MloDisDB: a manually curated database of the relations between membraneless organelles and diseases

Bioinformatic approaches of liquid-liquid phase separation in human disease

ABSTRACT

Biomolecular aggregation within cellular environments via liquid-liquid phase separation (LLPS) spontaneously forms droplet-like structures, which play pivotal roles in diverse biological processes. These structures are closely associated with a range of diseases, including neurodegenerative disorders, cancer and infectious diseases, highlighting the significance of understanding LLPS mechanisms for elucidating disease pathogenesis, and exploring potential therapeutic interventions. In this review, we delineate recent advancements in LLPS research, emphasizing its pathological relevance, therapeutic considerations, and the pivotal role of bioinformatic tools and databases in facilitating LLPS investigations. Additionally, we undertook a comprehensive analysis of bioinformatic resources dedicated to LLPS research in order to elucidate their functionality and applicability. By providing comprehensive insights into current LLPS-related bioinformatics resources, this review highlights its implications for human health and disease.

Advanced computational approaches to understand protein aggregation

Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.

Innate immunity of vascular smooth muscle cells contributes to two-wave inflammation in atherosclerosis, twin-peak inflammation in aortic aneurysms and trans-differentiation potential into 25 cell types

Introduction

Vascular smooth muscle cells (VSMCs) are the predominant cell type in the medial layer of the aorta, which plays a critical role in aortic diseases. Innate immunity is the main driving force for cardiovascular diseases.

Methods

To determine the roles of innate immunity in VSMC and aortic pathologies, we performed transcriptome analyses on aortas from ApoE-/- angiotensin II (Ang II)-induced aortic aneurysm (AAA) time course, and ApoE-/- atherosclerosis time course, as well as VSMCs stimulated with danger-associated molecular patterns (DAMPs).

Results

We made significant findings: 1) 95% and 45% of the upregulated innate immune pathways (UIIPs, based on data of 1226 innate immune genes) in ApoE-/- Ang II-induced AAA at 7 days were different from that of 14 and 28 days, respectively; and AAA showed twin peaks of UIIPs with a major peak at 7 days and a minor peak at 28 days; 2) all the UIIPs in ApoE-/- atherosclerosis at 6 weeks were different from that of 32 and 78 weeks (two waves); 3) analyses of additional 12 lists of innate immune-related genes with 1325 cytokine and chemokine genes, 2022 plasma membrane protein genes, 373 clusters of differentiation (CD) marker genes, 280 nuclear membrane protein genes, 1425 nucleoli protein genes, 6750 nucleoplasm protein genes, 1496 transcription factors (TFs) including 15 pioneer TFs, 164 histone modification enzymes, 102 oxidative cell death genes, 68 necrotic cell death genes, and 47 efferocytosis genes confirmed two-wave inflammation in atherosclerosis and twin-peak inflammation in AAA; 4) DAMPs-stimulated VSMCs were innate immune cells as judged by the upregulation of innate immune genes and genes from 12 additional lists; 5) DAMPs-stimulated VSMCs increased trans-differentiation potential by upregulating not only some of 82 markers of 7 VSMC-plastic cell types, including fibroblast, osteogenic, myofibroblast, macrophage, adipocyte, foam cell, and mesenchymal cell, but also 18 new cell types (out of 79 human cell types with 8065 cell markers); 6) analysis of gene deficient transcriptomes indicated that the antioxidant transcription factor NRF2 suppresses, however, the other five inflammatory transcription factors and master regulators, including AHR, NF-KB, NOX (ROS enzyme), PERK, and SET7 promote the upregulation of twelve lists of innate immune genes in atherosclerosis, AAA, and DAMP-stimulated VSMCs; and 7) both SET7 and trained tolerance-promoting metabolite itaconate contributed to twin-peak upregulation of cytokines in AAA.

Discussion

Our findings have provided novel insights on the roles of innate immune responses and nuclear stresses in the development of AAA, atherosclerosis, and VSMC immunology and provided novel therapeutic targets for treating those significant cardiovascular and cerebrovascular diseases.

Liquid-Liquid Phase Separation Sheds New Light upon Cardiovascular Diseases

Liquid-liquid phase separation (LLPS) is a biophysical process that mediates the precise and complex spatiotemporal coordination of cellular processes. Proteins and nucleic acids are compartmentalized into micron-scale membrane-less droplets via LLPS. These droplets, termed biomolecular condensates, are highly dynamic, have concentrated components, and perform specific functions. Biomolecular condensates have been observed to organize diverse key biological processes, including gene transcription, signal transduction, DNA damage repair, chromatin organization, and autophagy. The dysregulation of these biological activities owing to aberrant LLPS is important in cardiovascular diseases. This review provides a detailed overview of the regulation and functions of biomolecular condensates, provides a comprehensive depiction of LLPS in several common cardiovascular diseases, and discusses the revolutionary therapeutic perspective of modulating LLPS in cardiovascular diseases and new treatment strategies relevant to LLPS.

Sequence variations of phase-separating proteins and resources for studying biomolecular condensates

Phase separation (PS) is an important mechanism underlying the formation of biomolecular condensates. Physiological condensates are associated with numerous biological processes, such as transcription, immunity, signaling, and synaptic transmission. Changes in particular amino acids or segments can disturb the protein's phase behavior and interactions with other biomolecules in condensates. It is thus presumed that variations in the phase-separating-prone domains can significantly impact the properties and functions of condensates. The dysfunction of condensates contributes to a number of pathological processes. Pharmacological perturbation of these condensates is proposed as a promising way to restore physiological states. In this review, we characterize the variations observed in PS proteins that lead to aberrant biomolecular compartmentalization. We also showcase recent advancements in bioinformatics of membraneless organelles (MLOs), focusing on available databases useful for screening PS proteins and describing endogenous condensates, guiding researchers to seek the underlying pathogenic mechanisms of biomolecular condensates.

Biological soft matter: intrinsically disordered proteins in liquid-liquid phase separation and biomolecular condensates

The facts that many proteins with crucial biological functions do not have unique structures and that many biological processes are compartmentalized into the liquid-like biomolecular condensates, which are formed via liquid-liquid phase separation (LLPS) and are not surrounded by the membrane, are revolutionizing the modern biology. These phenomena are interlinked, as the presence of intrinsic disorder represents an important requirement for a protein to undergo LLPS that drives biogenesis of numerous membrane-less organelles (MLOs). Therefore, one can consider these phenomena as crucial constituents of a new IDP-LLPS-MLO field. Furthermore, intrinsically disordered proteins (IDPs), LLPS, and MLOs represent a clear link between molecular and cellular biology and soft matter and condensed soft matter physics. Both IDP and LLPS/MLO fields are undergoing explosive development and generate the ever-increasing mountain of crucial data. These new data provide answers to so many long-standing questions that it is difficult to imagine that in the very recent past, protein scientists and cellular biologists operated without taking these revolutionary concepts into account. The goal of this essay is not to deliver a comprehensive review of the IDP-LLPS-MLO field but to provide a brief and rather subjective outline of some of the recent developments in these exciting fields.

PhaSepDB in 2022: annotating phase separation-related proteins with droplet states, co-phase separation partners and other experimental information

Phase separation (PS) proteins form droplets to regulate myriad membraneless organelles (MLOs) and cellular pathways such as transcription, signaling transduction and protein degeneration. PS droplets are usually liquid-like and can convert to hydrogel/solid-like under certain conditions. The PS behavior of proteins is regulated by co-PS partners and mutations, modifications, oligomerizations, repeat regions and alternative splicing of the proteins. With growing interest in PS condensates and associated proteins, we established PhaSepDB 1.0, which provided experimentally verified PS proteins and MLO-related proteins. The past few years witnessed a surge in PS-related research works; thus, we kept updating PhaSepDB. The current PhaSepDB contains 1419 PS entries, 770 low-throughput MLO-related entries and 7303 high-throughput MLO-related entries. We provided more detailed annotations of PS proteins, including PS verification experiments, regions used in experiments, phase diagrams of different experimental conditions, droplet states, co-PS partners and PS regulatory information. We believe that researchers can go further in studying PS proteins with the updated PhaSepDB (http://db.phasep.pro/).

Aberrant liquid-liquid phase separation and amyloid aggregation of proteins related to neurodegenerative diseases

Recent evidence has shown that the processes of liquid-liquid phase separation (LLPS) or liquid-liquid phase transitions (LLPTs) are a crucial and prevalent phenomenon that underlies the biogenesis of numerous membrane-less organelles (MLOs) and biomolecular condensates within the cells. Findings show that processes associated with LLPS play an essential role in physiology and disease. In this review, we discuss the physical and biomolecular factors that contribute to the development of LLPS, the associated functions, as well as their consequences for cell physiology and neurological disorders. Additionally, the finding of mis-regulated proteins, which have long been linked to aggregates in neuropathology, are also known to induce LLPS/LLPTs, prompting a lot of interest in understanding the connection between aberrant phase separation and disorder conditions. Moreover, the methods used in recent and ongoing studies in this field are also explored, as is the possibility that these findings will encourage new lines of inquiry into the molecular causes of neurodegenerative diseases.

Complementarity of the residue-level protein function and structure predictions in human proteins

Sequence-based predictors of the residue-level protein function and structure cover a broad spectrum of characteristics including intrinsic disorder, secondary structure, solvent accessibility and binding to nucleic acids. They were catalogued and evaluated in numerous surveys and assessments. However, methods focusing on a given characteristic are studied separately from predictors of other characteristics, while they are typically used on the same proteins. We fill this void by studying complementarity of a representative collection of methods that target different predictions using a large, taxonomically consistent, and low similarity dataset of human proteins. First, we bridge the gap between the communities that develop structure-trained vs. disorder-trained predictors of binding residues. Motivated by a recent study of the protein-binding residue predictions, we empirically find that combining the structure-trained and disorder-trained predictors of the DNA-binding and RNA-binding residues leads to substantial improvements in predictive quality. Second, we investigate whether diverse predictors generate results that accurately reproduce relations between secondary structure, solvent accessibility, interaction sites, and intrinsic disorder that are present in the experimental data. Our empirical analysis concludes that predictions accurately reflect all combinations of these relations. Altogether, this study provides unique insights that support combining results produced by diverse residue-level predictors of protein function and structure.

Databases for intrinsically disordered proteins

Intrinsically disordered regions (IDRs) lacking a fixed three-dimensional protein structure are widespread and play a central role in cell regulation. Only a small fraction of IDRs have been functionally characterized, with heterogeneous experimental evidence that is largely buried in the literature. Predictions of IDRs are still difficult to estimate and are poorly characterized. Here, an overview of the publicly available knowledge about IDRs is reported, including manually curated resources, deposition databases and prediction repositories. The types, scopes and availability of the various resources are analyzed, and their complementarity and overlap are highlighted. The volume of information included and the relevance to the field of structural biology are compared.