Atypical structural tendencies among low-complexity domains in the Protein Data Bank proteome

Intrinsic disorder and salt-dependent conformational changes of the N-terminal region of TFIP11 splicing factor

Tuftelin Interacting Protein 11 (TFIP11) was identified as a critical human spliceosome assembly regulator, interacting with multiple proteins and localising in membrane-less organelles. However, a lack of structural information on TFIP11 limits the rationalisation of its biological role. TFIP11 is predicted as an intrinsically disordered protein (IDP), and more specifically concerning its N-terminal (N-TER) region. IDPs lack a defined tertiary structure, existing as a dynamic conformational ensemble, favouring protein-protein and protein-RNA interactions. IDPs are involved in liquid-liquid phase separation (LLPS), driving the formation of subnuclear compartments. Combining disorder prediction, molecular dynamics, and spectroscopy methods, this contribution shows the first evidence TFIP11 N-TER is a polyampholytic IDP, exhibiting a structural duality with the coexistence of ordered and disordered assemblies, depending on the ionic strength. Increasing the salt concentration enhances the protein conformational flexibility, presenting a more globule-like shape, and a fuzzier unstructured arrangement that could favour LLPS and protein-RNA interaction. The most charged and hydrophilic regions are the most impacted, including the G-Patch domain essential to TFIP11 function. This study gives a better understanding of the salt-dependent conformational behaviour of the N-TER TFIP11, supporting the hypothesis of the formation of different types of protein assembly, in line with its multiple biological roles.

One Step Closer to the Understanding of the Relationship IDR-LCR-Structure

Intrinsically disordered regions (IDRs) in protein sequences are emerging as functionally important elements for interaction and regulation. While being generally flexible, we previously showed, by observation of experimentally obtained structures, that they contain regions of reduced sequence complexity that have an increased propensity to form structure. Here we expand the universe of cases taking advantage of structural predictions by AlphaFold. Our studies focus on low complexity regions (LCRs) found within IDRs, where these LCRs have only one or two residue types (polyX and polyXY, respectively). In addition to confirming previous observations that polyE and polyEK have a tendency towards helical structure, we find a similar tendency for other LCRs such as polyQ and polyER, most of them including charged residues. We analyzed the position of polyXY containing IDRs within proteins, which allowed us to show that polyAG and polyAK accumulate at the N-terminal, with the latter showing increased helical propensity at that location. Functional enrichment analysis of polyXY with helical propensity indicated functions requiring interaction with RNA and DNA. Our work adds evidence of the function of LCRs in interaction-dependent structuring of disordered regions, encouraging the development of tools for the prediction of their dynamic structural properties.

Low complexity domains of the nucleocapsid protein of SARS-CoV-2 form amyloid fibrils

The self-assembly of the Nucleocapsid protein (NCAP) of SARS-CoV-2 is crucial for its function. Computational analysis of the amino acid sequence of NCAP reveals low-complexity domains (LCDs) akin to LCDs in other proteins known to self-assemble as phase separation droplets and amyloid fibrils. Previous reports have described NCAP's propensity to phase-separate. Here we show that the central LCD of NCAP is capable of both, phase separation and amyloid formation. Within this central LCD we identified three adhesive segments and determined the atomic structure of the fibrils formed by each. Those structures guided the design of G12, a peptide that interferes with the self-assembly of NCAP and demonstrates antiviral activity in SARS-CoV-2 infected cells. Our work, therefore, demonstrates the amyloid form of the central LCD of NCAP and suggests that amyloidogenic segments of NCAP could be targeted for drug development.

Light, Water, and Melatonin: The Synergistic Regulation of Phase Separation in Dementia

The swift rise in acceptance of molecular principles defining phase separation by a broad array of scientific disciplines is shadowed by increasing discoveries linking phase separation to pathological aggregations associated with numerous neurodegenerative disorders, including Alzheimer’s disease, that contribute to dementia. Phase separation is powered by multivalent macromolecular interactions. Importantly, the release of water molecules from protein hydration shells into bulk creates entropic gains that promote phase separation and the subsequent generation of insoluble cytotoxic aggregates that drive healthy brain cells into diseased states. Higher viscosity in interfacial waters and limited hydration in interiors of biomolecular condensates facilitate phase separation. Light, water, and melatonin constitute an ancient synergy that ensures adequate protein hydration to prevent aberrant phase separation. The 670 nm visible red wavelength found in sunlight and employed in photobiomodulation reduces interfacial and mitochondrial matrix viscosity to enhance ATP production via increasing ATP synthase motor efficiency. Melatonin is a potent antioxidant that lowers viscosity to increase ATP by scavenging excess reactive oxygen species and free radicals. Reduced viscosity by light and melatonin elevates the availability of free water molecules that allow melatonin to adopt favorable conformations that enhance intrinsic features, including binding interactions with adenosine that reinforces the adenosine moiety effect of ATP responsible for preventing water removal that causes hydrophobic collapse and aggregation in phase separation. Precise recalibration of interspecies melatonin dosages that account for differences in metabolic rates and bioavailability will ensure the efficacious reinstatement of the once-powerful ancient synergy between light, water, and melatonin in a modern world.

Guide to studying intrinsically disordered proteins by high-speed atomic force microscopy

Intrinsically disordered proteins (IDPs) are partially or entirely disordered. Their intrinsically disordered regions (IDRs) dynamically explore a wide range of structural space by their highly flexible nature. Due to this distinct feature largely different from structured proteins, conventional structural analyses relying on ensemble averaging is unsuitable for characterizing the dynamic structure of IDPs. Therefore, single-molecule measurement tools have been desired in IDP studies. High-speed atomic force microscopy (HS-AFM) is a unique tool that allows us to directly visualize single biomolecules at 2-3 nm lateral and ∼ 0.1 nm vertical spatial resolution, and at sub-100 ms temporal resolution under near physiological conditions, without any chemical labeling. HS-AFM has been successfully used not only to characterize the shape and motion of IDP molecules but also to visualize their function-related dynamics. In this article, after reviewing the principle and current performances of HS-AFM, we describe experimental considerations in the HS-AFM imaging of IDPs and methods to quantify molecular features from captured images. Finally, we outline recent HS-AFM imaging studies of IDPs.

Repair Foci as Liquid Phase Separation: Evidence and Limitations

In response to DNA double strand breaks (DSB), repair proteins accumulate at damaged sites, forming membrane-less condensates or "foci". The formation of these foci and their disassembly within the proper time window are essential for genome integrity. However, how these membrane-less sub-compartments are formed, maintained and disassembled remains unclear. Recently, several studies across different model organisms proposed that DNA repair foci form via liquid phase separation. In this review, we discuss the current research investigating the physical nature of repair foci. First, we present the different models of condensates proposed in the literature, highlighting the criteria to differentiate them. Second, we discuss evidence of liquid phase separation at DNA repair sites and the limitations of this model to fully describe structures formed in response to DNA damage. Finally, we discuss the origin and possible function of liquid phase separation for DNA repair processes.

Expansion and functional analysis of the SR-related protein family across the domains of life

Serine/arginine-rich (SR) proteins comprise a family of proteins that is predominantly found in eukaryotes and plays a prominent role in RNA splicing. A characteristic feature of SR proteins is the presence of an S/R-rich low-complexity domain (RS domain), often in conjunction with spatially distinct RNA recognition motifs (RRMs). To date, 52 human proteins have been classified as SR or SR-related proteins. Here, using an unbiased series of composition criteria together with enrichment for known RNA binding activity, we identified >100 putative SR-related proteins in the human proteome. This method recovers known SR and SR-related proteins with high sensitivity (∼94%), yet identifies a number of additional proteins with many of the hallmark features of true SR-related proteins. Newly identified SR-related proteins display slightly different amino acid compositions yet similar levels of post-translational modification, suggesting that these new SR-related candidates are regulated in vivo and functionally important. Furthermore, candidate SR-related proteins with known RNA-binding activity (but not currently recognized as SR-related proteins) are nevertheless strongly associated with a variety of functions related to mRNA splicing and nuclear speckles. Finally, we applied our SR search method to all available reference proteomes, and provide maps of RS domains and Pfam annotations for all putative SR-related proteins as a resource. Together, these results expand the set of SR-related proteins in humans, and identify the most common functions associated with SR-related proteins across all domains of life.

Transcription factors perform a 2-step search of the nucleus

Transcription factors regulate gene expression by binding to regulatory DNA and recruiting regulatory protein complexes. The DNA-binding and protein-binding functions of transcription factors are traditionally described as independent functions performed by modular protein domains. Here, I argue that genome binding can be a 2-part process with both DNA-binding and protein-binding steps, enabling transcription factors to perform a 2-step search of the nucleus to find their appropriate binding sites in a eukaryotic genome. I support this hypothesis with new and old results in the literature, discuss how this hypothesis parsimoniously resolves outstanding problems, and present testable predictions.

Insights from analyses of low complexity regions with canonical methods for protein sequence comparison

Low complexity regions are fragments of protein sequences composed of only a few types of amino acids. These regions frequently occur in proteins and can play an important role in their functions. However, scientists are mainly focused on regions characterized by high diversity of amino acid composition. Similarity between regions of protein sequences frequently reflect functional similarity between them. In this article, we discuss strengths and weaknesses of the similarity analysis of low complexity regions using BLAST, HHblits and CD-HIT. These methods are considered to be the gold standard in protein similarity analysis and were designed for comparison of high complexity regions. However, we lack specialized methods that could be used to compare the similarity of low complexity regions. Therefore, we investigated the existing methods in order to understand how they can be applied to compare such regions. Our results are supported by exploratory study, discussion of amino acid composition and biological roles of selected examples. We show that existing methods need improvements to efficiently search for similar low complexity regions. We suggest features that have to be re-designed specifically for comparing low complexity regions: scoring matrix, multiple sequence alignment, e-value, local alignment and clustering based on a set of representative sequences. Results of this analysis can either be used to improve existing methods or to create new methods for the similarity analysis of low complexity regions.

Low Complexity Induces Structure in Protein Regions Predicted as Intrinsically Disordered

There is increasing evidence that many intrinsically disordered regions (IDRs) in proteins play key functional roles through interactions with other proteins or nucleic acids. These interactions often exhibit a context-dependent structural behavior. We hypothesize that low complexity regions (LCRs), often found within IDRs, could have a role in inducing local structure in IDRs. To test this, we predicted IDRs in the human proteome and analyzed their structures or those of homologous sequences in the Protein Data Bank (PDB). We then identified two types of simple LCRs within IDRs: regions with only one (polyX or homorepeats) or with only two types of amino acids (polyXY). We were able to assign structural information from the PDB more often to these LCRs than to the surrounding IDRs (polyX 61.8% > polyXY 50.5% > IDRs 39.7%). The most frequently observed polyX and polyXY within IDRs contained E (Glu) or G (Gly). Structural analyses of these sequences and of homologs indicate that polyEK regions induce helical conformations, while the other most frequent LCRs induce coil structures. Our work proposes bioinformatics methods to help in the study of the structural behavior of IDRs and provides a solid basis suggesting a structuring role of LCRs within them.

Binary Matrix Method to Enumerate, Hierarchically Order, and Structurally Classify Peptide Aggregation

Protein aggregation is a common and complex phenomenon in biological processes, yet a robust analysis of this aggregation process remains elusive. The commonly used methods such as center-of-mass to center-of-mass (COM-COM) distance, the radius of gyration (R_g), hydrogen bonding (HB), and solvent accessible surface area do not quantify the aggregation accurately. Herein, a new and robust method that uses an aggregation matrix (AM) approach to investigate peptide aggregation in a MD simulation trajectory is presented. An nxn two-dimensional AM is created by using the interpeptide C_α-C_α cutoff distances, which are binarily encoded (0 or 1). These aggregation matrices are analyzed to enumerate, hierarchically order, and structurally classify the aggregates. Comparison of the present AM method suggests that it is superior to the HB method since it can incorporate nonspecific interactions and the R_g and COM-COM methods since the cutoff distance is independent of the length of the peptide. More importantly, the present method can structurally classify the peptide aggregates, which the conventional R_g, COM-COM, and HB methods fail to do. The unique selling point of this method is its ability to structurally classify peptide aggregates using two-dimensional matrices.

Deciphering how naturally occurring sequence features impact the phase behaviours of disordered prion-like domains

Prion-like low-complexity domains (PLCDs) have distinctive sequence grammars that determine their driving forces for phase separation. Here we uncover the physicochemical underpinnings of how evolutionarily conserved compositional biases influence the phase behaviour of PLCDs. We interpret our results in the context of the stickers-and-spacers model for the phase separation of associative polymers. We find that tyrosine is a stronger sticker than phenylalanine, whereas arginine is a context-dependent auxiliary sticker. In contrast, lysine weakens sticker-sticker interactions. Increasing the net charge per residue destabilizes phase separation while also weakening the strong coupling between single-chain contraction in dilute phases and multichain interactions that give rise to phase separation. Finally, glycine and serine residues act as non-equivalent spacers, and thus make the glycine versus serine contents an important determinant of the driving forces for phase separation. The totality of our results leads to a set of rules that enable comparative estimates of composition-specific driving forces for PLCD phase separation.

Deciphering how naturally occurring sequence features impact the phase behaviours of disordered prion-like domains

Prion-like low-complexity domains (PLCDs) have distinctive sequence grammars that determine their driving forces for phase separation. Here we uncover the physicochemical underpinnings of how evolutionarily conserved compositional biases influence the phase behaviour of PLCDs. We interpret our results in the context of the stickers-and-spacers model for the phase separation of associative polymers. We find that tyrosine is a stronger sticker than phenylalanine, whereas arginine is a context-dependent auxiliary sticker. In contrast, lysine weakens sticker-sticker interactions. Increasing the net charge per residue destabilizes phase separation while also weakening the strong coupling between single-chain contraction in dilute phases and multichain interactions that give rise to phase separation. Finally, glycine and serine residues act as non-equivalent spacers, and thus make the glycine versus serine contents an important determinant of the driving forces for phase separation. The totality of our results leads to a set of rules that enable comparative estimates of composition-specific driving forces for PLCD phase separation.

Visualization of intrinsically disordered proteins by high-speed atomic force microscopy

High-speed atomic force microscopy (HS-AFM) is a powerful tool established 13 years ago. This methodology can capture individual protein molecules carrying out functional activities under near-physiological conditions, without chemical labeling, at 2-3 nm lateral and ∼0.1 nm vertical spatial resolution, and at sub-100 ms temporal resolution. Although most biological HS-AFM studies thus far target structured proteins, HS-AFM is also ideally suited to study the dynamics of intrinsically disordered proteins. Here we review some of the dynamic structures and processes of intrinsically disordered proteins that have been unveiled by HS-AFM imaging.

Karyopherin abnormalities in neurodegenerative proteinopathies

Neurodegenerative proteinopathies are characterized by progressive cell loss that is preceded by the mislocalization and aberrant accumulation of proteins prone to aggregation. Despite their different physiological functions, disease-related proteins like tau, α-synuclein, TAR DNA binding protein-43, fused in sarcoma and mutant huntingtin, all share low complexity regions that can mediate their liquid-liquid phase transitions. The proteins' phase transitions can range from native monomers to soluble oligomers, liquid droplets and further to irreversible, often-mislocalized aggregates that characterize the stages and severity of neurodegenerative diseases. Recent advances into the underlying pathogenic mechanisms have associated mislocalization and aberrant accumulation of disease-related proteins with defective nucleocytoplasmic transport and its mediators called karyopherins. These studies identify karyopherin abnormalities in amyotrophic lateral sclerosis, frontotemporal dementia, Alzheimer's disease, and synucleinopathies including Parkinson's disease and dementia with Lewy bodies, that range from altered expression levels to the subcellular mislocalization and aggregation of karyopherin α and β proteins. The reported findings reveal that in addition to their classical function in nuclear import and export, karyopherins can also act as chaperones by shielding aggregation-prone proteins against misfolding, accumulation and irreversible phase-transition into insoluble aggregates. Karyopherin abnormalities can, therefore, be both the cause and consequence of protein mislocalization and aggregate formation in degenerative proteinopathies. The resulting vicious feedback cycle of karyopherin pathology and proteinopathy identifies karyopherin abnormalities as a common denominator of onset and progression of neurodegenerative disease. Pharmacological targeting of karyopherins, already in clinical trials as therapeutic intervention targeting cancers such as glioblastoma and viral infections like COVID-19, may therefore represent a promising new avenue for disease-modifying treatments in neurodegenerative proteinopathies.

Entropy and Fractal Dimension Study of the TDP-43 Protein Low Complexity Domain Sequence in ALS Disease Severity and SARS-CoV-2 Gene Sequences in Virulence Variability

The low complexity domain (LCD) sequence has been defined in terms of entropy using a 12 amino acid sliding window along a protein sequence in the study of disease-related genes. The amyotrophic lateral sclerosis (ALS)-related TDP-43 protein sequence with intra-LCD structural information based on cryo-EM data was published recently. An application of entropy and Higuchi fractal dimension calculations was described using the Znf521 and HAR1 sequences. A computational analysis of the intra-LCD sequence entropy and Higuchi fractal dimension values at the amino acid level and at the ATCG nucleotide level were conducted without the sliding window requirement. The computational results were consistent in predicting the intermediate entropy/fractal dimension value produced when two subsequences at two different entropy/fractal dimension values were combined. The computational method without the application of a sliding-window was extended to an analysis of the recently reported virulent genes—Orf6, Nsp6, and Orf7a—in SARS-CoV-2. The relationship between the virulence functionality and entropy values was found to have correlation coefficients between 0.84 and 0.99, using a 5% uncertainty on the cell viability data. The analysis found that the most virulent Orf6 gene sequence had the lowest nucleotide entropy and the highest protein fractal dimension, in line with extreme value theory. The Orf6 codon usage bias in relation to vaccine design was discussed.

The Different Faces of the TDP-43 Low-Complexity Domain: The Formation of Liquid Droplets and Amyloid Fibrils

Transactive response DNA-binding protein 43 (TDP-43) is a nucleic acid-binding protein that is involved in transcription and translation regulation, non-coding RNA processing, and stress granule assembly. Aside from its multiple functions, it is also known as the signature protein in the hallmark inclusions of amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) patients. TDP-43 is built of four domains, but its low-complexity domain (LCD) has become an intense research focus that brings to light its possible role in TDP-43 functions and involvement in the pathogenesis of these neurodegenerative diseases. Recent endeavors have further uncovered the distinct biophysical properties of TDP-43 under various circumstances. In this review, we summarize the multiple structural and biochemical properties of LCD in either promoting the liquid droplets or inducing fibrillar aggregates. We also revisit the roles of the LCD in paraspeckles, stress granules, and cytoplasmic inclusions to date.

Human tRNAs with inosine 34 are essential to efficiently translate eukarya-specific low-complexity proteins

The modification of adenosine to inosine at the wobble position (I34) of tRNA anticodons is an abundant and essential feature of eukaryotic tRNAs. The expansion of inosine-containing tRNAs in eukaryotes followed the transformation of the homodimeric bacterial enzyme TadA, which generates I34 in tRNAArg and tRNALeu, into the heterodimeric eukaryotic enzyme ADAT, which modifies up to eight different tRNAs. The emergence of ADAT and its larger set of substrates, strongly influenced the tRNA composition and codon usage of eukaryotic genomes. However, the selective advantages that drove the expansion of I34-tRNAs remain unknown. Here we investigate the functional relevance of I34-tRNAs in human cells and show that a full complement of these tRNAs is necessary for the translation of low-complexity protein domains enriched in amino acids cognate for I34-tRNAs. The coding sequences for these domains require codons translated by I34-tRNAs, in detriment of synonymous codons that use other tRNAs. I34-tRNA-dependent low-complexity proteins are enriched in functional categories related to cell adhesion, and depletion in I34-tRNAs leads to cellular phenotypes consistent with these roles. We show that the distribution of these low-complexity proteins mirrors the distribution of I34-tRNAs in the phylogenetic tree.

Biological Phase Separation and Biomolecular Condensates in Plants

A surge in research focused on understanding the physical principles governing the formation, properties, and function of membraneless compartments has occurred over the past decade. Compartments such as the nucleolus, stress granules, and nuclear speckles have been designated as biomolecular condensates to describe their shared property of spatially concentrating biomolecules. Although this research has historically been carried out in animal and fungal systems, recent work has begun to explore whether these same principles are relevant in plants. Effectively understanding and studying biomolecular condensates require interdisciplinary expertise that spans cell biology, biochemistry, and condensed matter physics and biophysics. As such, some involved concepts may be unfamiliar to any given individual. This review focuses on introducing concepts essential to the study of biomolecular condensates and phase separation for biologists seeking to carry out research in this area and further examines aspects of biomolecular condensates that are relevant to plant systems.

LCD-Composer: an intuitive, composition-centric method enabling the identification and detailed functional mapping of low-complexity domains

Low complexity domains (LCDs) in proteins are regions predominantly composed of a small subset of the possible amino acids. LCDs are involved in a variety of normal and pathological processes across all domains of life. Existing methods define LCDs using information-theoretical complexity thresholds, sequence alignment with repetitive regions, or statistical overrepresentation of amino acids relative to whole-proteome frequencies. While these methods have proven valuable, they are all indirectly quantifying amino acid composition, which is the fundamental and biologically-relevant feature related to protein sequence complexity. Here, we present a new computational tool, LCD-Composer, that directly identifies LCDs based on amino acid composition and linear amino acid dispersion. Using LCD-Composer's default parameters, we identified simple LCDs across all organisms available through UniProt and provide the resulting data in an accessible form as a resource. Furthermore, we describe large-scale differences between organisms from different domains of life and explore organisms with extreme LCD content for different LCD classes. Finally, we illustrate the versatility and specificity achievable with LCD-Composer by identifying diverse classes of LCDs using both simple and multifaceted composition criteria. We demonstrate that the ability to dissect LCDs based on these multifaceted criteria enhances the functional mapping and classification of LCDs.

Get closer and make hotspots: liquid-liquid phase separation in plants

Liquid-liquid phase separation (LLPS) facilitates the formation of membraneless compartments in a cell and allows the spatiotemporal organization of biochemical reactions by concentrating macromolecules locally. In plants, LLPS defines cellular reaction hotspots, and stimulus-responsive LLPS is tightly linked to a variety of cellular and biological functions triggered by exposure to various internal and external stimuli, such as stress responses, hormone signaling, and temperature sensing. Here, we provide an overview of the current understanding of physicochemical forces and molecular factors that drive LLPS in plant cells. We illustrate how the biochemical features of cellular condensates contribute to their biological functions. Additionally, we highlight major challenges for the comprehensive understanding of biological LLPS, especially in view of the dynamic and robust organization of biochemical reactions underlying plastic responses to environmental fluctuations in plants.

Regulation of SETD2 stability is important for the fidelity of H3K36me3 deposition

Background

The histone H3K36me3 mark regulates transcription elongation, pre-mRNA splicing, DNA methylation, and DNA damage repair. However, knowledge of the regulation of the enzyme SETD2, which deposits this functionally important mark, is very limited.

Results

Here, we show that the poorly characterized N-terminal region of SETD2 plays a determining role in regulating the stability of SETD2. This stretch of 1–1403 amino acids contributes to the robust degradation of SETD2 by the proteasome. Besides, the SETD2 protein is aggregate prone and forms insoluble bodies in nuclei especially upon proteasome inhibition. Removal of the N-terminal segment results in the stabilization of SETD2 and leads to a marked increase in global H3K36me3 which, uncharacteristically, happens in a Pol II-independent manner.

Conclusion

The functionally uncharacterized N-terminal segment of SETD2 regulates its half-life to maintain the requisite cellular amount of the protein. The absence of SETD2 proteolysis results in a Pol II-independent H3K36me3 deposition and protein aggregation.

A proposed role for the SARS-CoV-2 nucleocapsid protein in the formation and regulation of biomolecular condensates

To date, the recently discovered SARS-CoV-2 virus has afflicted >6.9 million people worldwide and disrupted the global economy. Development of effective vaccines or treatments for SARS-CoV-2 infection will be aided by a molecular-level understanding of SARS-CoV-2 proteins and their interactions with host cell proteins. The SARS-CoV-2 nucleocapsid (N) protein is highly homologous to the N protein of SARS-CoV, which is essential for viral RNA replication and packaging into new virions. Emerging models indicate that nucleocapsid proteins of other viruses can form biomolecular condensates to spatiotemporally regulate N protein localization and function. Our bioinformatic analyses, in combination with pre-existing experimental evidence, suggest that the SARS-CoV-2 N protein is capable of forming or regulating biomolecular condensates in vivo by interaction with RNA and key host cell proteins. We discuss multiple models, whereby the N protein of SARS-CoV-2 may harness this activity to regulate viral life cycle and host cell response to viral infection.