this antibody also reacted with several human proteins expressed mainly in the small intestine, ovary, and stomach. Taken together, these results showed that most cSCSs are likely incapable of inducing autoantibodies but that at least EPLDVL functions as a self-epitope, suggesting a serious possibility of infection-induced or vaccine-induced autoantibodies in humans. High-risk cSCSs, including EPLDVL, should be excluded from vaccine epitopes to prevent potential autoimmune disorders.

Redox-Regulated Synthetic Channels: Enabling Reversible Ion Transport by Modulating the Ion-Permeation Pathway

Natural redox-regulated channel proteins often utilize disulfide bonds as redox sensors for adaptive regulation of channel conformations in response to diverse physiological environments. In this study, we developed novel synthetic ion channels capable of reversibly switching their ion-transport capabilities by incorporating multiple disulfide bonds into artificial systems. X-ray structural analysis and electrophysiological experiments demonstrated that these disulfide-bridged molecules possess well-defined tubular cavities and can be efficiently inserted into lipid bilayers to form artificial ion channels. More importantly, the disulfide bonds in these molecules serve as redox-tunable switches to regulate the formation and disruption of ion-permeation pathways, thereby achieving a transition in the transmembrane transport process between the ON and OFF states.

Living in trinity of extremes: Genomic and proteomic signatures of halophilic, thermophilic, and pH adaptation

Since nucleic acids and proteins of unicellular prokaryotes are directly exposed to extreme environmental conditions, it is possible to explore the genomic-proteomic compositional determinants of molecular mechanisms of adaptation developed by them in response to harsh environmental conditions. Using a wealth of currently available complete genomes/proteomes we were able to explore signatures of adaptation to three environmental factors, pH, salinity, and temperature, observing major trends in compositions of their nucleic acids and proteins. We derived predictors of thermostability, halophilic, and pH adaptations and complemented them by the principal components analysis. We observed a clear difference between thermophilic and salinity/pH adaptations, whereas latter invoke seemingly overlapping mechanisms. The genome-proteome compositional trade-off reveals an intricate balance between the work of base paring and base stacking in stabilization of coding DNA and r/tRNAs, and, at the same time, universal requirements for the stability and foldability of proteins regardless of the nucleotide biases. Nevertheless, we still found hidden fingerprints of ancient evolutionary connections between the nucleotide and amino acid compositions indicating their emergence, mutual evolution, and adjustment. The evolutionary perspective on the adaptation mechanisms is further studied here by means of the comparative analysis of genomic/proteomic traits of archaeal and bacterial species. The overall picture of genomic/proteomic signals of adaptation obtained here provides a foundation for future engineering and design of functional biomolecules resistant to harsh environments.

Do "Newly Born" orphan proteins resemble "Never Born" proteins? A study using three deep learning algorithms

"Newly Born" proteins, devoid of detectable homology to any other proteins, known as orphan proteins, occur in a single species or within a taxonomically restricted gene family. They are generated by the expression of novel open reading frames, and appear throughout evolution. We were curious if three recently developed programs for predicting protein structures, namely, AlphaFold2, RoseTTAFold, and ESMFold, might be of value for comparison of such "Newly Born" proteins to random polypeptides with amino acid content similar to that of native proteins, which have been called "Never Born" proteins. The programs were used to compare the structures of two sets of "Never Born" proteins that had been expressed-Group 1, which had been shown experimentally to possess substantial secondary structure, and Group 3, which had been shown to be intrinsically disordered. Overall, although the models generated were scored as being of low quality, they nevertheless revealed some general principles. Specifically, all four members of Group 1 were predicted to be compact by all three algorithms, in agreement with the experimental data, whereas the members of Group 3 were predicted to be very extended, as would be expected for intrinsically disordered proteins, again consistent with the experimental data. These predicted differences were shown to be statistically significant by comparing their accessible surface areas. The three programs were then used to predict the structures of three orphan proteins whose crystal structures had been solved, two of which display novel folds. Surprisingly, only for the protein which did not have a novel fold, and was taxonomically restricted, rather than being a true orphan, did all three algorithms predict very similar, high-quality structures, closely resembling the crystal structure. Finally, they were used to predict the structures of seven orphan proteins with well-identified biological functions, whose 3D structures are not known. Two proteins, which were predicted to be disordered based on their sequences, are predicted by all three structure algorithms to be extended structures. The other five were predicted to be compact structures with only two exceptions in the case of AlphaFold2. All three prediction algorithms make remarkably similar and high-quality predictions for one large protein, HCO_11565, from a nematode. It is conjectured that this is due to many homologs in the taxonomically restricted family of which it is a member, and to the fact that the Dali server revealed several nonrelated proteins with similar folds. An animated Interactive 3D Complement (I3DC) is available in Proteopedia at http://proteopedia.org/w/Journal:Proteins:3.

Ultrasensitive HPLC-MS Quantification of S-(2-Succino) Cysteine Based on Ethanol/Acetyl Chloride Derivatization in Fumarate Accumulation Cells

Succination is a nonenzymatic and irreversible post-translational modification (PTM) with important biological significance, yielding S-(2-succino) cysteine (2SC) residue. This PTM is low in abundance and often requires a large amount of protein samples for 2SC quantification. In this work, an efficient quantification method based on ethanol/acetyl chloride chemical derivatization was developed. The three carboxyl groups of 2SC were all esterified to increase hydrophobicity, greatly improving its ionization efficiency. The sensitivity was increased by 112 times; the limit of detection was reduced to 0.885 fmol, and the protein usage was reduced by at least 10 times. The established method was used to detect the overall concentration of 2SC in fumarate accumulation cells quantitatively.

DistilProtBert: a distilled protein language model used to distinguish between real proteins and their randomly shuffled counterparts

SUMMARY

Recently, deep learning models, initially developed in the field of natural language processing (NLP), were applied successfully to analyze protein sequences. A major drawback of these models is their size in terms of the number of parameters needed to be fitted and the amount of computational resources they require. Recently, 'distilled' models using the concept of student and teacher networks have been widely used in NLP. Here, we adapted this concept to the problem of protein sequence analysis, by developing DistilProtBert, a distilled version of the successful ProtBert model. Implementing this approach, we reduced the size of the network and the running time by 50%, and the computational resources needed for pretraining by 98% relative to ProtBert model. Using two published tasks, we showed that the performance of the distilled model approaches that of the full model. We next tested the ability of DistilProtBert to distinguish between real and random protein sequences. The task is highly challenging if the composition is maintained on the level of singlet, doublet and triplet amino acids. Indeed, traditional machine-learning algorithms have difficulties with this task. Here, we show that DistilProtBert preforms very well on singlet, doublet and even triplet-shuffled versions of the human proteome, with AUC of 0.92, 0.91 and 0.87, respectively. Finally, we suggest that by examining the small number of false-positive classifications (i.e. shuffled sequences classified as proteins by DistilProtBert), we may be able to identify de novo potential natural-like proteins based on random shuffling of amino acid sequences.

AVAILABILITY AND IMPLEMENTATION

https://github.com/yarongef/DistilProtBert.

Experimental Approaches for Investigating Disulfide-Based Redox Relays in Cells

Reversible oxidation of cysteine residues within proteins occurs naturally during normal cellular homeostasis and can increase during oxidative stress. Cysteine oxidation often leads to the formation of disulfide bonds, which can impact protein folding, stability, and function. Work in both prokaryotic and eukaryotic models over the past five decades has revealed several multiprotein systems that use thiol-dependent oxidoreductases to mediate disulfide bond reduction, formation, and/or rearrangement. Here, I provide an overview of how these systems operate to carry out disulfide exchange reactions in different cellular compartments, with a focus on their roles in maintaining redox homeostasis, transducing redox signals, and facilitating protein folding. Additionally, I review thiol-independent and thiol-dependent approaches for interrogating what proteins partner together in such disulfide-based redox relays. While the thiol-independent approaches rely either on predictive measures or standard procedures for monitoring protein-protein interactions, the thiol-dependent approaches include direct disulfide trapping methods as well as thiol-dependent chemical cross-linking. These strategies may prove useful in the systematic characterization of known and newly discovered disulfide relay mechanisms and redox switches involved in oxidant defense, protein folding, and cell signaling.

The Mutational Robustness of the Genetic Code and Codon Usage in Environmental Context: A Non-Extremophilic Preference?

The genetic code was evolved, to some extent, to minimize the effects of mutations. The effects of mutations depend on the amino acid repertoire, the structure of the genetic code and frequencies of amino acids in proteomes. The amino acid compositions of proteins and corresponding codon usages are still under selection, which allows us to ask what kind of environment the standard genetic code is adapted to. Using simple computational models and comprehensive datasets comprising genomic and environmental data from all three domains of Life, we estimate the expected severity of non-synonymous genomic mutations in proteins, measured by the change in amino acid physicochemical properties. We show that the fidelity in these physicochemical properties is expected to deteriorate with extremophilic codon usages, especially in thermophiles. These findings suggest that the genetic code performs better under non-extremophilic conditions, which not only explains the low substitution rates encountered in halophiles and thermophiles but the revealed relationship between the genetic code and habitat allows us to ponder on earlier phases in the history of Life.

The language of proteins: NLP, machine learning & protein sequences

Natural language processing (NLP) is a field of computer science concerned with automated text and language analysis. In recent years, following a series of breakthroughs in deep and machine learning, NLP methods have shown overwhelming progress. Here, we review the success, promise and pitfalls of applying NLP algorithms to the study of proteins. Proteins, which can be represented as strings of amino-acid letters, are a natural fit to many NLP methods. We explore the conceptual similarities and differences between proteins and language, and review a range of protein-related tasks amenable to machine learning. We present methods for encoding the information of proteins as text and analyzing it with NLP methods, reviewing classic concepts such as bag-of-words, k-mers/n-grams and text search, as well as modern techniques such as word embedding, contextualized embedding, deep learning and neural language models. In particular, we focus on recent innovations such as masked language modeling, self-supervised learning and attention-based models. Finally, we discuss trends and challenges in the intersection of NLP and protein research.

Otaki J. Search for Human-Specific Proteins Based on Availability Scores of Short Constituent Sequences: Identification of a WRWSH Protein in Human Testis

Little is known about protein sequences unique in humans. Here, we performed alignment-free sequence comparisons based on the availability (frequency bias) of short constituent amino acid (aa) sequences (SCSs) in proteins to search for human-specific proteins. Focusing on 5-aa SCSs (pentats), exhaustive comparisons of availability scores among the human proteome and other nine mammalian proteomes in the nonredundant (nr) database identified a candidate protein containing WRWSH, here called FAM75, as human-specific. Examination of various human genome sequences revealed that FAM75 had genomic DNA sequences for either WRWSH or WRWSR due to a single nucleotide polymorphism (SNP). FAM75 and its related protein FAM205A were found to be produced through alternative splicing. The FAM75 transcript was found only in humans, but the FAM205A transcript was also present in other mammals. In humans, both FAM75 and FAM205A were expressed specifically in testis at the mRNA level, and they were immunohistochemically located in cells in seminiferous ducts and in acrosomes in spermatids at the protein level, suggesting their possible function in sperm development and fertilization. This study highlights a practical application of SCS-based methods for protein searches and suggests possible contributions of SNP variants and alternative splicing of FAM75 to human evolution.

Global chemical modifications comparison of human plasma proteome from two different age groups

In this study, two groups of human plasma proteome at different age groups (old and young) were used to perform a comparison of global chemical modifications, as determined by tandem mass spectrometry (MS/MS) combined with non-limiting modification identification algorithms. The sulfhydryl in the cysteine A total of 4 molecular modifications were found to have significant differences passing random grouping tests: the succinylation and phosphorylation modification of cysteine (Cys, C) and the modification of lysine (Lys, K) with threonine (Thr, T) were significantly higher in the old group than in the young group, while the carbamylation of lysine was lower in the young group. We speculate that there is an increase in certain modified proteins in the blood of the old people which, in turn, changes the function of those proteins. This change may be one of the reasons why old people are more likely than young people to be at risk for age-related diseases, such as metabolic diseases, cerebral and cardiovascular diseases, and cancer.

Integration of sulfate assimilation with carbon and nitrogen metabolism in transition from C3 to C4 photosynthesis

The first product of sulfate assimilation in plants, cysteine, is a proteinogenic amino acid and a source of reduced sulfur for plant metabolism. Cysteine synthesis is the convergence point of the three major pathways of primary metabolism: carbon, nitrate, and sulfate assimilation. Despite the importance of metabolic and genetic coordination of these three pathways for nutrient balance in plants, the molecular mechanisms underlying this coordination, and the sensors and signals, are far from being understood. This is even more apparent in C4 plants, where coordination of these pathways for cysteine synthesis includes the additional challenge of differential spatial localization. Here we review the coordination of sulfate, nitrate, and carbon assimilation, and show how they are altered in C4 plants. We then summarize current knowledge of the mechanisms of coordination of these pathways. Finally, we identify urgent questions to be addressed in order to understand the integration of sulfate assimilation with carbon and nitrogen metabolism particularly in C4 plants. We consider answering these questions to be a prerequisite for successful engineering of C4 photosynthesis into C3 crops to increase their efficiency.

Bis (Salicylaldehyde-1, 2-Phenylene Diimine)Mn(III) Chloride (Mn(III)-Salophen) Catalysed Oxidation of Thiols to Symmetrical Disulfides Using Urea Hydrogen Peroxide (UHP) as Mild and Efficient Oxidant

A variety of thiols were oxidised efficiently by a catalytic amount of Mn(III)-salophen 1 in the presence of urea hydrogen peroxide adduct 2 as a convenient and mild oxidant to afford the corresponding disulfides in high yields in quite short reaction times.

Identification of a Molecular Latch that Regulates Staphylococcal Virulence

Virulence induction in the Staphylococcus aureus is under the control of a quorum sensing (QS) circuit encoded by the accessory gene regulator (agr) locus. Allelic variation within agr produces four QS specificity groups, each producing a unique secreted autoinducer peptide (AIP) and receptor histidine kinase (RHK), AgrC. Cognate AIP-AgrC interactions activate virulence through a two-component signaling cascade, whereas non-cognate pairs are generally inhibitory. Here we pinpoint a key hydrogen-bonding interaction within AgrC that acts as a switch to convert helical motions propagating from the receptor sensor domain into changes in inter-domain association within the kinase module. AgrC mutants lacking this interaction are constitutively active in vitro and in vivo, the latter leading to a pronounced attenuation of S. aureus biofilm formation. Thus, our work sheds light on the regulation of this biomedically important RHK.

Adaptation of Proteins to the Cold in Antarctic Fish: A Role for Methionine?

The evolution of antifreeze glycoproteins has enabled notothenioid fish to flourish in the freezing waters of the Southern Ocean. Whereas successful at the biodiversity level to life in the cold, paradoxically at the cellular level these stenothermal animals have problems producing, folding, and degrading proteins at their ambient temperatures of -1.86 °C. In this first multi-species transcriptome comparison of the amino acid composition of notothenioid proteins with temperate teleost proteins, we show that, unlike psychrophilic bacteria, Antarctic fish provide little evidence for the mass alteration of protein amino acid composition to enhance protein folding and reduce protein denaturation in the cold. The exception was the significant overrepresentation of positions where leucine in temperate fish proteins was replaced by methionine in the notothenioid orthologues. We hypothesize that these extra methionines have been preferentially assimilated into the genome to act as redox sensors in the highly oxygenated waters of the Southern Ocean. This redox hypothesis is supported by analyses of notothenioids showing enrichment of genes associated with responses to environmental stress, particularly reactive oxygen species. So overall, although notothenioid fish show cold-associated problems with protein homeostasis, they may have modified only a selected number of biochemical pathways to work efficiently below 0 °C. Even a slight warming of the Southern Ocean might disrupt the critical functions of this handful of key pathways with considerable impacts for the functioning of this ecosystem in the future.

Cysteine reactivity across the subcellular universe

Cysteine residues are concentrated at key functional sites within proteins, performing diverse roles in metal binding, catalysis, and redox chemistry. Chemoproteomic platforms to interrogate the reactive cysteinome have developed significantly over the past 10 years, resulting in a greater understanding of cysteine functionality, modification, and druggability. Recently, chemoproteomic methods to examine reactive cysteine residues from specific subcellular organelles have provided significantly improved proteome coverage and highlights the unique functionalities of cysteine residues mediated by cellular localization. Here, the diverse physicochemical properties of the mammalian subcellular organelles are explored in the context of their effects on cysteine reactivity. The unique functions of cysteine residues found in the mitochondria and endoplasmic reticulum are highlighted, together with an overview into chemoproteomic platforms employed to investigate cysteine reactivity in subcellular organelles.

Global pentapeptide statistics are far away from expected distributions

The relationships between polypeptide composition, sequence, structure and function have been puzzling biologists ever since first protein sequences were determined. Here, we study the statistics of occurrence of all possible pentapeptide sequences in known proteins. To compensate for the non-uniform distribution of individual amino acid residues in protein sequences, we investigate separately all possible permutations of every given amino acid composition. For the majority of permutation groups we find that pentapeptide occurrences deviate strongly from the expected binomial distributions, and that the observed distributions are also characterized by high numbers of outlier sequences. An analysis of identified outliers shows they often contain known motifs and rare amino acids, suggesting that they represent important functional elements. We further compare the pentapeptide composition of regions known to correspond to protein domains with that of non-domain regions. We find that a substantial number of pentapeptides is clearly strongly favored in protein domains. Finally, we show that over-represented pentapeptides are significantly related to known functional motifs and to predicted ancient structural peptides.

Proteome-scale relationships between local amino acid composition and protein fates and functions

Proteins with low-complexity domains continue to emerge as key players in both normal and pathological cellular processes. Although low-complexity domains are often grouped into a single class, individual low-complexity domains can differ substantially with respect to amino acid composition. These differences may strongly influence the physical properties, cellular regulation, and molecular functions of low-complexity domains. Therefore, we developed a bioinformatic approach to explore relationships between amino acid composition, protein metabolism, and protein function. We find that local compositional enrichment within protein sequences is associated with differences in translation efficiency, abundance, half-life, protein-protein interaction promiscuity, subcellular localization, and molecular functions of proteins on a proteome-wide scale. However, local enrichment of related amino acids is sometimes associated with opposite effects on protein regulation and function, highlighting the importance of distinguishing between different types of low-complexity domains. Furthermore, many of these effects are discernible at amino acid compositions below those required for classification as low-complexity or statistically-biased by traditional methods and in the absence of homopolymeric amino acid repeats, indicating that thresholds employed by classical methods may not reflect biologically relevant criteria. Application of our analyses to composition-driven processes, such as the formation of membraneless organelles, reveals distinct composition profiles even for closely related organelles. Collectively, these results provide a unique perspective and detailed insights into relationships between amino acid composition, protein metabolism, and protein functions.

Low-complexity domains in protein sequences are regions that are composed of only a few amino acids in the protein “alphabet”. These domains often have unique chemical properties and play important biological roles in both normal and disease-related processes. While a number of approaches have been developed to define low-complexity domains, these methods each possess conceptual limitations. Therefore, we developed a complementary approach that focuses on local amino acid composition (i.e. the amino acid composition within small regions of proteins). We find that high local composition of individual amino acids is associated with pervasive effects on protein metabolism, subcellular localization, and molecular function on a proteome-wide scale. Importantly, the nature of the effects depend on the type of amino acid enriched within the examined domains, and are observable in the absence of classically-defined low-complexity (and related) domains. Furthermore, we define the compositions of proteins involved in the formation of membraneless, protein-rich organelles such as stress granules and P-bodies. Our results provide a coherent view and unprecedented resolution of the effects of local amino acid enrichment on protein biology.

In silico identification and characterization of sensory motifs in the transcriptional regulators of the ArsR-SmtB family

The ArsR-SmtB family of proteins displays the greatest diversity among the bacterial metal-binding transcriptional regulators with regard to the variety of metal ions that they can sense. In the presence of increased levels of toxic heavy metals, these proteins dissociate from their cognate DNA upon the direct binding of metal ions to the appropriate sites, designated motifs on the proteins, either at the interface of the dimers or at the intra-subunit locations. In addition to the metal-mediated regulation, some proteins were also found to control transcription via redox reactions. In the present work, we have identified several new sequence motifs and expanded the knowledge base of metal binding sites in the ArsR-SmtB family of transcriptional repressors, and characterized them in terms of the ligands to the metal, distribution among different phyla of bacteria and archaea, amino acid propensities, protein length distributions and evolutionary interrelationships. We built structural models of the motifs to show the importance of specific residues in an individual motif. The wide abundance of these motifs in sequences of bacteria and archaea indicates the importance of these regulators in combating metal-toxicity within and outside of the hosts. We also show that by using residue composition, one can distinguish the ArsR-SmtB proteins from other metalloregulatory families. In addition, we show the importance of horizontal gene transfer in microorganisms, residing in similar habitats, on the evolution of the structural motifs in the family. Knowledge of the diverse metalloregulatory systems in microorganisms could enable us to manipulate specific genes that may result in a toxic metal-free environment.

Insights into Unfolded Proteins from the Intrinsic ϕ/ψ Propensities of the AAXAA Host-Guest Series

Various host-guest peptide series are used by experimentalists as reference conformational states. One such use is as a baseline for random-coil NMR chemical shifts. Comparison to this random-coil baseline, through secondary chemical shifts, is used to infer protein secondary structure. The use of these random-coil data sets rests on the perception that the reference chemical shifts arise from states where there is little or no conformational bias. However, there is growing evidence that the conformational composition of natively and nonnatively unfolded proteins fail to approach anything that can be construed as random coil. Here, we use molecular dynamics simulations of an alanine-based host-guest peptide series (AAXAA) as a model of unfolded and denatured states to examine the intrinsic propensities of the amino acids. We produced ensembles that are in good agreement with the experimental NMR chemical shifts and confirm that the sampling of the 20 natural amino acids in this peptide series is be far from random. Preferences toward certain regions of conformational space were both present and dependent upon the environment when compared under conditions typically used to denature proteins, i.e., thermal and chemical denaturation. Moreover, the simulations allowed us to examine the conformational makeup of the underlying ensembles giving rise to the ensemble-averaged chemical shifts. We present these data as an intrinsic backbone propensity library that forms part of our Structural Library of Intrinsic Residue Propensities to inform model building, to aid in interpretation of experiment, and for structure prediction of natively and nonnatively unfolded states.

Analysis of the optimality of the standard genetic code

Many theories have been proposed attempting to explain the origin of the genetic code. In this work, we compare performance of the standard genetic code against millions of randomly generated codes. On left, ability of genetic codes to encode additional information and their robustness to frameshift mutations.

Limitations of Mass Spectrometry-Based Peptidomic Approaches

Mass spectrometry-based peptidomic approaches are powerful techniques to detect and identify the peptide content of biological samples. The present study investigated the limitations of peptidomic approaches using trimethylammonium butyrate isotopic tags to quantify relative peptide levels and Mascot searches to identify peptides. Data were combined from previous studies on human cell lines or mouse tissues. The combined databases contain 2155 unique peptides ranging in mass from 444 to 8765 Da, with the vast majority between 1 and 3 kDa. The amino acid composition of the identified peptides generally reflected the frequency in the Eukaryotic proteome with the exception of Cys, which was not present in any of the identified peptides in the free-SH form but was detected at low frequency as a disulfide with Cys residues, a disulfide with glutathione, or as S-cyanocysteine. To test if the low detection rate of peptides smaller than 500 Da, larger than 3 kDa, or containing Cys was a limitation of the peptidomics procedure, tryptic peptides of known proteins were processed for peptidomics using the same approach used for human cell lines and mouse tissues. The identified tryptic peptides ranged from 516 to 2418 Da, whereas the theoretical digest ranged from 217 to 7559 Da. Peptides with Cys were rarely detected and, if present, the Cys was usually modified S-cyanocysteine. Additionally, peptides with mono- and di-iodo Tyr and His were identified. Taken together, there are limitations of peptidomic techniques, and awareness of these limitations is important to properly use and interpret results. Graphical Abstract ᅟ.

Environmental Pressure May Change the Composition Protein Disorder in Prokaryotes

Many prokaryotic organisms have adapted to incredibly extreme habitats. The genomes of such extremophiles differ from their non-extremophile relatives. For example, some proteins in thermophiles sustain high temperatures by being more compact than homologs in non-extremophiles. Conversely, some proteins have increased volumes to compensate for freezing effects in psychrophiles that survive in the cold. Here, we revealed that some differences in organisms surviving in extreme habitats correlate with a simple single feature, namely the fraction of proteins predicted to have long disordered regions. We predicted disorder with different methods for 46 completely sequenced organisms from diverse habitats and found a correlation between protein disorder and the extremity of the environment. More specifically, the overall percentage of proteins with long disordered regions tended to be more similar between organisms of similar habitats than between organisms of similar taxonomy. For example, predictions tended to detect substantially more proteins with long disordered regions in prokaryotic halophiles (survive high salt) than in their taxonomic neighbors. Another peculiar environment is that of high radiation survived, e.g. by Deinococcus radiodurans. The relatively high fraction of disorder predicted in this extremophile might provide a shield against mutations. Although our analysis fails to establish causation, the observed correlation between such a simplistic, coarse-grained, microscopic molecular feature (disorder content) and a macroscopic variable (habitat) remains stunning.

Global analysis of myocardial peptides containing cysteines with irreversible sulfinic and sulfonic acid post-translational modifications

Cysteine (Cys) oxidation is a crucial post-translational modification (PTM) associated with redox signaling and oxidative stress. As Cys is highly reactive to oxidants it forms a range of post-translational modifications, some that are biologically reversible (e.g. disulfides, Cys sulfenic acid) and others (Cys sulfinic [Cys-SO2H] and sulfonic [Cys-SO3H] acids) that are considered "irreversible." We developed an enrichment method to isolate Cys-SO2H/SO3H-containing peptides from complex tissue lysates that is compatible with tandem mass spectrometry (MS/MS). The acidity of these post-translational modification (pKa Cys-SO3H < 0) creates a unique charge distribution when localized on tryptic peptides at acidic pH that can be utilized for their purification. The method is based on electrostatic repulsion of Cys-SO2H/SO3H-containing peptides from cationic resins (i.e. "negative" selection) followed by "positive" selection using hydrophilic interaction liquid chromatography. Modification of strong cation exchange protocols decreased the complexity of initial flowthrough fractions by allowing for hydrophobic retention of neutral peptides. Coupling of strong cation exchange and hydrophilic interaction liquid chromatography allowed for increased enrichment of Cys-SO2H/SO3H (up to 80%) from other modified peptides. We identified 181 Cys-SO2H/SO3H sites from rat myocardial tissue subjected to physiologically relevant concentrations of H2O2 (<100 μm) or to ischemia/reperfusion (I/R) injury via Langendorff perfusion. I/R significantly increased Cys-SO2H/SO3H-modified peptides from proteins involved in energy utilization and contractility, as well as those involved in oxidative damage and repair.

Stoichiometric model and flux balance analysis for a mixed culture of Leptospirillum ferriphilum and Ferroplasma acidiphilum

The oxidation process of sulfide minerals in natural environments is achieved by microbial communities from the Archaea and Bacteria domains. A metabolic reconstruction of two dominant species, Leptospirillum ferriphilum and Ferroplasma acidiphilum, which are always found together as a mixed culture in this natural environments, was made. The metabolic model, composed of 152 internal reactions and 29 transport reactions, describes the main interactions between these species, assuming that both use ferrous iron as energy source, and F. acidiphilum takes advantage of the organic compounds secreted by L. ferriphilum for chemomixotrophic growth. A first metabolic model for a mixed culture used in bacterial leaching is proposed in this article, which pretends to represent the characteristics of the mixed culture in a simplified manner. It was evaluated with experimental data through flux balance analysis (FBA) using as objective function the maximization of biomass. The growth yields on ferrous iron obtained for each microorganism are consistent with experimental data, and the flux distribution obtained allows understanding of the metabolic capabilities of both microorganisms growing together in a bioleaching process. The model was used to simulate the growth of F. acidiphilum on different substrates, to determine in silico which compounds maximize cell growth, and which are essential. Knockout simulations were carried out for L. ferriphilum and F. acidiphilum metabolic models, predicting key enzymes of central metabolism. The results of this analysis are consistent with experimental data from literature, showing a robust behavior of the metabolic model.

The fundamental tradeoff in genomes and proteomes of prokaryotes established by the genetic code, codon entropy, and physics of nucleic acids and proteins

Background

Mutations in nucleotide sequences provide a foundation for genetic variability, and selection is the driving force of the evolution and molecular adaptation. Despite considerable progress in the understanding of selective forces and their compositional determinants, the very nature of underlying mutational biases remains unclear.

Results

We explore here a fundamental tradeoff, which analytically describes mutual adjustment of the nucleotide and amino acid compositions and its possible effect on the mutational biases. The tradeoff is determined by the interplay between the genetic code, optimization of the codon entropy, and demands on the structure and stability of nucleic acids and proteins.

Conclusion

The tradeoff is the unifying property of all prokaryotes regardless of the differences in their phylogenies, life styles, and extreme environments. It underlies mutational biases characteristic for genomes with different nucleotide and amino acid compositions, providing foundation for evolution and adaptation.

Reviewers

This article was reviewed by Eugene Koonin, Michael Gromiha, and Alexander Schleiffer.

Electronic supplementary material

The online version of this article (doi:10.1186/s13062-014-0029-2) contains supplementary material, which is available to authorized users.

Structural basis of redox-dependent modulation of galectin-1 dynamics and function

Galectin-1 (Gal-1), a member of a family of multifunctional lectins, plays key roles in diverse biological processes including cell signaling, immunomodulation, neuroprotection and angiogenesis. The presence of an unusual number of six cysteine residues within Gal-1 sequence prompted a detailed analysis of the impact of the redox environment on the functional activity of this lectin. We examined the role of each cysteine residue in the structure and function of Gal-1 using both experimental and computational approaches. Our results show that: (i) only three cysteine residues present in each carbohydrate recognition domain (CRD) (Cys2, Cys16 and Cys88) were important in protein oxidation, (ii) oxidation promoted the formation of the Cys16-Cys88 disulfide bond, as well as multimers through Cys2, (iii) the oxidized protein did not bind to lactose, probably due to poor interactions with Arg48 and Glu71, (iv) in vitro oxidation by air was completely reversible and (v) oxidation by hydrogen peroxide was relatively slow (1.7 ± 0.2 M(-1) s(-1) at pH 7.4 and 25°C). Finally, an analysis of key cysteines in other human galectins is also provided in order to predict their behaviour in response to redox variations. Collectively, our data provide new insights into the structural basis of Gal-1 redox regulation with critical implications in physiology and pathology.

A competitive chemical-proteomic platform to identify zinc-binding cysteines

Zinc ions (Zn(2+)) play vital catalytic, structural, and regulatory roles in protein function and are commonly chelated to cysteine residues within the protein framework. Current methods to identify Zn(2+)-binding cysteines rely on computational studies based on known Zn(2+)-chelating motifs, as well as high-resolution structural data. These available approaches preclude the global identification of putative Zn(2+)-chelating cysteines, particularly on poorly characterized proteins in the proteome. Herein, we describe an experimental platform that identifies metal-binding cysteines on the basis of their reduced nucleophilicity upon treatment with metal ions. As validation of our platform, we utilize a peptide-based cysteine-reactive probe to show that the known Zn(2+)-chelating cysteine in sorbitol dehydrogenase (SORD) demonstrates an expected loss in nucleophilicity in the presence of Zn(2+) ions and a gain in nucleophilicity upon treatment with a Zn(2+) chelator. We also identified the active-site cysteine in glutathione S-transferase omega-1 (GSTO1) as a potential Zn(2+)-chelation site, albeit with lower metal affinity relative to SORD. Treatment of recombinant GSTO1 with Zn(2+) ions results in a dose-dependent decrease in GSTO1 activity. Furthermore, we apply a promiscuous cysteine-reactive probe to globally identify putative Zn(2+)-binding cysteines across ∼900 cysteines in the human proteome. This proteomic study identified several well-characterized Zn(2+)-binding proteins, as well as numerous uncharacterized proteins from functionally distinct classes. This platform is highly versatile and provides an experimental tool that complements existing computational and structural methods to identify metal-binding cysteine residues.

Puzzling over protein cysteine phosphorylation – assessment of proteomic tools for S-phosphorylation profiling

The article provides useful information necessary for designing experiments in the emerging cysteine phosphoproteomics.

Catch me if you can: challenges and applications of cross-linking approaches

Biomolecular complexes are the groundwork of life and the basis for cell signaling, energy transfer, motion, stability and cellular metabolism. Understanding the underlying complex interactions on the molecular level is an essential step to obtain a comprehensive insight into cellular and systems biology. For the investigation of molecular interactions, various methods, including Förster resonance energy transfer, nuclear magnetic resonance spectroscopy, X-ray crystallography and yeast two-hybrid screening, can be utilized. Nevertheless, the most reliable approach for structural proteomics and the identification of novel protein-binding partners is chemical cross-linking. The rationale is that upon forming a covalent bond between a protein and its interaction partner (protein, lipid, RNA/DNA, carbohydrate) the native complex state is "frozen" and accessible for detailed mass spectrometric analysis. In this review we provide a synopsis on crosslinker design, chemistry, pitfalls, limitations and novel applications in the field, and feature an overview of current software applications.

Molecular mechanisms of adaptation emerging from the physics and evolution of nucleic acids and proteins

DNA, RNA and proteins are major biological macromolecules that coevolve and adapt to environments as components of one highly interconnected system. We explore here sequence/structure determinants of mechanisms of adaptation of these molecules, links between them, and results of their mutual evolution. We complemented statistical analysis of genomic and proteomic sequences with folding simulations of RNA molecules, unraveling causal relations between compositional and sequence biases reflecting molecular adaptation on DNA, RNA and protein levels. We found many compositional peculiarities related to environmental adaptation and the life style. Specifically, thermal adaptation of protein-coding sequences in Archaea is characterized by a stronger codon bias than in Bacteria. Guanine and cytosine load in the third codon position is important for supporting the aerobic life style, and it is highly pronounced in Bacteria. The third codon position also provides a tradeoff between arginine and lysine, which are favorable for thermal adaptation and aerobicity, respectively. Dinucleotide composition provides stability of nucleic acids via strong base-stacking in ApG dinucleotides. In relation to coevolution of nucleic acids and proteins, thermostability-related demands on the amino acid composition affect the nucleotide content in the second codon position in Archaea.

Systematic analysis of compositional order of proteins reveals new characteristics of biological functions and a universal correlate of macroevolution

We present a novel analysis of compositional order (CO) based on the occurrence of Frequent amino-acid Triplets (FTs) that appear much more than random in protein sequences. The method captures all types of proteomic compositional order including single amino-acid runs, tandem repeats, periodic structure of motifs and otherwise low complexity amino-acid regions. We introduce new order measures, distinguishing between ‘regularity’, ‘periodicity’ and ‘vocabulary’, to quantify these phenomena and to facilitate the identification of evolutionary effects. Detailed analysis of representative species across the tree-of-life demonstrates that CO proteins exhibit numerous functional enrichments, including a wide repertoire of particular patterns of dependencies on regularity and periodicity. Comparison between human and mouse proteomes further reveals the interplay of CO with evolutionary trends, such as faster substitution rate in mouse leading to decrease of periodicity, while innovation along the human lineage leads to larger regularity. Large-scale analysis of 94 proteomes leads to systematic ordering of all major taxonomic groups according to FT-vocabulary size. This is measured by the count of Different Frequent Triplets (DFT) in proteomes. The latter provides a clear hierarchical delineation of vertebrates, invertebrates, plants, fungi and prokaryotes, with thermophiles showing the lowest level of FT-vocabulary. Among eukaryotes, this ordering correlates with phylogenetic proximity. Interestingly, in all kingdoms CO accumulation in the proteome has universal characteristics. We suggest that CO is a genomic-information correlate of both macroevolution and various protein functions. The results indicate a mechanism of genomic ‘innovation’ at the peptide level, involved in protein elongation, shaped in a universal manner by mutational and selective forces.

Variations in compositionally ordered (CO) sections of proteins, such as amino acid runs, tandem repeats and low complexity regions, are often considered as a third type of genomic variation along with SNP and CNV. At the microevolutionary scale, they are involved in the rapid evolution of numerous biological functions and the development of novel phenotypic complex traits, including disease in human, in particular neurodegeneration and cancer. At the macroevolutionary scale, the best discriminating proteomic factor between super-kingdoms is the prevalence of CO proteins in eukaryotes. The analysis of CO structures has so far been quite eclectic. Here we introduce a novel unifying methodology, accounting for all types of low-complexity regions and repetitive phenomena, including the existence of large periodic structures in protein sequences. We define new CO measures providing insights into the correlation of CO with protein function and with evolution. In particular, a large-scale analysis of 94 proteomes shows that the CO vocabulary of frequently appearing amino acid triplets serves as a measure of taxonomic ordering separating major clades from each other. It unravels a missing genomic correlate of macroevolution and serves as a novel phylogenetic tool. This suggests that major CO generation occurs during the creation of a completely new species, i.e. during macroevolutionary events.

Evolution of complete proteomes: guanine-cytosine pressure, phylogeny and environmental influences blend the proteomic architecture

Background

Guanine-cytosine (GC) composition is an important feature of genomes. Likewise, amino acid composition is a distinct, but less valued, feature of proteomes. A major concern is that it is not clear what valuable information can be acquired from amino acid composition data. To address this concern, in-depth analyses of the amino acid composition of the complete proteomes from 63 archaea, 270 bacteria, and 128 eukaryotes were performed.

Results

Principal component analysis of the amino acid matrices showed that the main contributors to proteomic architecture were genomic GC variation, phylogeny, and environmental influences. GC pressure drove positive selection on Ala, Arg, Gly, Pro, Trp, and Val, and adverse selection on Asn, Lys, Ile, Phe, and Tyr. The physico-chemical framework of the complete proteomes withstood GC pressure by frequency complementation of GC-dependent amino acid pairs with similar physico-chemical properties. Gln, His, Ser, and Val were responsible for phylogeny and their constituted components could differentiate archaea, bacteria, and eukaryotes. Environmental niche was also a significant factor in determining proteomic architecture, especially for archaea for which the main amino acids were Cys, Leu, and Thr. In archaea, hyperthermophiles, acidophiles, mesophiles, psychrophiles, and halophiles gathered successively along the environment-based principal component. Concordance between proteomic architecture and the genetic code was also related closely to genomic GC content, phylogeny, and lifestyles.

Conclusions

Large-scale analyses of the complete proteomes of a wide range of organisms suggested that amino acid composition retained the trace of GC variation, phylogeny, and environmental influences during evolution. The findings from this study will help in the development of a global understanding of proteome evolution, and even biological evolution.

Quantifying Changes in the Cellular Thiol-Disulfide Status during Differentiation of B Cells into Antibody-Secreting Plasma Cells

Plasma cells produce and secrete massive amounts of disulfide-containing antibodies. To accommodate this load on the secretory machinery, the differentiation of resting B cells into antibody-secreting plasma cells is accompanied by a preferential expansion of the secretory compartments of the cells and by an up-regulation of enzymes involved in redox regulation and protein folding. We have quantified the absolute levels of protein thiols, protein disulfides, and glutathionylated proteins in whole cells. The results show that while the global thiol-disulfide state is affected to some extent by the differentiation, steady-state levels of glutathionylated protein thiols are less than 0.3% of the total protein cysteines, even in fully differentiated cells, and the overall protein redox state is not affected until late in differentiation, when large-scale IgM production is ongoing. A general expansion of the ER does not affect global protein redox status until an extensive production of cargo proteins has started.

Sulfenic acid chemistry, detection and cellular lifetime

BACKGROUND

Reactive oxygen species-mediated cysteine sulfenic acid modification has emerged as an important regulatory mechanism in cell signaling. The stability of sulfenic acid in proteins is dictated by the local microenvironment and ability of antioxidants to reduce this modification. Several techniques for detecting this cysteine modification have been developed, including direct and in situ methods.

SCOPE OF REVIEW

This review presents a historical discussion of sulfenic acid chemistry and highlights key examples of this modification in proteins. A comprehensive survey of available detection techniques with advantages and limitations is discussed. Finally, issues pertaining to rates of sulfenic acid formation, reduction, and chemical trapping methods are also covered.

MAJOR CONCLUSIONS

Early chemical models of sulfenic acid yielded important insights into the unique reactivity of this species. Subsequent pioneering studies led to the characterization of sulfenic acid formation in proteins. In parallel, the discovery of oxidant-mediated cell signaling pathways and pathological oxidative stress has led to significant interest in methods to detect these modifications. Advanced methods allow for direct chemical trapping of protein sulfenic acids directly in cells and tissues. At the same time, many sulfenic acids are short-lived and the reactivity of current probes must be improved to sample these species, while at the same time, preserving their chemical selectivity. Inhibitors with binding scaffolds can be rationally designed to target sulfenic acid modifications in specific proteins.

GENERAL SIGNIFICANCE

Ever increasing roles for protein sulfenic acids have been uncovered in physiology and pathology. A more complete understanding of sulfenic acid-mediated regulatory mechanisms will continue to require rigorous and new chemical insights. This article is part of a Special Issue entitled Current methods to study reactive oxygen species - pros and cons and biophysics of membrane proteins. Guest Editor: Christine Winterbourn.

Versatile probes for the selective detection of vicinal-dithiol-containing proteins: design, synthesis, and application in living cells

Endogenous vicinal-dithiol-containing proteins (VDPs) that have two thiol groups close to each other in space play a significant importance in maintaining the cellular redox microenvironment. Approaches to identify VDPs mainly rely on monitoring the different concentration of monothiol and total thiol groups or on indirect labeling of vicinal thiols by using p-aminophenylarsenoxide (PAO). Our previous work has reported the direct labeling of VDPs with a highly selective receptor PAO analogue, which could realize fluorescence detection of VDPs directly in living cells. Herein, we developed a conjugated approach to expand detectable tags to nitrobenzoxadiazole (NBD), fluorescein, naphthalimide, and biotin for the synthesis of a series of probes. Different linkers have also been introduced toward conjugation of VTA2 with these functional tags. These synthesized flexible probes with various features will offer new tools for the potential identification and visualization of vicinal dithiols existing in different regions of VDPs in living cells. These probes are convenient tools for proteomics studies of various disease-related VDPs and for the discovery of new drug targets.

A frequency-based linguistic approach to protein decoding and design: Simple concepts, diverse applications, and the SCS Package

Protein structure and function information is coded in amino acid sequences. However, the relationship between primary sequences and three-dimensional structures and functions remains enigmatic. Our approach to this fundamental biochemistry problem is based on the frequencies of short constituent sequences (SCSs) or words. A protein amino acid sequence is considered analogous to an English sentence, where SCSs are equivalent to words. Availability scores, which are defined as real SCS frequencies in the non-redundant amino acid database relative to their probabilistically expected frequencies, demonstrate the biological usage bias of SCSs. As a result, this frequency-based linguistic approach is expected to have diverse applications, such as secondary structure specifications by structure-specific SCSs and immunological adjuvants with rare or non-existent SCSs. Linguistic similarities (e.g., wide ranges of scale-free distributions) and dissimilarities (e.g., behaviors of low-rank samples) between proteins and the natural English language have been revealed in the rank-frequency relationships of SCSs or words. We have developed a web server, the SCS Package, which contains five applications for analyzing protein sequences based on the linguistic concept. These tools have the potential to assist researchers in deciphering structurally and functionally important protein sites, species-specific sequences, and functional relationships between SCSs. The SCS Package also provides researchers with a tool to construct amino acid sequences de novo based on the idiomatic usage of SCSs.

Diverse functional roles of reactive cysteines

Cysteine residues on proteins play key roles in catalysis and regulation. These functional cysteines serve as active sites for nucleophilic and redox catalysis, sites of allosteric regulation, and metal-binding ligands on proteins from diverse classes including proteases, kinases, metabolic enzymes, and transcription factors. In this review, we focus on a few select examples that serve to highlight the multiple functions performed by cysteines, with an emphasis on cysteine-mediated protein activities implicated in cancer. The enhanced reactivity of functional cysteines renders them susceptible to modification by electrophilic species. Toward this end, we discuss recent advancements and future prospects for utilizing cysteine-reactive small molecules as drugs and imaging agents for the treatment and diagnosis of cancer.