Unraveling the functional dark matter through global metagenomics.

Metagenomes encode an enormous diversity of proteins, reflecting a multiplicity of functions and activities1,2. Exploration of this vast sequence space has been limited to a comparative analysis against reference microbial genomes and protein families derived from those genomes. Here, to examine the scale of yet untapped functional diversity beyond what is currently possible through the lens of reference genomes, we develop a computational approach to generate reference-free protein families from the sequence space in metagenomes. We analyse 26,931 metagenomes and identify 1.17 billion protein sequences longer than 35 amino acids with no similarity to any sequences from 102,491 reference genomes or the Pfam database3. Using massively parallel graph-based clustering, we group these proteins into 106,198 novel sequence clusters with more than 100 members, doubling the number of protein families obtained from the reference genomes clustered using the same approach. We annotate these families on the basis of their taxonomic, habitat, geographical and gene neighbourhood distributions and, where sufficient sequence diversity is available, predict protein three-dimensional models, revealing novel structures. Overall, our results uncover an enormously diverse functional space, highlighting the importance of further exploring the microbial functional dark matter.

NMPFamsDB: a database of novel protein families from microbial metagenomes and metatranscriptomes.

The Novel Metagenome Protein Families Database (NMPFamsDB) is a database of metagenome- and metatranscriptome-derived protein families, whose members have no hits to proteins of reference genomes or Pfam domains. Each protein family is accompanied by multiple sequence alignments, Hidden Markov Models, taxonomic information, ecosystem and geolocation metadata, sequence and structure predictions, as well as 3D structure models predicted with AlphaFold2. In its current version, NMPFamsDB hosts over 100 000 protein families, each with at least 100 members. The reported protein families significantly expand (more than double) the number of known protein sequence clusters from reference genomes and reveal new insights into their habitat distribution, origins, functions and taxonomy. We expect NMPFamsDB to be a valuable resource for microbial proteome-wide analyses and for further discovery and characterization of novel functions. NMPFamsDB is publicly available in http://www.nmpfamsdb.org/ or https://bib.fleming.gr/NMPFamsDB.

Flame (v2.0): advanced integration and interpretation of functional enrichment results from multiple sources.

Functional enrichment is the process of identifying implicated functional terms from a given input list of genes or proteins. In this article, we present Flame (v2.0), a web tool which offers a combinatorial approach through merging and visualizing results from widely used functional enrichment applications while also allowing various flexible input options. In this version, Flame utilizes the aGOtool, g: Profiler, WebGestalt, and Enrichr pipelines and presents their outputs separately or in combination following a visual analytics approach. For intuitive representations and easier interpretation, it uses interactive plots such as parameterizable networks, heatmaps, barcharts, and scatter plots. Users can also: (i) handle multiple protein/gene lists and analyse union and intersection sets simultaneously through interactive UpSet plots, (ii) automatically extract genes and proteins from free text through text-mining and Named Entity Recognition (NER) techniques, (iii) upload single nucleotide polymorphisms (SNPs) and extract their relative genes, or (iv) analyse multiple lists of differentially expressed proteins/genes after selecting them interactively from a parameterizable volcano plot. Compared to the previous version of 197 supported organisms, Flame (v2.0) currently allows enrichment for 14 436 organisms. AVAILABILITY AND IMPLEMENTATION: Web Application: http://flame.pavlopouloslab.info. Code: https://github.com/PavlopoulosLab/Flame. Docker: https://hub.docker.com/r/pavlopouloslab/flame.

Arena3Dweb: interactive 3D visualization of multilayered networks.

Efficient integration and visualization of heterogeneous biomedical information in a single view is a key challenge. In this study, we present Arena3Dweb, the first, fully interactive and dependency-free, web application which allows the visualization of multilayered graphs in 3D space. With Arena3Dweb, users can integrate multiple networks in a single view along with their intra- and inter-layer connections. For clearer and more informative views, users can choose between a plethora of layout algorithms and apply them on a set of selected layers either individually or in combination. Users can align networks and highlight node topological features, whereas each layer as well as the whole scene can be translated, rotated and scaled in 3D space. User-selected edge colors can be used to highlight important paths, while node positioning, coloring and resizing can be adjusted on-the-fly. In its current version, Arena3Dweb supports weighted and unweighted undirected graphs and is written in R, Shiny and JavaScript. We demonstrate the functionality of Arena3Dweb using two different use-case scenarios; one regarding drug repurposing for SARS-CoV-2 and one related to GPCR signaling pathways implicated in melanoma. Arena3Dweb is available at http://bib.fleming.gr:3838/Arena3D or http://bib.fleming.gr/Arena3D.

Extended Human G-Protein Coupled Receptor Network: Cell-Type-Specific Analysis of G-Protein Coupled Receptor Signaling Pathways.

G-protein coupled receptors (GPCRs) mediate crucial physiological functions in humans, have been implicated in an array of diseases, and are therefore prime drug targets. GPCRs signal via a multitude of pathways, mainly through G-proteins and ß-arrestins, to regulate effectors responsible for cellular responses. The limited number of transducers results in different GPCRs exerting control on the same pathway, while the availability of signaling proteins in a cell defines the result of GPCR activation. The aim of this study was to construct the extended human GPCR network (hGPCRnet) and examine the effect that cell-type specificity has on GPCR signaling pathways. To achieve this, protein-protein interaction data between GPCRs, G-protein coupled receptor kinases (GRKs), Gα subunits, ß-arrestins, and effectors were combined with protein expression data in cell types. This resulted in the hGPCRnet, a very large interconnected network, and similar cell-type-specific networks in which, distinct GPCR signaling pathways were formed. Finally, a user friendly web application, hGPCRnet ( http://bioinformatics.biol.uoa.gr/hGPCRnet ), was created to allow for the visualization and exploration of these networks and of GPCR signaling pathways. This work, and the resulting application, can be useful in further studies of GPCR function and pharmacology.

Delving into the amyloidogenic core of human leukocyte chemotactic factor 2.

ALECT2 (leukocyte chemotactic factor 2) amyloidosis is one of the most recently identified amyloid-related diseases, with LECT2 amyloids commonly found in different types of tissues. Under physiological conditions, LECT2 is a 16 kDa multifunctional protein produced by the hepatocytes and secreted into circulation. The pathological mechanisms causing LECT2 transition into the amyloid state are still largely unknown. In the case of ALECT2 patients, there is no disease-causing mutation, yet almost all patients carry a common polymorphism that appears to be necessary but not sufficient to directly trigger amyloidogenesis. In this work, we followed a reductionist methodology in order to detect critical amyloidogenic "hot-spots" during the fibrillation of LECT2. By associating experimental and computational assays, this approach reveals the explicit amyloidogenic core of human LECT2 and pinpoints regions with distinct amyloidogenic properties. The fibrillar architecture of LECT2 polymers, based on our results, provides a wealth of detailed information about the amyloidogenic "hot-spot" interactions and represents a starting point for future peptide-driven intervention in ALECT2 amyloidosis.

The gram-negative outer membrane modeler: Automated building of lipopolysaccharide-rich bacterial outer membranes in four force fields.

Outer membranes are a crucial component of Gram-negative bacteria, containing standard lipids in their inner leaflet, lipopolysaccharides (LPSs) in their outer leaflet, and transmembrane ß-barrels known as outer membrane proteins (OMPs). OMPs regulate functions such as substrate transport and cell movement, while LPSs act as a protective barrier for bacteria and can cause toxic reactions in humans. However, the experimental study of outer membranes is challenging. Molecular dynamics simulations are often used for the computational study of membrane systems, but the preparation of complex, LPS-rich outer membranes is not straightforward. The Gram-Negative Outer Membrane Modeler (GNOMM) is an automated pipeline for preparing simulation systems of OMPs embedded in LPS-containing membranes in four different force fields. Given the physiological and clinical importance of outer membranes and their components, GNOMM can be a useful tool in the study of their structure, function, and implications in diseases. GNOMM is available at http://bioinformatics.biol.uoa.gr/GNOMM. © 2019 Wiley Periodicals, Inc.

Structural characterization and molecular dynamics simulations of the caprine and bovine solute carrier family 11 A1 (SLC11A1).

Natural Resistance-Associated Macrophage Proteins are a family of transmembrane divalent metal ion transporters, with important implications in life of both bacteria and mammals. Among them, the Solute Carrier family 11 member A1 (SLC11A1) has been implicated with susceptibility to infection by Mycobacterium avium subspecies paratuberculosis (MAP), potentially causing Crohn's disease in humans and paratuberculosis (PTB) in ruminants. Our previous research had focused on sequencing the mRNA of the caprine slc11a1 gene and pinpointed polymorphisms that contribute to caprine SLC11A1's susceptibility to infection by MAP in PTB. Despite its importance, little is known on the structural/dynamic features of mammalian SLC11A1 that may influence its function under normal or pathological conditions at the protein level. In this work we studied the structural architecture of SLC11A1 in Capra hircus and Bos taurus through molecular modeling, molecular dynamics simulations in different, functionally relevant configurations, free energy calculations of protein-metal interactions and sequence conservation analysis. The results of this study propose a three dimensional structure for SLC11A1 with conserved sequence and structural features and provide hints for a potential mechanism through which divalent metal ion transport is conducted. Given the importance of SLC11A1 in susceptibility to PTB, this study provides a framework for further studies on the structure and dynamics of SLC11A1 in other organisms, to gain 3D structural insight into the macromolecular arrangements of SLC11A1 but also suggesting a potential mechanism which divalent metal ion transport is conducted.

Hidden Aggregation Hot-Spots on Human Apolipoprotein E: A Structural Study.

Human apolipoprotein E (apoE) is a major component of lipoprotein particles, and under physiological conditions, is involved in plasma cholesterol transport. Human apolipoprotein E found in three isoforms (E2; E3; E4) is a member of a family of apolipoproteins that under pathological conditions are detected in extracellular amyloid depositions in several amyloidoses. Interestingly, the lipid-free apoE form has been shown to be co-localized with the amyloidogenic Aß peptide in amyloid plaques in Alzheimer's disease, whereas in particular, the apoE4 isoform is a crucial risk factor for late-onset Alzheimer's disease. Evidence at the experimental level proves that apoE self-assembles into amyloid fibrilsin vitro, although the misfolding mechanism has not been clarified yet. Here, we explored the mechanistic insights of apoE misfolding by testing short apoE stretches predicted as amyloidogenic determinants by AMYLPRED, and we computationally investigated the dynamics of apoE and an apoE-Αß complex. Our in vitro biophysical results prove that apoE peptide-analogues may act as the driving force needed to trigger apoE aggregation and are supported by the computational apoE outcome. Additional computational work concerning the apoE-Αß complex also designates apoE amyloidogenic regions as important binding sites for oligomeric Αß; taking an important step forward in the field of Alzheimer's anti-aggregation drug development.

αCGRP, another amyloidogenic member of the CGRP family.

The Calcitonin-gene related peptide (CGRP) family is a group of peptide hormones, which consists of IAPP, calcitonin, adrenomedullin, intermedin, αCGRP and ßCGRP. IAPP and calcitonin have been extensively associated with the formation of amyloid fibrils, causing Type 2 Diabetes and Medullary Thyroid Carcinoma, respectively. In contrast, the potential amyloidogenic properties of αCGRP still remain unexplored, although experimental trials have indicated its presence in deposits, associated with the aforementioned disorders. Therefore, in this work, we investigated the amyloidogenic profile of αCGRP, a 37-residue-long peptide hormone, utilizing both biophysical experimental techniques and Molecular Dynamics simulations. These efforts unravel a novel amyloidogenic member of the CGRP family and provide insights into the mechanism underlying the αCGRP polymerization.

Tracking the amyloidogenic core of IAPP amyloid fibrils: Insights from micro-Raman spectroscopy.

Human islet amyloid polypeptide (hIAPP) is the major protein component of extracellular amyloid deposits, located in the islets of Langerhans, a hallmark of type II diabetes. The underlying mechanisms of IAPP aggregation have not yet been clearly defined, although the highly amyloidogenic sequence of the protein has been extensively studied. Several segments have been highlighted as aggregation-prone regions (APRs), with much attention focused on the central 8-17 and 20-29 stretches. In this work, we employ micro-Raman spectroscopy to identify specific regions that are contributing to or are excluded from the amyloidogenic core of IAPP amyloid fibrils. Our results demonstrate that both the N-terminal region containing a conserved disulfide bond between Cys residues at positions 2 and 7, and the C-terminal region containing the only Tyr residue are excluded from the amyloid core. Finally, by performing detailed aggregation assays and molecular dynamics simulations on a number of IAPP variants, we demonstrate that point mutations within the central APRs contribute to the reduction of the overall amyloidogenic potential of the protein but do not completely abolish the formation of IAPP amyloid fibrils.

Molecular dynamics simulations and structure-based network analysis reveal structural and functional aspects of G-protein coupled receptor dimer interactions.

A significant amount of experimental evidence suggests that G-protein coupled receptors (GPCRs) do not act exclusively as monomers but also form biologically relevant dimers and oligomers. However, the structural determinants, stoichiometry and functional importance of GPCR oligomerization remain topics of intense speculation. In this study we attempted to evaluate the nature and dynamics of GPCR oligomeric interactions. A representative set of GPCR homodimers were studied through Coarse-Grained Molecular Dynamics simulations, combined with interface analysis and concepts from network theory for the construction and analysis of dynamic structural networks. Our results highlight important structural determinants that seem to govern receptor dimer interactions. A conserved dynamic behavior was observed among different GPCRs, including receptors belonging in different GPCR classes. Specific GPCR regions were highlighted as the core of the interfaces. Finally, correlations of motion were observed between parts of the dimer interface and GPCR segments participating in ligand binding and receptor activation, suggesting the existence of mechanisms through which dimer formation may affect GPCR function. The results of this study can be used to drive experiments aimed at exploring GPCR oligomerization, as well as in the study of transmembrane protein-protein interactions in general.

A ß-solenoid model of the Pmel17 repeat domain: insights to the formation of functional amyloid fibrils.

Pmel17 is a multidomain protein involved in biosynthesis of melanin. This process is facilitated by the formation of Pmel17 amyloid fibrils that serve as a scaffold, important for pigment deposition in melanosomes. A specific luminal domain of human Pmel17, containing 10 tandem imperfect repeats, designated as repeat domain (RPT), forms amyloid fibrils in a pH-controlled mechanism in vitro and has been proposed to be essential for the formation of the fibrillar matrix. Currently, no three-dimensional structure has been resolved for the RPT domain of Pmel17. Here, we examine the structure of the RPT domain by performing sequence threading. The resulting model was subjected to energy minimization and validated through extensive molecular dynamics simulations. Structural analysis indicated that the RPT model exhibits several distinct properties of ß-solenoid structures, which have been proposed to be polymerizing components of amyloid fibrils. The derived model is stabilized by an extensive network of hydrogen bonds generated by stacking of highly conserved polar residues of the RPT domain. Furthermore, the key role of invariant glutamate residues is proposed, supporting a pH-dependent mechanism for RPT domain assembly. Conclusively, our work attempts to provide structural insights into the RPT domain structure and to elucidate its contribution to Pmel17 amyloid fibril formation.

kmerDB: A database encompassing the set of genomic and proteomic sequence information for each species.

The decrease in sequencing expenses has facilitated the creation of reference genomes and proteomes for an expanding array of organisms. Nevertheless, no established repository that details organism-specific genomic and proteomic sequences of specific lengths, referred to as kmers, exists to our knowledge. In this article, we present kmerDB, a database accessible through an interactive web interface that provides kmer-based information from genomic and proteomic sequences in a systematic way. kmerDB currently contains 202,340,859,107 base pairs and 19,304,903,356 amino acids, spanning 54,039 and 21,865 reference genomes and proteomes, respectively, as well as 6,905,362 and 149,305,183 genomic and proteomic species-specific sequences, termed quasi-primes. Additionally, we provide access to 5,186,757 nucleic and 214,904,089 peptide sequences absent from every genome and proteome, termed primes. kmerDB features a user-friendly interface offering various search options and filters for easy parsing and searching. The service is available at: www.kmerdb.com.

Visualizing metagenomic and metatranscriptomic data: A comprehensive review.

The fields of Metagenomics and Metatranscriptomics involve the examination of complete nucleotide sequences, gene identification, and analysis of potential biological functions within diverse organisms or environmental samples. Despite the vast opportunities for discovery in metagenomics, the sheer volume and complexity of sequence data often present challenges in processing analysis and visualization. This article highlights the critical role of advanced visualization tools in enabling effective exploration, querying, and analysis of these complex datasets. Emphasizing the importance of accessibility, the article categorizes various visualizers based on their intended applications and highlights their utility in empowering bioinformaticians and non-bioinformaticians to interpret and derive insights from meta-omics data effectively.

Interactions of the α-subunits of heterotrimeric G-proteins with GPCRs, effectors and RGS proteins: a critical review and analysis of interacting surfaces, conformational shifts, structural diversity and electrostatic potentials.

G-protein coupled receptors (GPCRs) are one of the largest families of membrane receptors in eukaryotes. Heterotrimeric G-proteins, composed of α, ß and γ subunits, are important molecular switches in the mediation of GPCR signaling. Receptor stimulation after the binding of a suitable ligand leads to G-protein heterotrimer activation and dissociation into the Gα subunit and Gßγ heterodimer. These subunits then interact with a large number of effectors, leading to several cell responses. We studied the interactions between Gα subunits and their binding partners, using information from structural, mutagenesis and Bioinformatics studies, and conducted a series of comparisons of sequence, structure, electrostatic properties and intermolecular energies among different Gα families and subfamilies. We identified a number of Gα surfaces that may, in several occasions, participate in interactions with receptors as well as effectors. The study of Gα interacting surfaces in terms of sequence, structure and electrostatic potential reveals features that may account for the Gα subunit's behavior towards its interacting partners. The electrostatic properties of the Gα subunits, which in some cases differ greatly not only between families but also between subfamilies, as well as the G-protein interacting surfaces of effectors and regulators of G-protein signaling (RGS) suggest that electrostatic complementarity may be an important factor in G-protein interactions. Energy calculations also support this notion. This information may be useful in future studies of G-protein interactions with GPCRs and effectors.

Proteome-Wide Detection and Annotation of Receptor Tyrosine Kinases (RTKs): RTK-PRED and the TyReK Database.

Receptor tyrosine kinases (RTKs) form a highly important group of protein receptors of the eukaryotic cell membrane. They control many vital cellular functions and are involved in the regulation of complex signaling networks. Mutations in RTKs have been associated with different types of cancers and other diseases. Although they are very important for proper cell function, they have been experimentally studied in a limited range of eukaryotic species. Currently, there is no available database for RTKs providing information about their function, expression, and interactions. Therefore, the identification of RTKs in multiple organisms, the documentation of their characteristics, and the collection of related information would be very useful. In this paper, we present a novel RTK detection pipeline (RTK-PRED) and the Receptor Tyrosine Kinases Database (TyReK-DB). RTK-PRED combines profile HMMs with transmembrane topology prediction to identify and classify potential RTKs. Proteins of all eukaryotic reference proteomes of the UniProt database were used as input in RTK-PRED leading to a filtered dataset of 20,478 RTKs. Based on the information collected for these RTKs from multiple databases, the relational TyReK database was created.

NucEnvDB: A Database of Nuclear Envelope Proteins and Their Interactions.

The nuclear envelope (NE) is a double-membrane system surrounding the nucleus of eukaryotic cells. A large number of proteins are localized in the NE, performing a wide variety of functions, from the bidirectional exchange of molecules between the cytoplasm and the nucleus to chromatin tethering, genome organization, regulation of signaling cascades, and many others. Despite its importance, several aspects of the NE, including its protein-protein interactions, remain understudied. In this work, we present NucEnvDB, a publicly available database of NE proteins and their interactions. Each database entry contains useful annotation including a description of its position in the NE, its interactions with other proteins, and cross-references to major biological repositories. In addition, the database provides users with a number of visualization and analysis tools, including the ability to construct and visualize protein-protein interaction networks and perform functional enrichment analysis for clusters of NE proteins and their interaction partners. The capabilities of NucEnvDB and its analysis tools are showcased by two informative case studies, exploring protein-protein interactions in Hutchinson-Gilford progeria and during SARS-CoV-2 infection at the level of the nuclear envelope.

SCALA: A complete solution for multimodal analysis of single-cell Next Generation Sequencing data.

Analysis and interpretation of high-throughput transcriptional and chromatin accessibility data at single-cell (sc) resolution are still open challenges in the biomedical field. The existence of countless bioinformatics tools, for the different analytical steps, increases the complexity of data interpretation and the difficulty to derive biological insights. In this article, we present SCALA, a bioinformatics tool for analysis and visualization of single-cell RNA sequencing (scRNA-seq) and Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) datasets, enabling either independent or integrative analysis of the two modalities. SCALA combines standard types of analysis by integrating multiple software packages varying from quality control to the identification of distinct cell populations and cell states. Additional analysis options enable functional enrichment, cellular trajectory inference, ligand-receptor analysis, and regulatory network reconstruction. SCALA is fully parameterizable, presenting data in tabular format and producing publication-ready visualizations. The different available analysis modules can aid biomedical researchers in exploring, analyzing, and visualizing their data without any prior experience in coding. We demonstrate the functionality of SCALA through two use-cases related to TNF-driven arthritic mice, handling both scRNA-seq and scATAC-seq datasets. SCALA is developed in R, Shiny and JavaScript and is mainly available as a standalone version, while an online service of more limited capacity can be found at http://scala.pavlopouloslab.info or https://scala.fleming.gr.

Arena3Dweb: interactive 3D visualization of multilayered networks supporting multiple directional information channels, clustering analysis and application integration.

Arena3Dweb is an interactive web tool that visualizes multi-layered networks in 3D space. In this update, Arena3Dweb supports directed networks as well as up to nine different types of connections between pairs of nodes with the use of Bézier curves. It comes with different color schemes (light/gray/dark mode), custom channel coloring, four node clustering algorithms which one can run on-the-fly, visualization in VR mode and predefined layer layouts (zig-zag, star and cube). This update also includes enhanced navigation controls (mouse orbit controls, layer dragging and layer/node selection), while its newly developed API allows integration with external applications as well as saving and loading of sessions in JSON format. Finally, a dedicated Cytoscape app has been developed, through which users can automatically send their 2D networks from Cytoscape to Arena3Dweb for 3D multi-layer visualization. Arena3Dweb is accessible at http://arena3d.pavlopouloslab.info or http://arena3d.org.