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At least 919 records · Page 51Linked to original sources

bioRxiv2025

Comparison of Activities of Transcription Factor NF-κB from Two Jellyfish Models

Herein, transcription factor Nuclear Factor-kappaB (NF-{kappa}B) is characterized as the downstream effector of putative innate immune signaling pathways from two model jellyfish, Aurelia aurita (Aa) and Clytia hemisphaerica (Ch). Both jellyfish NF-{kappa}B proteins consist primarily of the N-terminal DNA-binding/dimerization domain, and they lack the C-terminal ankyrin repeat inhibitory domain found in vertebrate NF-{kappa}B proteins. Both jellyfish NF-{kappa}B proteins bind to a consensus mammalian NF-{kappa}B binding site, and their AlphaFold3-predicted structures on DNA are similar to that of mouse NF-{kappa}B p50. Neither Aa- nor Ch-NF-{kappa}B activated transcription of an NF-{kappa}B-site reporter gene in human cells; however, Aa-NF-{kappa}B did activate transcription from a GAL4-site reporter gene in yeast, whereas Ch-NF-{kappa}B did not. Aa- and Ch-NF-{kappa}B were both constitutively located in the nucleus when expressed in vertebrate cells. Homologs of I{kappa}B-like proteins from both species interacted with their corresponding NF-{kappa}B proteins in co-immunoprecipitation assays in HEK 293T cells. These I{kappa}B-like proteins influenced the subcellular localization of their cognate NF-{kappa}B proteins in vertebrate cells, and their ankyrin repeat domains were predicted to interact with Ch-NF-{kappa}B in a manner similar to mammalian I{kappa}B and NF-{kappa}B. RNA-sequencing data from Ch animals indicate that Ch-NF-{kappa}B is expressed at high levels in early developmental stages, when Ch-I{kappa}B expression is low, suggesting that active Ch-NF-{kappa}B controls an early developmental process. In contrast, in adult animals the expression of Ch-I{kappa}B is high, suggesting that Ch-NF-{kappa}B requires a signal in order to become active. Overall, these results provide comparative information on the structure, activity, and mRNA expression of jellyfish NF-{kappa}B pathway proteins among jellyfish, and they suggest roles for NF-{kappa}B in developing and adult jellyfish.

molecular biology↗

bioRxiv2021

Spatially resolved whole transcriptome profiling in human and mouse tissue using Digital Spatial Profiling

Emerging spatial profiling technology has enabled high-plex molecular profiling in biological tissues, preserving the spatial and morphological context of gene expression. Here we describe expanding the chemistry for the Digital Spatial Profiling platform to quantify whole transcriptomes in human and mouse tissues using a wide range of spatial profiling strategies and sample types. We designed multiplexed in situ hybridization probe pools targeting the protein-coding genes in the human and mouse transcriptomes, hereafter referred to as the human or mouse Whole Transcriptome Atlas (WTA). We validated the human and mouse WTA using cell lines to demonstrate concordance with orthogonal gene expression profiling methods in profiled region sizes ranging from ~10-500 cells. By benchmarking against bulk RNAseq and fluorescence in situ hybridization, we demonstrate robust transcript detection possible down to ~100 transcripts per region. To assess the performance of WTA across tissue and sample types, we applied WTA to biological questions in cancer, molecular pathology, and developmental biology. We show that spatial profiling with WTA can detect expected spatial gene expression differences between tumor and tumor microenvironment, identify spatial disease-specific heterogeneity in gene expression in histological structures of the human kidney, and comprehensively map transcriptional programs in anatomical substructures of nine organs in the developing mouse embryo. Digital Spatial Profiling technology with the WTA assays provides a flexible method for spatial whole transcriptome profiling applicable to diverse tissue types and biological contexts.

genomics↗

bioRxiv2021

SWI/SNF senses carbon starvation with a pH-sensitive low complexity sequence

It is increasingly appreciated that intracellular pH changes are important biological signals. This motivates the elucidation of molecular mechanisms of pH-sensing. We determined that a nucleocytoplasmic pH oscillation was required for the transcriptional response to carbon starvation in S. cerevisiae. The SWI/SNF chromatin remodeling complex is a key mediator of this transcriptional response. We found that a glutamine-rich low complexity sequence (QLC) in the SNF5 subunit of this complex, and histidines within this sequence, were required for efficient transcriptional reprogramming during carbon starvation. Furthermore, the SNF5 QLC mediated pH-dependent recruitment of SWI/SNF to a model promoter in vitro. Simulations showed that protonation of histidines within the SNF5 QLC lead to conformational expansion, providing a potential biophysical mechanism for regulation of these interactions. Together, our results indicate that that pH changes are a second messenger for transcriptional reprogramming during carbon starvation, and that the SNF5 QLC acts as a pH-sensor.

molecular biology↗

bioRxiv2022

Uncovering the "ZIP code" for bZIP dimers reveals novel motifs, regulatory rules and one billion years of cis-element evolution

Many eukaryotic transcription factors (TF) form homodimer or heterodimer complexes to regulate gene expression. For example, dimerization properties of the basic leucine zipper (bZIP) family play a critical role in regulating the unique biological functions in all eukaryotes. However, the molecular mechanism underlying the binding sequence and functional specificity of homo- versus heterodimers remains elusive. To fill this gap, we developed a double DNA Affinity Purification sequencing (dDAP-seq) technique that maps heterodimer DNA binding sites in an endogenous genome context. Our genome-wide binding profiles of twenty pairs of C/S1 bZIP heterodimers and S1 homodimers in Arabidopsis revealed that heterodimerization significantly expands the DNA binding preferences of bZIP TFs. Analysis of the heterodimer target genes in stress response and development suggest heterodimerization gives rise to regulatory responses that are distinct from the homodimers. In addition to the classic ACGT elements recognized by plant bZIPs, we found that the C/S1 heterodimers bound to motifs that might share an origin with the GCN4 cis-elements in yeast that diverged from plants more than one billion years ago. Importantly, heterodimer binding specificities can be distinguished by their relative preference for ACGT motifs versus GCN4-related motifs. More broadly, our study demonstrates the potential of dDAP-seq in deciphering the DNA binding specificities of interacting TFs that are key for combinatorial gene regulation.

molecular biology↗

bioRxiv2022

Study on endogenous inhibitors against PD-L1: cAMP as a potential candidate

The discovery of new anticancer drugs targeting the PD-1/PD-L1 pathway has been research hotspots. In this study, a combination of biological affinity ultrafiltration (BAU), UPLC-HRMS, molecular dynamic (MD) simulations and molecular docking methods were applied to search for endogenous active compounds that can inhibit the binding of PD-L1 and PD-1. We screened dozens of potential cancer related endogenous compounds. The results showed that cyclic adenosine monophosphate (cAMP) had a direct inhibition effect on the PD-1/PD-L1 binding with an in vitro IC50 value of about 2.7 {micro}M determined by homogeneous time-resolved fluorescence (HTRF) assay. The binding mode analyses for the cAMP - dimeric/monomeric PD-L1 complex indicated that cAMP was likely to bind to the dimeric PD-L1, since the binding free energies of the cAMP - dimeric and monomeric PD-L1 complex were about 23.6 and 15.1 kcal/mol, respectively, from MD simulations. The direct binding assay using surface plasmon resonance (SPR) method showed that cAMP could also bind to monomeric PD-L1 fixed on the sensor chip surface with a KD value of about 1.72 mM. Our findings suggested that cAMP may directly inhibit the PD-1/PD-L1 interaction.

molecular biology↗

bioRxiv2022

Molecular determinants of dynamic protein-protein interactions in the functional cycle of the membrane protein DsbD

Molecular recognition is of central importance in biology. The molecular determinants shaping recognition of one protein domain by another are incompletely understood, especially in the context of the complex function of molecular machines. Here, we combine NMR experiments and molecular dynamics simulations to elucidate the determinants of recognition of the C-terminal (cDsbD) domain of the transmembrane reductant conductor DsbD by its cognate partner, the N-terminal domain of the protein (nDsbD). As part of the natural cycle of this oxidoreductase, which effectively transfers electrons from the cytoplasm to the periplasm of Gram-negative bacteria, cDsbD and nDsbD toggle between oxidised and reduced states, something that modulates the affinity of the domains for each other and prevents otherwise unproductive reactions. We find that the redox state of cDsbD determines the dissociation rate of cDsbD-nDsbD complexes. Molecular dynamics simulations demonstrate how the redox-state of the active site determines the stability of inter-domain hydrogen bonds and thus the dissociation rate. AlphaFold modelling and atomistic molecular dynamics simulations of full-length DsbD in a realistic bacterial membrane again highlights the close proximity of the periplasmic domains and the importance of tuning the strength of the interactions of the periplasmic domains to enable electron transfer to cognate periplasmic partners such as CcmG. Our AlphaFold models are consistent with in vivo functional assays of DsbD mutants, which together help to reveal for the first-time a putative binding site for thioredoxin on the cytoplasmic side of DsbD.

biophysics↗

bioRxiv2023

Oligonucleotide-directed proximity-interactome mapping (O-MAP): A unified method for discovering RNA-interacting proteins, transcripts and genomic loci in situ.

Throughout biology, RNA molecules form complex networks of molecular interactions that are central to their function, but remain challenging to investigate. Here, we introduce Oligonucleotide-mediated proximity-interactome MAPping (O-MAP), a straightforward method for elucidating the biomolecules near an RNA of interest, within its native cellular context. O-MAP uses programmable oligonucleotide probes to deliver proximity-biotinylating enzymes to a target RNA, enabling nearby molecules to be enriched by streptavidin pulldown. O-MAP induces exceptionally precise RNA-localized in situ biotinylation, and unlike alternative methods it enables straightforward optimization of its targeting accuracy. Using the 47S pre-ribosomal RNA and long noncoding RNA Xist as models, we develop O-MAP workflows for unbiased discovery of RNA-proximal proteins, transcripts, and genomic loci. This revealed unexpected co-compartmentalization of Xist and other chromatin-regulatory RNAs and enabled systematic characterization of nucleolar-chromatin interactions across multiple cell lines. O-MAP is portable to cultured cells, organoids, and tissues, and to RNAs of various lengths, abundances, and sequence composition. And, O-MAP requires no genetic manipulation and uses exclusively off-the-shelf parts. We therefore anticipate its application to a broad array of RNA phenomena.

molecular biology↗

bioRxiv2024

Precious3GPT: Multimodal Multi-Species Multi-Omics Multi-Tissue Transformer for Aging Research and Drug Discovery

We present a multimodal multi-species multi-omics multi-tissue transformer for aging research and drug discovery capable of performing multiple tasks such as age prediction across species, target discovery, tissue, sex, and disease sample classification, drug sensitivity prediction, replication of omics response and prediction of biological and phenotypic response to compound treatment. This model combines textual, tabular, and knowledge graph-derived representations of biological experiments to provide insights into molecular-level biological processes. We demonstrate that P3GPT has developed an intuition for the interactions between compounds, pathologies, and gene regulation in the context of multiple species and tissues. In these areas, it outperforms existing LLMs and we highlight its utility in diverse case studies. P3GPT is a general model that may be used as a target identification tool, aging clock, digital laboratory, and scientific assistant. The model is intended as a community resource available open source as well as via a Discord server.

bioinformatics↗

bioRxiv2023

C9orf72 gene networks in the human brain correlate with cortical thickness in C9-FTD and implicate vulnerable cell types

IntroductionA hexanucleotide repeat expansion (HRE) intronic to chromosome 9 open reading frame 72 (C9orf72) is recognized as the most common genetic cause of amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and ALS-FTD. Identifying genes that show similar regional co-expression patterns to C9orf72 may help identify novel gene targets and biological mechanisms that mediate selective vulnerability to ALS and FTD pathogenesis. MethodsWe leveraged mRNA expression data in healthy brain from the Allen Human Brain Atlas to evaluate C9orf72 co-expression patterns. To do this, we correlated average C9orf72 expression values in 51 regions across different anatomical divisions (cortex, subcortex, cerebellum) with average gene expression values for 15,633 protein-coding genes, including 50 genes known to be associated with ALS, FTD, or ALS-FTD. We then evaluated whether the identified C9orf72 co-expressed genes correlated with patterns of cortical thickness in symptomatic C9orf72 pathogenic HRE carriers (n=19). Lastly, we explored whether genes with significant C9orf72 radiogenomic correlations (i.e., C9orf72 gene network) were enriched in specific cell populations in the brain and enriched for specific biological and molecular pathways. ResultsA total of 1,748 genes showed an anatomical distribution of gene expression in the brain similar to C9orf72 and significantly correlated with patterns of cortical thickness in C9orf72 HRE carriers. This C9orf72 gene network was differentially expressed in cell populations previously implicated in ALS and FTD, including layer 5b cells, cholinergic motor neurons in the spinal cord, and medium spiny neurons of the striatum, and was enriched for biological and molecular pathways associated with multiple neurotransmitter systems, protein ubiquitination, autophagy, and MAPK signaling, among others. ConclusionsConsidered together, we identified a network of C9orf72-associated genes that may influence selective regional and cell-type-specific vulnerabilities in ALS/FTD.

neuroscience↗

bioRxiv2021

Non-coding circular RNAs repertoire and expression profile during Brassica rapa pollen development

Circular RNAs (circRNAs) are covalently closed long non-coding RNA (lncRNA) molecules generated by the back-splicing of exons from linear precursor mRNAs. Though linear lncRNAs have been shown to play important regulatory roles in diverse biological and developmental processes, little is known about the role of their circular counterparts. In this study, we have performed high-throughput RNA sequencing to delineate the expression profile and potential function of circRNAs during the five stages of pollen development in Brassica rapa. A total of 1180 circRNAs were detected in pollen development, of which 367 showed stage-specific expression patterns. Functional enrichment and metabolic pathway analysis showed that the parent genes of circRNAs were mainly involved in pollen-related molecular and biological processes such as mitotic and meiosis cell division, DNA processes, protein synthesis, protein modification, and polysaccharide biosynthesis. Moreover, by predicting the circRNA-miRNA network from our differentially expressed circRNAs, we found 88 circRNAs with potential miRNA binding sites suggesting their role in post-transcriptional regulation of the genes. Finally, we confirmed the back-splicing sites of 9 randomly selected circRNAS using divergent primers and Sanger sequencing. Our study presents the first systematic analysis of circular RNAs during pollen development and forms the basis of future studies for unlocking complex gene regulatory networks underpinning reproduction in flowering plants.

molecular biology↗

bioRxiv2023

Engineering genetic circuits in receiver cells for diffusion-based molecular data communications

Developments in bioengineering and nanotechnology have ignited the research on biological and molecular communication systems. Despite potential benefits, engineering communication systems to carry data signals using biological messenger molecules is challenging. Diffusing molecules may fall behind their schedule to arrive at a receiver, interfering with symbols of subsequent time slots and distorting the signal. Theoretical molecular communication models often focus solely on the characteristics of the communication channel and fail to provide an end-to-end system response, since they assume a simple thresholding process for a receiver cell and overlook how the receiver can detect the incoming distorted molecular signal. There is a need to develop viable end-to-end communication models. In this paper, we present a model-based framework for designing diffusion-based molecular communication systems coupled with synthetic genetic circuits. We describe a novel approach to encode information as a sequence of bits, each transmitted from a sender as a burst of specific number of molecules, control cellular behavior, and minimize cellular signal interference by employing equalization techniques from communication theory. This approach allows the encoding and de-coding of data bits efficiently using two different types of molecules that act as the data carrier and the antagonist to cancel out the heavy tail of the former. We also present Period Finder, as a tool to optimize communication parameters, including the number of molecules and symbol duration. This tool facilitates automating the choice of communication parameters and identifying the best communication scenarios that can produce efficient cellular signals.

synthetic biology↗

bioRxiv2024

Y chromosome shredding in Anopheles gambiae: insight into the cellular dynamics of a novel synthetic sex ratio distorter.

Despite efforts to explore the genome of the malaria vector Anopheles gambiae, the Y chromosome of this species remains enigmatic. The large number of repetitive and heterochromatic DNA sequences makes the Y chromosome exceptionally difficult to fully assemble, hampering the progress of gene editing techniques and functional studies for this chromosome. In this study, we made use of a bioinformatic platform to identify Y-specific repetitive DNA sequences that served as a target site for a CRISPR/Cas9 system. The activity of Cas9 in the reproductive organs of males caused damage to Y-bearing sperm without affecting their fertility, leading to a strong female bias in the progeny. Cytological investigation allowed us to identify meiotic defects and investigate sperm selection in this new synthetic sex ratio distorter system. In addition, alternative promoters enable us to target the Y chromosome in specific tissues and developmental stages of male mosquitoes, enabling studies that shed light on the role of this chromosome in male gametogenesis. This work paves the way for further insight into the poorly characterised Y chromosome of Anopheles gambiae. Moreover, the sex distorter strain we have generated promises to be a valuable tool for the advancement of studies in the field of developmental biology, with the potential to support the progress of genetic strategies aimed at controlling malaria mosquitoes and other pest species. Author summaryGenetic elements known as sex ratio meiotic drive can manipulate the sex ratio of offspring, favouring the male or female sex. This fascinating phenomenon has inspired the development of synthetic sex ratio distorter systems in several organisms. In species where females and males harbour XX and XY sex chromosomes respectively, the X-chromosome can be shredded during male gametogenesis, leading to the production of non-functional X-bearing sperm, while Y-bearing sperm are left intact and able to fertilise the eggs. These systems can produce offspring that are extremely biased towards males, which can be used as genetic tools to control harmful insect populations. In our study, we applied this molecular strategy to target the Y chromosome of Anopheles gambiae. Our aim was to investigate the cellular consequences of the shredding of this chromosome, the impact on meiosis and sperm selection, and the potential to achieve strong female bias in the offspring. The outcome of this study enhances our understanding of the molecular and biological mechanisms behind synthetic sex-ratio distorters in Anopheles mosquitoes, which could inform the development of vector control strategies that target sex ratio. Additionally, we present a genetic sexing strain able to produce mostly females, providing a valuable genetic tool for fundamental studies on this deadly vector.

molecular biology↗

bioRxiv2016

The Reading Frame Surveillance Hypothesis and the Origins of RNAi

Abbreviations\n\nAbstractAn alternative model for protein translation is presented wherein ribosomes utilize a complementary RNA copy of protein coding sequences to monitor the progress of messenger RNAs during their translation to reduce the frequency of frameshifting errors. The synthesis of this framing RNA is postulated to be catalyzed by the small subunit of the ribosome, in the decoding center, by excising and concatemerizing tRNA anticodons bound to each codon of the mRNA template. Various components of the model are supported by previous observations of tRNA mutants that impact ribosomal frameshifting, unique globin-coding RNAs in developing erythroblasts, and the epigenetic, intergenerational transfer of phenotypic traits via mammalian sperm RNA. Confirmation of the proposed translation mechanism is experimentally tractable and might significantly enhance our understanding of several fundamental biological processes.

Molecular Biology↗

bioRxiv2026

PHENOCAUZ: Linking Human Symptoms, Drug Side Effects and Efficacy to Their Molecular Causes Using Mendelian Disease Biology

Human diseases and adverse drug reactions are ultimately recognized through clinical symptoms, yet the molecular determinants of most symptoms remain unknown. To address this key issue, we present PHENOCAUZ, a computational framework that links symptoms to their causative proteins by integrating Mendelian phenotype-gene relationships with molecular features of proteins. Starting from symptom annotations derived from Mendelian phenotypes and their causal genes, PHENOCAUZ identifies biological pathways and processes associated with individual symptoms and trains a machine learning model to predict symptom-causing proteins beyond those currently implicated in Mendelian diseases. The approach is motivated by the hypothesis that if dysfunction of a protein produces a symptom in a Mendelian disorder, the same protein may contribute to the same symptom in a complex disease or cause drug toxicity. Benchmarking across 2,344 symptoms and 4,828 Mendelian proteins using leave-one-out cross-validation yielded an estimated precision of approximately 0.70 among the top predictions. Predicted symptom-protein relationships show strong pathway-level agreement with literature-curated symptom-protein associations, efficacious drug targets and disease mode-of-action proteins. PHENOCAUZ also enables practical applications including prediction of severe drug side effects and identification of candidate therapeutics for ovarian, prostate, and breast cancers as well as noncancer diseases such as dementia and Crohns disease. These results demonstrate that Mendelian disease biology provides a powerful route to connect clinical symptoms with their molecular determinants and translate those insights into drug discovery and safety prediction. Significance StatementClinical symptoms define how diseases and drug side effects are recognized, yet the molecular determinants of most symptoms remain unknown. We introduce PHENOCAUZ, a framework that uses Mendelian disease gene-phenotype relationships to infer the proteins and pathways responsible for human symptoms, by linking symptoms to molecular mechanisms and enabling the prediction of adverse drug reactions and discovery of potential therapeutic targets for both Mendelian and complex diseases.

bioinformatics↗

bioRxiv2020

Transcriptome-wide analysis of expressed resistance gene analogs (RGAs) in mango

Mango is an economically important fruit crop largely cultivated in the (sub)tropics and thus, is constantly challenged by a myriad of insect pests and diseases. Here, we identified and characterized the resistance gene analogs (RGAs) of mango from de novo assembly of transcriptomic sequences. A core RGA database of mango with 747 protein models was established and classified based on conserved domains and motifs: 53 nucleotide binding site proteins (NBS); 27 nucleotide binding site-leucine rich repeat proteins (NBS-LRR); 17 coiled-coil NBS-LRR (CNL); 2 toll/interleukin-1 receptor NBS-LRR (TNL); 29 coiled-coil NBS (CN); 4 toll/interleukin-1 receptor NBS (TN); 17 toll/interleukin-1 receptor with unknown domain (TX); 158 receptor-like proteins (RLP); 362 receptor-like kinases (RLK); 72 transmembrane coiled-coil domain protein (TM-CC), and 6 NBS-encoding proteins with other domains. The various molecular functions, biological processes, and cellular localizations of these RGAs were functionally well-annotated through gene ontology (GO) analysis, and their expression profiles across different mango varieties were also determined. Phylogenetic analysis broadly clustered the core RGAs into 6 major clades based on their domain classification, while TM-CC proteins formed subclades all across the tree. The phylogenetic results suggest highly divergent functions of the RGAs which also provide insights into the mango-pest co-evolutionary arms race. From the mango RGA transcripts, 134 unique EST-SSR loci were identified, and primers were designed targeting these potential markers. To date, this is the most comprehensive analysis of mango RGAs which offer a trove of markers for utilization in resistance breeding of mango.

molecular biology↗

bioRxiv2021

PlotXpress, a webtool for normalization and visualization of reporter expression data

In molecular cell biology, reporter assays are frequently used to investigate gene expression levels. Reporter assays employ a gene that encodes a light-emitting protein, of which the luminescence is quantified as a proxy of gene expression. Commercial parties provide reporter assay kits that include protocols and specialized detection machinery. However, downstream analysis of the output data and their presentation are not standardized. We have developed plotXpress to fill this gap, providing a free, open-source platform for the semi-automated analysis and standardized visualisation of experimental gene reporter data. Users can upload raw luminescence data acquired from a reporter gene assay with an internal control. In plotXpress, the data is corrected for sample variation with the internal control and the average for each condition is calculated. When a reference condition is selected the fold change is calculated for all other conditions, based on the selected reference. The results are shown as dot plots with a statistical summary, which can be adjusted to create publication-grade plots without requiring coding skills. Altogether, plotXpress is an open-source, low-threshold, web-based tool, that promotes a standardized and reproducible analysis while providing an appealing visualization of reporter data. The webtool can be accessed at: https://huygens.science.uva.nl/PlotXpress/ O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/451595v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1b499aborg.highwire.dtl.DTLVardef@1d4d375org.highwire.dtl.DTLVardef@186bac1org.highwire.dtl.DTLVardef@4ed7bc_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2022

Local structural dynamics of alpha-synuclein correlate with aggregation in different physiological conditions

In Parkinsons disease and other synucleinopathies, the intrinsically disordered, presynaptic protein alpha-synuclein misfolds and aggregates. We hypothesise that the exposure of alpha-synuclein to different cellular environments, with different chemical compositions, pH and binding partners, alters its biological and pathological function by inducing changes in molecular conformation. Our custom instrumentation and software enable measurement of the amide hydrogen exchange rates of wild-type alpha-synuclein at amino acid resolution under physiological conditions, mimicking those in the extracellular, intracellular, and lysosomal compartments of cells. We characterised the aggregation kinetics and morphology of the resulting fibrils and correlate these with structural changes in the monomer. Our findings reveal that the C-terminal residues of alpha-synuclein are driving its nucleation and thus its aggregation. Furthermore, the entire NAC region and specific other residues strongly promoted elongation of fibrils. This provides new detail on our current understanding of the relationship between the local chemical environment and monomeric conformations of alpha-synuclein.

molecular biology↗

bioRxiv2024

State of the Interactomes: an evaluation of molecular networks for generating biological insights

Advancements in genomic and proteomic technologies have powered the use of gene and protein networks ("interactomes") for understanding genotype-phenotype translation. However, the proliferation of interactomes complicates the selection of networks for specific applications. Here, we present a comprehensive evaluation of 46 current human interactomes, encompassing protein-protein interactions as well as gene regulatory, signaling, colocalization, and genetic interaction networks. Our analysis shows that large composite networks such as HumanNet, STRING, and FunCoup are most effective for identifying disease genes, while smaller networks such as DIP and SIGNOR demonstrate strong interaction prediction performance. These findings provide a benchmark for interactomes across diverse network biology applications and clarify factors that influence network performance. Furthermore, our evaluation pipeline paves the way for continued assessment of emerging and updated interaction networks in the future.

bioinformatics↗