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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2024

Proteomic Profiling of Mesenchymal Stem Cell-Derived Extracellular Vesicles: Impact of Isolation Methods on Protein Cargo

Extracellular vesicles (EVs) are nanosized vesicles with a lipid bilayer that are secreted by cells and play a critical role in cell-to-cell communication. Despite the promising reports regarding their diagnostic and therapeutic potential, the utilization of EVs in the clinical setting is limited due to insufficient information about their cargo and a lack of standardization in isolation and analysis methods. Considering protein cargos in EVs as key contributors to their therapeutic potency, we conducted a tandem mass tag (TMT) quantitative proteomics analysis of three subpopulations of mesenchymal stem cell (MSC)-derived EVs obtained through three different isolation techniques: ultracentrifugation (UC), high-speed centrifugation (HS), and ultracentrifugation on sucrose cushion (SU). Subsequently, we checked EV marker expression, size distribution, and morphological characterization, followed by bioinformatic analysis. The bioinformatic analysis of the proteome results revealed that these subpopulations exhibit distinct molecular and functional characteristics. The choice of isolation method impacts the proteome of isolated EVs by isolating different subpopulations of EVs. Specifically, EVs isolated through the high-speed centrifugation (HS) method exhibited a higher abundance of ribosomal and mitochondrial proteins. Functional apoptosis assays comparing isolated mitochondria with different EV isolation methods revealed that HS-EVs, but not other EVs, induced early apoptosis in cancer cells. On the other hand, EVs isolated using the sucrose cushion (SU) and ultracentrifugation (UC) methods demonstrated a higher abundance of proteins primarily involved in the immune response, cellLJcell interactions, and extracellular matrix interactions. Our analyses unveil notable disparities in proteins and associated biological functions among EV subpopulations, underscoring the importance of meticulously selecting isolation methods and resultant EV subpopulations based on the intended application.

cell biology↗

bioRxiv2024

Highly accurate metagenome-assembled genomes from human gut microbiota using long-read assembly, binning, and consolidation methods

Long-read metagenomic sequencing is a powerful approach for cataloging the microbial diversity present in complex microbiomes, including the human gut microbiome. We performed a deep-sequencing experiment using PacBio HiFi reads to obtain metagenome-assembled genomes (MAGs) from a pooled human gut microbiome. We performed long-read metagenome assembly using two methods (hifiasm-meta, metMDBG), used improved bioinformatic and proximity ligation binning strategies to cluster contigs and identify MAGs, and developed a novel framework to compare and consolidate MAGs (pb-MAG-mirror). We found proximity ligation binning yielded more MAGs than bioinformatic binning, but our novel comparison framework resulted in higher MAG yields than either binning strategy individually. In total, from 255 Gbp of total HiFi data we produced 595 total MAGs (including 175 high-quality MAGs) using hifiasm-meta, and 547 total MAGs (including 277 high-quality MAGs) with metaMDBG. Hifiasm-meta assembled almost twice as many strain-level MAGs as metaMDBG (246 vs. 156), but both assembly methods produced up to five strains for a species. Approximately 85% of the MAGs were assigned to known species, but we recovered >35 high-quality MAGs that represent uncultured diversity. Based on strict similarity scores, we found 125 MAGs were unequivocally shared across the assembly methods at the strain level, representing [~]22% of the total MAGs recovered per method. Finally, we detected more total viral sequences in the metaMDBG assembly versus the hifiasm-meta assembly ([~]6,700 vs. [~]4,500). Overall, we find the use of HiFi sequencing, improved metagenome assembly methods, and complementary binning strategies is highly effective for rapidly cataloging microbial genomes in complex microbiomes.

microbiology↗

bioRxiv2024

Transposable Element (TE) insertion predictions from RNAseq inputs and TE impact on RNA splicing and gene expression in Drosophila brain transcriptomes.

Recent studies have suggested that Transposable Elements (TEs) residing in introns frequently splice into and alter primary gene coding transcripts. To re-examine the exonization of TEs into protein-coding gene transcripts, we re-analyzed a Drosophila neuron circadian rhythm RNAseq dataset and a deep long RNA fly midbrain RNAseq dataset using our Transposon Insertion and Depletion Analyzer (TIDAL) program. Our TIDAL results were able to predict several TE insertions from RNAseq data that were consistent with previous published studies. However, we also uncovered many discrepancies in TE-exonization calls, such as reads that mainly support intron retention of the TE and little support for chimeric mRNA spliced to the TE. We then deployed rigorous gDNA-PCR and RT-PCR procedures on TE-mRNA fusion candidates to see how many of bioinformatics predictions could be validated. By testing a w1118 strain from which the deeper long RNAseq data was derived from and comparing to an OreR strain, only 9 of 23 TIDAL candidates (<40%) could be validated as a novel TE insertion by gDNA-PCR, indicating that deeper study is needed on using RNAseq as inputs into current TE-insertion prediction programs. Of these validated calls, the RT-PCR results only supported TE-intron retention. Lastly, in the Dscam2 and Bx genes of the w1118 strain that contained intronic TEs, gene expression was 2-3 times higher than the OreR genes lacking the TEs. This studys validation approach indicates that chimeric TE-mRNAs are infrequent and cautions that more optimization is required in bioinformatics programs to call TE insertions using RNAseq datasets.

genetics↗

bioRxiv2024

Identification of ethanol analgesia quantitative trait loci and candidate genes in BXD recombinant inbred mouse lines

Alcohol consumption produces acute analgesic effects, and people experiencing pain conditions may drink alcohol to alleviate discomfort. However, tolerance to the analgesic properties of alcohol could prompt escalating consumption and dependence. Both nociception and alcohol-induced analgesia are under significant genetic control. Understanding the genetic architecture of these processes could inform better treatment options for people with pain conditions. This study aims to identify quantitative trait loci (QTL) driving variation in ethanol-induced analgesia across BXD recombinant inbred mouse lines. Male and female mice from 62 BXD strains received ethanol or saline oral gavage for five days and were tested for hot plate (HP) latency at baseline, Day 1, and Day 5. QTL mapping of HP phenotypes identified a significant provisional QTL on chromosome 17 for Day 1 HP latency in mice receiving ethanol. An additional highly suggestive QTL was present on chromosome 9 for the difference in pre- and post-ethanol thermal nociception. Candidate genes within QTL support intervals were provisionally identified using HP phenotypic correlations to transcriptomic database, expression QTL analysis, and other bioinformatics inquiries. The combined behavioral and bioinformatic analyses yielded strong ethanol analgesia candidate genes, specifically Myo6. Thus, the results of this genetic study of ethanol-induced analgesia in BXD mouse strains may contribute significantly to our understanding of the molecular basis for individual variation in the analgesic response to acute ethanol.

genetics↗

bioRxiv2024

Quantifying microbial DNA in metagenomes improves microbial trait estimation

Shotgun metagenomics is a powerful tool for studying the genomic traits of microbial community members, such as genome size, gene content, etc. While such traits can be used to better understand the ecology and evolution of microbial communities, the accuracy of their estimations can be critically influenced by both known and unknown factors. One factor that can bias trait estimations is the proportion of eukaryotic DNA in a metagenome, as some bioinformatic tools assume that all DNA reads in a metagenome are non-eukaryotic. Here, we help resolve a recent debate about the influence of eukaryotic DNA in the estimation of average genome size from a global soil sample dataset using a new bioinformatic tool. Contrary to what was assumed, our reanalysis of this dataset revealed that soil samples can contain a substantial proportion of eukaryotic DNA ([~]38.8%), which severely inflated average genome size estimates. We report that correcting for this bias significantly improves the statistical support for the negative relationship between average bacterial genome size and soil pH. These results highlight that metagenomes can contain large quantities of eukaryotic DNA, and that new methods that correct for this can improve microbial trait estimation.

microbiology↗

bioRxiv2024

Multiscale regulation of nutrient stress responses in Escherichia coli from chromatin structure to small regulatory RNAs

Recent research has indicated the presence of heterochromatin-like regions of extended protein occupancy and transcriptional silencing of bacterial genomes. We utilized an integrative approach to track chromatin structure and transcription in E. coli K-12 across a wide range of nutrient conditions. In the process, we identified multiple loci which act similarly to facultative heterochromatin in eukaryotes, normally silenced but permitting expression of genes under specific conditions. We also found a strong enrichment of small regulatory RNAs (sRNAs) among the set of differentially expressed transcripts during nutrient stress. Using a newly developed bioinformatic pipeline, the transcription factors regulating sRNA expression were bioinformatically predicted, with experimental follow-up revealing novel relationships for 36 sRNA-transcription factors candidates. Direct regulation of sRNA expression was confirmed by mutational analysis for five sRNAs of metabolic interest: IsrB, CsrB and CsrC, GcvB, and GadY. Our integrative analysis thus reveals additional layers of complexity in the nutrient stress response in E. coli and provides a framework for revealing similar poorly understood regulatory logic in other organisms.

systems biology↗

bioRxiv2024

Integrated single-cell RNA-seq analysis revealed PTN secreted by fibroblasts acting on itself and macrophages via SDC4 ligand in myocardial hypertrophy

BackgroundHypertrophic cardiomyopathy (HCM) is characterized by massive myocardial hypertrophy, which is the most frequent cause of sudden death and can lead to heart failure (HF) or stroke. The objective of this study was to explore the communication network among various cells in the heart of pathological HCM derived from transverse aortic constriction (TAC) mouse model, and investigate the potential mechanism through data mining, biological informatics analysis, and experimental validation. Methods and ResultsThe integrated analyses including CellChat, Seurat, gene ontology (GO), pseudo-time trajectory analysis, and weighted gene co-expression network analysis (WGCNA) were performed based on the single-cell RNA-seq data (scRNA-seq). In vitro tests were conducted to verify bioinformatic analysis findings through enzyme-linked immunosorbent assay (ELISA), real-time quantitative PCR (RT-qPCR), Edu staining, and transwell assay. In vivo tests were also performed to further verify bioinformatic analysis findings by western blot and immunofluorescence assays based on our established TAC mouse model with myocardial hypertrophy. Our results showed that in the heart of TAC mouse, the interaction between cardiac fibroblasts and macrophages was most common, and the increasing pleiotrophin (PTN) secreted by cardiac fibroblasts could promote themselves proliferation or invasion as well as stimulate macrophage activation to release inflammatory cytokines, such as TNF-, IL-6, Cox-2, Cd83, Egr2, and IL-10 through acting on its ligand recombinant Syndecan 4 (SDC4), which may affect cardiomyocyte normal function and eventually cause HCM. This study first demonstrated that PTN derived from cardiac fibroblasts may act on SDC4 to play crucial role in myocardial hypertrophy, which may be a potential therapeutic targets for patients with pathological HCM. ConclusionsIn this study, the complex interaction network between cardiac fibroblasts and macrophages of TAC mice based on the scRNA-seq data was investigated, and we found that the increasing PTN secreted by cardiac fibroblasts under cardiac pressure overload could promote themselves proliferation or invasion as well as stimulate macrophage activation to release inflammatory cytokines through acting on SDC4 ligand, which may affect cardiomyocyte normal function and eventually cause HCM. In addition, our study suggested that PTN derived from cardiac fibroblasts may act on SDC4 ligand to play crucial role in myocardial hypertrophy, which may be a potential therapeutic targets for patients with pathological HCM.

cell biology↗

bioRxiv2024

Human microbiome-derived peptide affects the development of experimental autoimmune encephalomyelitis via molecular mimicry

BackgroundGut commensal microbiota has been identified as a potential environmental risk factor for multiple sclerosis (MS), and numerous studies have linked the commensal microorganism with the onset of MS. However, little is known about the mechanisms underlying the gut microbiome and host-immune system interaction. MethodsWe employed bioinformatics methodologies to identify human microbial-derived peptides by analyzing their similarity to the MHC II-TCR binding patterns of self-antigens. Subsequently, we conducted a range of in vitro and in vivo assays to assess the encephalitogenic potential of these microbial-derived peptides. FindingsWe analyzed 304,246 human microbiome genomes and 103 metagenomes collected from the MS cohort and identified 731 nonredundant analogs of myelin oligodendrocyte glycoprotein peptide 35-55 (MOG35-55). Of note, half of these analogs could bind to MHC II and interact with TCR through structural modeling of the interaction using fine-tuned AlphaFold. Among the 8 selected peptides, the peptide (P3) shows the ability to activate MOG35-55-specific CD4+ T cells in vitro. Furthermore, P3 shows encephalitogenic capacity and has the potential to induce EAE in some animals. Notably, mice immunized with a combination of P3 and MOG35-55 develop severe EAE. Additionally, dendritic cells could process and present P3 to MOG-specific CD4+ T cells and activate these cells. InterpretationOur data suggests the potential involvement of a MOG35-55-mimic peptide derived from the gut microbiota as a molecular trigger of EAE pathogenesis. Our findings offer direct evidence of how microbes can initiate the development of EAE, suggesting a potential microbiome-based therapeutic target for inhibiting the progression of MS. FundingNational Natural Science Foundation of China (82371350 to GY) Research in contextO_ST_ABSEvidence before this studyC_ST_ABSOn July 31, 2024, we conducted a search on PubMed for articles containing the phrases "gut microbiome and multiple sclerosis" and "gut microbiome and experimental autoimmune encephalomyelitis." This search yielded a total of 630 and 151 articles, respectively, indicating that the relationship between gut microbiota and the development of MS and EAE is well established. In contrast, our search for "gut microbiome and molecular mimicry and experimental autoimmune encephalomyelitis" revealed only two review papers, highlighting a significant gap in the literature regarding the role of molecular mimicry in connecting gut microbiome dynamics to the development of EAE. Added value of this studyIn this study, we employed bioinformatics tools to screen for microbial-derived peptides in the gut that potentially cross-react with autoantigen-specific TCR. Our key findings include: 1) Identification of MOG35-55 mimics within the human gut microbiome by employing a combination of TCR-binding footprint screening and prediction model of peptide-MHC II-TCR complexes; 2) Microbial-derived MOG35-55 mimics can cross-react with MOG35-55-specific CD4+ T cells; 3) Among them, peptide 3 predicted from Akkermansia muciniphila can induce moderate EAE in mice; 4) Dendritic cells could process and present peptide 3 to MOG-specific CD4+ T cells and activate these cells. Implications of all the available evidenceThis study suggests the potential involvement of a MOG35-55-mimic peptide derived from the gut microbiota as a molecular trigger of EAE pathogenesis. These data may provide a potential microbiome-based therapeutic target for inhibiting the progression of MS.

immunology↗

bioRxiv2024

Systematically investigating and identifying unmodified bacteriocins in the human gut microbiome

Human gut microbiota produces unmodified bacteriocins, natural antimicrobial peptides that protect against pathogens and regulate host physiology. However, current bioinformatic tools limit the comprehensive investigation of bacteriocins biosynthesis, obstructing research into their biological functions. Here, we introduce IIBacFinder, a superior analysis pipeline for identifying unmodified class II bacteriocins. Through large-scale bioinformatic analysis and experimental validation, we demonstrate their widespread distribution across the bacterial kingdom, with being niche-specific and enriched in the human microbiome. Analyzing over 280,000 bacterial genomes, we reveal the diverse potential of human gut bacteria to produce these bacteriocins. Guided by meta-omics analysis, we synthesized 26 hypothetical bacteriocins from gut commensal species, with 16 showing antibacterial activities. Further ex vivo tests show minimal impact of narrow-spectrum bacteriocins on human fecal microbiota. Our study highlights the huge biosynthetic potential of unmodified bacteriocins in the human gut, paving the way for understanding their biological functions and health implications.

microbiology↗

bioRxiv2024

Probing the eukaryotic microbes of ruminants with a deep-learning classifier and comprehensive protein databases

Metagenomics, particularly genome-resolved metagenomics, has significantly deepened our understanding of microbes, illuminating their taxonomic and functional diversity and roles in ecology, physiology, and evolutions. However, eukaryotic populations within various microbiomes, including those in the mammalian gastrointestinal (GI) tract, remain relatively underexplored in metagenomic studies due to the lack of comprehensive reference genome databases and robust bioinformatics tools. The GI tract of ruminants, particularly the rumen, contains a high eukaryotic biomass although a relatively low diversity of ciliates and fungi, which significantly impact feed digestion, methane emissions, and rumen microbial ecology. In the present study, we developed GutEuk, a bioinformatics tool that improves upon the currently available Tiara and EukRep in accurately identifying metagenome eukaryotic sequences. GutEuk is optimized for high precision across different sequence lengths. It can also distinguish fungal and protozoal sequences, facilitating further elucidation of their unique ecological and physiological impacts. GutEuk was shown to facilitate a comprehensive analysis of protozoa and fungi within more than one thousand rumen metagenomes, revealing a greater genomic diversity among protozoa than previously documented. We further curated several ruminant eukaryotic protein databases, significantly enhancing our ability to distinguish the functional roles of ruminant fungi and protozoa from those of prokaryotes. Overall, the newly developed package GutEuk and its associated databases create new opportunities for in-depth study of GI tract eukaryotes.

microbiology↗

bioRxiv2024

Who Grows There? A Course-based Undergraduate Research Experience to explore the human microbiome through 16S DNA metabarcoding

We describe a two week Course-based Undergraduate Research Experience (CURE) to introduce students to next-generation DNA sequencing, molecular biology methods and a bioinformatic workflow. The CURE is designed to take students with little to no technical and bioinformatic experience through key steps of the protocol through scaffolded laboratory and computational practicals. Our students extract and amplify human microbiome DNA using 16S ribosomal RNA specific primers, then construct a sequencing library for Oxford Nanopore based sequencing. They taxonomically assign the sequencing reads, and determine the ecological community composition using relevant software packages. Our students were able to successfully prepare sequencing libraries and analyse the data to produce relevant figures, demonstrating they met the learning objectives of the CURE. Students identified that they had developed higher level learning as defined by Blooms taxonomy, and that their confidence in practical work significantly increased as a result of doing the CURE. We share recommendations for implementation of the CURE in undergraduate curricula, and adaptations of the methods for use in schools outreach. Our CURE successfully provides training for students in genetic analysis in an enjoyable and relatively time and cost efficient manner, preparing them for future research or careers in modern molecular biology techniques.

scientific communication and education↗

bioRxiv2024

Leaky ribosomal scanning enables tunable translation of bicistronic ORFs in green algae.

Advances in sequencing technology have unveiled examples of nucleus-encoded polycistronic genes, once considered rare. Exclusively polycistronic transcripts are prevalent in green algae, although the mechanism by which multiple polypeptides are translated from a single transcript is unknown. Here, we used bioinformatic and in vivo mutational analyses to evaluate competing mechanistic models for polycistronic expression in green algae. High-confidence manually curated datasets of bicistronic loci from two divergent green algae, Chlamydomonas reinhardtii and Auxenochlorella protothecoides, revealed 1) a preference for weak Kozak-like sequences for ORF 1 and 2) an underrepresentation of potential initiation codons before ORF 2, which are suitable conditions for leaky scanning to allow ORF 2 translation. We used mutational analysis in Auxenochlorella protothecoides to test the mechanism. In vivo manipulation of the ORF 1 Kozak-like sequence and start codon altered reporter expression at ORF 2, with a weaker Kozak-like sequence enhancing expression and a stronger one diminishing it. A synthetic bicistronic dual reporter demonstrated inversely adjustable activity of green fluorescent protein expressed from ORF 1 and luciferase from ORF 2, depending on the strength of the ORF 1 Kozak-like sequence. Our findings demonstrate that translation of multiple ORFs in green algal bicistronic transcripts is consistent with episodic leaky ribosome scanning of ORF 1 to allow translation at ORF 2. This work has implications for the potential functionality of upstream open reading frames found across eukaryotic genomes and for transgene expression in synthetic biology applications. Significance StatementTextbook dogma states that nucleus-encoded genes are monocistronic, producing transcripts with a single translated open reading frame. However, highly conserved bicistronic loci are pervasive in green algae that are separated by several hundred million years of evolution, speaking to their ancestral origins and functions within the Chlorophyte lineage. A combination of bioinformatic analysis and in vivo gene manipulation supports leaky ribosomal scanning as the primary mechanism for translation of multiple ORFs from bicistronic transcripts. We have successfully tuned synthesis levels of two proteins encoded on one mRNA by modifying the ORF 1 Kozak-like sequence. These findings may have broad applications in synthetic biology.

plant biology↗

bioRxiv2024

Modulation of Electrostatic Interactions as a Mechanism of Cryptic Adaptation of Colwellia to High Hydrostatic Pressure

The role of various interactions in determining the pressure adaptation of the proteome in piezophilic organisms remains to be established. It is clear that the adaptation is not limited to one or two proteins, but has a more general evolution of the characteristics of the entire proteome, the so-called cryptic evolution. Using the synergy between bioinformatics, computer simulations, and some experimental evidence, we probed the physico-chemical mechanisms of cryptic evolution of the proteome of psychrophilic strains of model organism, Colwellia, to adapt to life at various pressures, from the surface of the Arctic ice to the depth of the Mariana Trench. From the bioinformatics analysis of proteomes of several strains of Colwellia, we have identified the modulation of interactions between charged residues as a possible driver of evolutionary adaptation to high hydrostatic pressure. The computational modeling suggests that these interactions have different roles in modulating the function-stability relationship for different protein families. For several classes of proteins, the modulation of interactions between charges evolved to lead to an increase in stability with pressure, while for others, just the opposite is observed. The latter trend appears to benefit enzyme activity by countering structural rigidification due to the high pressure.

biophysics↗

bioRxiv2024

Seeing or believing in hyperplexed spatial proteomics via antibodies. New and old biases for an image-based technology.

Hyperplexed in-situ targeted proteomics via antibody immunodetection (i.e. > 15 markers) is changing how we classify cells and tissues. Differently from other high-dimensional single-cell assays (flow cytometry, single cell RNA sequencing), the human eye is a necessary component in multiple procedural steps: image segmentation, signal thresholding, antibody validation and iconographic rendering. Established methods complement the human image evaluation, but may carry undisclosed biases in such a new context, therefore we re-evaluate all the steps in hyperplexed proteomics. We found that the human eye can discriminate less than 64 out of 256 gray levels and has limitations in discriminating luminance levels in conventional histology images. Furthermore, only images containing visible signals are selected and eye-guided digital thresholding separates signal from noise. BRAQUE, a hyperplexed proteomic tool, can extract, in a marker-agnostic fashion, granular information from markers which have a very low signal-to-noise ratio and therefore are not visualized by traditional visual rendering. By analyzing a public human lymph node dataset, we also found unpredicted staining results by validated antibodies, which highlight the need to upgrade the definition of antibody specificity in hyperplexed immunostaining. Spatially hyperplexed methods upgrade and supplant traditional image-based analysis of tissue immunostaining, beyond the human eye contribution. IMPACT STATEMENTStaining with multiple biomarkers a single tissue section, multiplex staining, is changing how we examine in-situ normalcy, pathology and the interrelationship of good and bad biological actors. Bioinformatic pipelines developed to deal with high-dimensional datasets such as single cell RNA sequencing or multiparameter flow-cytometry have been adapted to analogous types of data derived from tissue, and co-exist with conventional image analysis tools and human eye-guided image evaluation. We wanted to evaluate if multiplex staining with more than 15 markers (hyperplexed) has comparable sensitivity to conventional image analysis and if these latter analysis tools carry undisclosed biases and should not be used together with hyperplexed staining. We found that the human eye has a reduced discriminative power for grayscale and luminance levels compared to the 8-bit available spectrum, affecting positive signal recognition above the noise. We also found that the granular analytical power of recent bioinformatic pipelines can extract information from images which defy human eye perception and deliver information unattainable with existing image analysis tools for single-stain images.

systems biology↗

bioRxiv2024

Investigating the role of axonal localization of sex peptide receptor in post-mating responses of female Drosophila melanogaster

This study elucidates the molecular mechanisms underlying the axonal localization of the sex peptide receptor, a pivotal G-protein coupled receptor in the Drosophila melanogaster post-mating response cascade. Utilizing transgenic expression, neuronal labeling, and bioinformatics analyses, we demonstrate that the N-terminal domain of SPR is indispensable for its axonal targeting in both Drosophila larval ventral nerve cord neurons and mouse hippocampal neurons. Deletion of the N-terminal domain abolished axonal localization, highlighting its critical role in this process. Intriguingly, the C-terminal domain of SPR appears to play a subordinate role in axonal targeting. Bioinformatical analysis revealed a striking homology between the N-terminus of SPR and the Broad-complex, Tramtrack, and Bric-a-brac/poxvirus and zinc finger family of proteins. The BTB domain, a conserved protein-protein interaction domain within this family, is implicated in diverse cellular processes and axonal targeting. Further investigation into the role of the BTB domain-like region in SPR could provide valuable insights into the molecular underpinnings of axonal targeting and post-mating responses in Drosophila. This research contributes to our understanding of the intricate mechanisms governing GPCR localization and function in the context of reproductive biology and neuronal signaling.

neuroscience↗

bioRxiv2024

ANALYSIS OF RESPIRATORY SYNCYTIAL VIRUS REVEALS CONSERVED RNA SECONDARY STRUCTURAL MOTIFS AND IMPACT VIRAL LIFECYCLE

An analysis that combined bioinformatics, comparative sequence/structural analysis, and experimental assays has been completed on respiratory syncytial virus (RSV). Both the genomic RNA and its reverse complement were studied using the novel bioinformatics pipeline ScanFold, which predicted 49 regions on RSV RNAs that appear to encode functional secondary structures (based on their unusually stable sequence order). Multiple motifs appear to be conserved between RSV and related virus strains, including one region within the F gene, which had a highly favorable overall prediction metric of a paired secondary structure. This motif was subjected to additional experimental analyses using SHAPE analysis to confirm ScanFold predicted secondary structure. In subsequent analysis, RSV F mRNA transcripts were made by in vitro transcription using T7 polymerase and transcripts which relaxed the predicted secondary structure yielded slightly higher mRNA transcripts and protein expression levels as wildtype F. However, using reverse genetics for comparison of viruses containing wildtype or relaxed F suggested that the predicted secondary structures may be critical for RSV replication in cells. To our knowledge, this is the first study to examine conserved RNA structures across multiple RSV strains and may help identify potential therapeutic targets to inhibit.

microbiology↗

bioRxiv2024

Experimental capture of genomic islands defines a widespread class of genetic element capable of non-autonomous transfer

Bacteria acquire new genes by horizontal gene transfer (HGT), typically mediated by mobile genetic elements (MGEs). While plasmids, bacteriophages and certain integrative and conjugative elements (ICEs) are well characterized, the broader diversity of MGEs remains poorly understood. Here, we propagated the bacterium Pseudomonas fluorescens SBW25 in the presence of filtrate obtained from garden compost communities. Genome sequencing of derived colonies revealed acquisition of three different mobile elements, each integrated immediately downstream of tmRNA, flanked by direct repeats, and encoding a tyrosine integrase (intY) and putative phage defense systems. Absent are genes with recognized roles in autonomous transfer. Interrogation of DNA sequence databases showed that similar elements are widespread in the genus Pseudomonas and beyond, with Vibrio Pathogenicity Island-1 (VPI-1) from V. cholerae as a notable example. Bioinformatic analyses demonstrate frequent horizontal transfer among diverse hosts. Detailed analysis of a single element, I55, showed that it is transferred between cells by a jumbo phage, and confers a fitness benefit via a type II restriction-modification system. Significance StatementThe impact of horizontal gene transfer on the evolution of bacteria outpaces that driven by spontaneous mutation, but knowledge of the range of mediators, the genes mobilized, and the mechanisms of movement have largely depended on inferences stemming from bioinformatics. Here we describe a real-time evolution experiment in which a single focal strain propagated with filtrate from a complex microbial community captured genetic elements carrying a diverse cargo of genes whose mobility was previously uncharacterized. The elements represent a widespread class of mobile DNA dependent only on a tyrosine integrase targeting a highly conserved genomic site. Genetic analysis of one element shows that it confers a significant fitness advantage via defense against bacteriophages, and hijacks a jumbo bacteriophage for intercellular transfer. Our findings reveal new insights into the hidden diversity and dynamics of MGEs in natural environments. ClassificationBiological Sciences / Microbiology

microbiology↗

bioRxiv2024

Evaluating Cross-linking-driven integrative modeling in peptide-HLAII complexes prediction with insights for refining predictive accuracy

ABSTRACTIn silico prediction of peptide-HLAII (human leucocyte antigen class II) complexes has emerged as a crucial approach in bioinformatics for deciphering antigen presentation mechanisms. Several in silico tools have been developed to predict peptide binding to HLAII alleles, trying to deconvolute the intricate peptide-HLAII binding specificity. These approaches integrate bases from molecular modeling, machine learning, and bioinformatics to predict peptide-HLAII interactions. Initially, structure-based methods relying on molecular docking algorithms were widespread, utilizing structural data of HLAII molecules and peptides to infer plausible binding conformations. These methods often faced challenges in accuracy due to the dynamic nature of peptide-HLAII interactions. Besides, the high flexibility of peptide sidechains makes their placement into the HLA-binding site even more complex. In recent years, machine learning techniques have drawn attention to peptide-HLAII binding predictions. Supervised learning algorithms, such as support vector machines (SVMs), neural networks, and ensemble methods, have been considerably applied to discriminate patterns from large datasets of experimentally validated peptide-HLAII binding affinities (like Immune Epitope Data Base, IEDB) and more recently mass spectrometry- eluted ligands from MHC-associated peptide proteomics (MAPPs) assay. The role of experiment- assisted integrative modeling in aiding peptide-HLAII complexes prediction still needs to be clarified. In this work, we benchmarked the use of AlphaLink2 (AlphaFold2 + cross-links restraints) and compared it to AlphaFold2 Multimer in predicting correct peptide binding motifs. These results can pave the way to an integrated strategy for vaccine development and protein deimmunization or autoimmunity mitigation.

immunology↗