Biology subjects

Yadav, A.

Publications and source records attributed to Yadav, A..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

Zinc nano-fertilization enhances wheat productivity and biofortification

Zinc (Zn) malnutrition has emerged as one of the major health challenges in developing nations across the globe. Development of Zn management protocols in staple food crops using modern scientific tools to enhance Zn concentration in grains along with augmented crop yields became utmost necessary. In this context a 2-year experiment was carried out to assess the effects of zinc oxide nanoparticles (ZnO-NPs) vis-a-vis bulk zinc sulfate (ZnSO4) on wheat growth, yield and Zn concentration in plant parts. Four levels of application of ZnO-NPs (0, 20, 25 and 30 mg kg-1) were compared with ZnSO4 (equal to Zinc concentration in ZnO-NPs). Results revealed that seed vigor was significantly (p <0.05) higher under 25 and 30 mg kg-1 soil ZnO-NPs treatments over ZnSO4. Among the crop yield parameters such as tillers (plant-1), grain weight (plant-1), biomass (plant-1) and grain yield were significantly (p <0.05) higher under ZnO-NPs 25 mg kg-1 treated soil as compared to any other treatment. Zinc concentration in grains increased with dose of ZnO-NPs and it was significantly more than ZnSO4 treated soil at each treatment level. ZnO-NPs and ZnSO4 treatments did not affect photosynthetic rate and chlorophyll (SPAD) content significantly. In conclusion, 25 mg kg-1 ZnO-NPs application could be recommended in wheat cultivation to improve growth, yield and grain Zn biofortification.

plant biology↗

bioRxiv2022

Structural, functional and evolutionary analysis of wheat WRKY45 protein: A combined bioinformatics and MD simulation approach

Bread wheat (Triticum aestivum L.) is the worlds second-most important cereal crop, as well as Indias. It is an allohexaploid composed of three homeologous sub-genomes (AA, BB, and DD), which is a constraint in determining the complete genome sequence. Several transcription factors have been implicated in both abiotic and biotic stress. WRKY transcription factors are among the best characterised in the context of pathogen defence mechanisms. Different members of the WRKY transcription factors have been shown to confer resistance to stress. But very little is known about the wheat WRKY transcription factors. In silico analysis of the TaWRKY45 protein was performed in the present study using several bioinformatics tools like motif scan, CD search, Netphos, NGlycos, GRAVY, and the SWISS MODEL. The study revealed that TaWRKY45 belongs to the group III family and contains hydrophilic proteins with 19 potential phosphorylation sites. TaWRKY45 protein was found to be orthologous to rice OsWRKY45 by phylogenetic analysis. The catalytic domain was analysed by motif scan which showed that TaWRKY45 has one WRKY domain and a C2-HC zinc finger motif. TaWRKY45s structure was determined to be more stable, more constrained, more compact, and have greater potential to interact with other molecules than OsWRKY45, according to MD simulation analysis. Thus, in silico analysis of transcription factors helps study protein function, interaction, and regulatory pathways.

bioinformatics↗

bioRxiv2022

A novel fluorobenzothiazole RBx 10080758 as a dual inhibitor against bacterial GyraseB (GyrB) and Topoisomerase IV (parE) of Gram-positive pathogens causing skin and respiratory infections

Development of a novel inhibitor targeting Gyrase B and Topoisomerase IV offers a potential opportunity to combat the drug resistance. In the present study, we extensively investigated the efficacy of RBx 10080758, a novel fluorobenzothiazole, against skin and respiratory infections caused by Staphylococci and Streptococci in in vitro and in vivo models. RBx 10080758 showed a potent IC50 of 0.06 M against Gyrase and Topoisomerase IV and also exhibited a strong whole cell in vitro activity with MIC ranges of 0.015-0.06, 0.015-0.03, 0.008-0.03, 0.008-0.03, 0.008-0.0.06, 0.015-0.06 g/ml against Staphylococcus. aureus, Streptococcus pneumoniae, Coagulase negative Staphylococci, Streptococcus viridans, Streptococcus pyogenes and Enterococcus, respectively. As expected from the novel class of molecule, it retains potent even against linezolid and vancomycin resistant strains. Interesting, in mouse systemic infection 10 mg/kg, IV dose protected 100% mice from lethal infections. In rat thigh infection model with MRSA WCUH29 at 45 mg/kg exhibited >3-log10 cfu reduction in thigh muscles. RBx 10080758 displayed potent in vitro and in vivo activity against a panel of MDR Gram-positive bacteria. As a novel chemical class, the fluorobenzothiazoles have the potential to become clinically viable antibiotics, to address the drug resistance problem by its unique dual targeting mechanism of action.

microbiology↗

bioRxiv2022

Targeting MALAT1 Augments Sensitivity to PARP Inhibition by Impairing Homologous Recombination in Prostate Cancer.

Poly(ADP-ribose) polymerase inhibitors (PARPi) have emerged as the most promising targeted therapeutic intervention for the treatment of metastatic castrate-resistant prostate cancer (mCRPC). However, the clinical utility of PARPi has been limited to a subset of patients who harbor aberrations in the homologous recombination (HR) pathway. Here, we report that targeting MALAT1, an oncogenic lncRNA, known to be elevated in advanced-stage prostate cancer (PCa) demonstrates contextual synthetic lethality with PARPi. We show that MALAT1 silencing reprograms the HR transcriptome, contriving BRCAness-like phenotype, thus enhancing sensitivity towards PARPi. Moreover, transcriptome profiles of mCRPC patients exhibit convergence between expression of MALAT1, HR pathway, and neuroendocrine markers. Mechanistically, we show that targeting MALAT1 leads to a decrease in EZH2, a member of polycomb repressor complex-2 (PRC2), which in turn upregulates the expression of RE1 Silencing Transcription Factor (REST), a key repressor of neuroendocrine differentiation. Overall, we showed that MALAT1 plays a pivotal role in maintaining genomic integrity, thereby promoting disease progression. Conclusively, our findings suggest that inhibiting MALAT1 confers PARPi sensitization in patients resistant to anti-androgens and conventional chemotherapeutics. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=195 SRC="FIGDIR/small/494272v1_ufig1.gif" ALT="Figure 1"> View larger version (70K): org.highwire.dtl.DTLVardef@80d842org.highwire.dtl.DTLVardef@f60793org.highwire.dtl.DTLVardef@6b81eforg.highwire.dtl.DTLVardef@1fa35d_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstract:C_FLOATNO The oncogenic lncRNA MALAT1 exhibits functional pleiotropy in PCa and promotes neuroendocrine differentiation. MALAT1 fosters PCa progression by modulating several hallmark oncogenic properties, such as malignant transformation, enhanced migratory capabilities, stemness, and ultimately contributes to drug resistance. MALAT1 enhances the transcriptional regulation of genes associated with homologous recombination thereby having a profound impact on the genome integrity in metastatic prostate cancer. Over the course of disease progression, it also promotes neuroendocrine trans-differentiation by depleting the levels of REST, the key repressor for NE transdifferentiation in prostate cancer. C_FIG

cancer biology↗

bioRxiv2022

The Human Motoneuron Expression Signature is Defined by ALS-Related Genes

The mammalian spinal cord functions as a community of glial and neuronal cell types to accomplish sensory processing, autonomic control, and movement; conversely, the dysfunction of these cell types following spinal cord injury or disease states can lead to chronic pain, paralysis, and death. While we have made great strides in understanding spinal cellular diversity in animal models, it is crucial to characterize human biology directly to uncover specialized features of basic function and to illuminate human pathology. Here, we present a cellular taxonomy of the adult human spinal cord using single nucleus RNA-sequencing with spatial transcriptomics and antibody validation. We observed 29 glial clusters, including rare cell types such as ependymal cells, and 35 neuronal clusters, which we found are organized principally by anatomical location. To demonstrate the potential of this resource for understanding human disease, we analyzed the transcriptome of spinal motoneurons that are prone to degeneration in amyotrophic lateral sclerosis (ALS) and other diseases. We found that, compared with all other spinal neurons, human motoneurons are defined by genes related to cell size, cytoskeletal structure, and ALS, thereby supporting a model of a specialized motoneuron molecular repertoire that underlies their selective vulnerability to disease. We include a publicly available browsable web resource with this work, in the hope that it will catalyze future discoveries about human spinal cord biology.

neuroscience↗

bioRxiv2022

Optimized transcriptional signature for evaluation of MEK/ERK pathway baseline activity and long-term modulations in ovarian cancer

Ovarian cancer is the most aggressive and lethal of all gynecologic malignancies. High activity of the MEK/ERK signaling pathway is tightly associated with tumor growth, high recurrence rate, and treatment resistance. Several transcriptional signatures were proposed recently for evaluation of MEK/ERK activity in tumor tissue. In the present study, we validated the performance of a robust multi-cancer MPAS 10-gene signature in various experimental models and publicly available sets of ovarian cancer samples. Expression of four MPAS genes (PHLDA1, DUSP4, EPHA2, and SPRY4) displayed reproducible responses to MEK/ERK activity modulations across several experimental models in vitro and in vivo. Levels of PHLDA1, DUSP4, and EPHA2 expression were also significantly associated with baseline levels of MEK/ERK pathway activity in multiple human ovarian cancer cell lines and ovarian cancer patient samples available from the TCGA database. High EPHA2 expression, platinum therapy resistance, and advanced age at diagnosis were associated with poor overall patient survival. Taken together, our results demonstrate that performance of transcriptional signatures is significantly affected by tissue specificity and aspects of particular experimental models. We therefore propose that gene expression signatures derived from comprehensive multi-cancer studies should be always validated for each cancer type.

cancer biology↗

bioRxiv2021

Brain Data Standards Ontology: A data-driven ontology of transcriptomically defined cell types in the primary motor cortex

Large-scale single-cell omics profiling is revolutionising our understanding of cell types in complex organs like the brain, where it is being used to define a complete catalogue of cell types, something that traditional methods struggle with due to the diversity and complexity of the brain. But this poses a problem. How do we organise such a catalogue - providing a standard way to refer to the cell types discovered, linking their classification and properties to supporting data? Cell ontologies provide a solution to recording definitions, classifications, and properties of cell types and provide standard identifiers for annotation, but they currently do not support the data driven cell type definitions and classifications needed for multi-modal single cell omics profiling. Here we describe the construction and application of a semi-automated, data-linked extension to the Cell Ontology that represents cell types in the Primary Motor Cortex of humans, mice and marmosets. The methods and resulting ontology are designed to be scalable and applicable to similar whole brain atlases currently in preparation.

neuroscience↗

bioRxiv2021

Seeing the unseen: A trifoliate (MYB117) mutant allele fortifies folate and carotenoids in tomato fruits

Micronutrient deficiency also termed hidden hunger affects a large segment of the human population, particularly in developing and underdeveloped nations. Tomato the second most consumed vegetable crop in the world after potato can serve as a sustainable source to alleviate micronutrient deficiency. In tomato, the mutations in the R2R3-MYB117 transcription factor elicit trifoliate leaves and initiate axillary meristems; however, its effect on fruit metabolome remains unexplored. The fruits of a new trifoliate (tf) allele (tf-5) were firmer, had higher {degrees}Brix, folate, and carotenoids. The transcriptome, proteome, and metabolome profiling of tf-5 reflected a broad-spectrum change in homeostasis. The tf-5 allele enhanced the fruit firmness by suppressing cell wall softening-related proteins. The tf-5 fruit displayed a substantial increase in aminome, particularly {gamma}-aminobutyric acid, with a parallel reduction in aminoacyl t-RNA synthases. The increased lipoxygenases proteins and transcripts seemingly elevated jasmonic acid. In addition, increased abscisic acid hydrolases transcripts coupled with reduced precursor supply lowered abscisic acid. The upregulation of carotenoids was mediated by modulation of methylerythreitol and plastoquinone pathways along with an increase in carotenoids isomerization proteins. The upregulation of folate in tf-5 was connoted by the increase in precursor p-aminobenzoic acid and transcripts of several folate biosynthesis pathway genes. The reduction in pterin-6-carboxylate and {gamma}-glutamyl hydrolase activity indicated that the diminished folate degradation also enriched folate levels. Our study delineates that introgression of the tf-5 can be used for the {gamma}-aminobutyric acid, carotenoids, and folate fortification of tomato. One-sentence summaryA tomato trifoliate allele encoding a truncated MYB117 transcription factor alters cellular homeostasis and fortifies {gamma}-aminobutyric acid, folate, and carotenoids in tomato fruits.

plant biology↗

bioRxiv2021

ProMetheusDB: an in-depth analysis of the high-quality human methyl-proteome

Protein Arginine (R) methylation is a post-translational modification involved in various biological processes, such as RNA splicing, DNA repair, immune response, signal transduction, and tumour development. Although several advancements were made in the study of this modification by mass spectrometry, researchers still face the problem of a high false discovery rate. We present a dataset of high-quality methylations obtained from several different heavy methyl SILAC (hmSILAC) experiments analysed with a machine learning-based tool doublets and show that this model allows for improved high-confidence identification of real methyl-peptides. Overall, our results are consistent with the notion that protein R methylation modulates protein:RNA interactions and suggest a role in rewiring protein:protein interactions, for which we provide experimental evidence for a representative case (i.e. NONO:PSPC1). Upon intersecting our R-methyl-sites dataset with a phosphosites dataset, we observed that R methylation correlates differently with S/T-Y phosphorylation in response to various stimuli. Finally, we explored the application of hmSILAC to identify unconventional methylated residues and successfully identified novel histone methylation marks on Serine 28 and Threonine 32 of H3.

bioinformatics↗

bioRxiv2021

A-GHN: Attention-based Fusion of Multiple GraphHeat Networks for Structural to Functional Brain Mapping

Over the last decade, there has been growing interest in learning the mapping from structural connectivity (SC) to functional connectivity (FC) of the brain. The spontaneous fluctuations of the brain activity during the restingstate as captured by functional MRI (rsfMRI) contain rich non-stationary dynamics over a relatively fixed structural connectome. Among the modeling approaches, graph diffusion-based methods with single and multiple diffusion kernels approximating static or dynamic functional connectivity have shown promise in predicting the FC given the SC. However, these methods are computationally expensive, not scalable, and fail to capture the complex dynamics underlying the whole process. Recently, deep learning methods such as GraphHeat networks along with graph diffusion have been shown to handle complex relational structures while preserving global information. In this paper, we propose a novel attention-based fusion of multiple GraphHeat networks (A-GHN) for mapping SC-FC. A-GHN enables us to model multiple heat kernel diffusion over the brain graph for approximating the complex Reaction Diffusion phenomenon. We argue that the proposed deep learning method overcomes the scalability and computational inefficiency issues but can still learn the SC-FC mapping successfully. Training and testing were done using the rsfMRI data of 100 participants from the human connectome project (HCP), and the results establish the viability of the proposed model. Furthermore, experiments demonstrate that A-GHN outperforms the existing methods in learning the complex nature of human brain function.

neuroscience↗

bioRxiv2021

Identification and Targeting Putative G-Quadruplex Sequences in Candida glabrata: A Route to Virulence and Pathogenesis Control?

An increase in the number of Candida species that are resistant to antifungal medication and increases worldwide. Even individuals that are never exposed to antibiotics showing resistance to antifungal drugs. The increase in resistant candida species strains requires a search for novel targets for new antifungal agents. Preventing infection caused by candida species is a tremendous challenge in medicine. Although availability and use of antifungal drugs, disseminated candidiasis leads to a high mortality rate of about 40-60%, poor diagnosis, and improper disease management. Interest in G-quadruplexes as a therapeutic target has been increased in recent years, following the implication of this non-canonical G-quadruplex secondary structure in pathological diseases. However, G-quadruplex has been reported in many pathogens contributing to virulence and pathogenesis, including bacterial pathogens such as Staphylcoccus aureus and Enterococcus spp. Etc, viruses such as SARS-CoV2, HIV, HPV etc., and Fungi such as Candida species, Aspergillus fumigatus, etc. The present aim of the study is to identify and targeting G-Quadruplex forming sequences present in the Candida glabrata. PQSFinder (R Package) identified more than 5000 putative G-quadruplex forming sequences. Out of these, we have used PQS present in the SDH1 gene of Candida glabrata. It may be a key target to ameliorate the C.glabrata infection because it encodes a protein that plays a vital role in energy production in C.glabrata cells shown in the figure. The structure was built based on the already current structure that is telomeric G4 AGGG (TTAGGG)3 {PDB ID-4G0F} for identifying its stabilization by Gold carbine derivatives. Molecular docking and ADMET analysis show that Compound A has the highest binding affinity and has the best ADMET properties among the two compounds. The present study represents PQS in the SDH1 gene could be a novel antifungal target.

bioinformatics↗

bioRxiv2021

Genomic analysis of family UBA6911 (Group 18 Acidobacteria) expands the metabolic capacities of the phylum and highlights adaptations to terrestrial habitats

Approaches for recovering and analyzing genomes belonging to novel, hitherto unexplored bacterial lineages have provided invaluable insights into the metabolic capabilities and ecological roles of yet-uncultured taxa. The phylum Acidobacteria is one of the most prevalent and ecologically successful lineages on earth yet, currently, multiple lineages within this phylum remain unexplored. Here, we utilize genomes recovered from Zodletone spring, an anaerobic sulfide and sulfur-rich spring in southwestern Oklahoma, as well as from multiple disparate soil and non-soil habitats, to examine the metabolic capabilities and ecological role of members of the family UBA6911 (group18) Acidobacteria. The analyzed genomes clustered into five distinct genera, with genera Gp18_AA60 and QHZH01 recovered from soils, genus Ga0209509 from anaerobic digestors, and genera Ga0212092 and UBA6911 from freshwater habitats. All genomes analyzed suggested that members of Acidobacteria group 18 are metabolically versatile heterotrophs capable of utilizing a wide range of proteins, amino acids, and sugars as carbon sources, possess respiratory and fermentative capacities, and display few auxotrophies. Soil-dwelling genera were characterized by larger genome sizes, higher number of CRISPR loci, an expanded carbohydrate active enzyme (CAZyme) machinery enabling de-branching of specific sugars from polymers, possession of a C1 (methanol and methylamine) degradation machinery, and a sole dependence on aerobic respiration. In contrast, non-soil genomes encoded a more versatile respiratory capacity for oxygen, nitrite, sulfate, trimethylamine N-oxide (TMAO) respiration, as well as the potential for utilizing the Wood Ljungdahl (WL) pathway as an electron sink during heterotrophic growth. Our results not only expand our knowledge of the metabolism of a yet-uncultured bacterial lineage, but also provide interesting clues on how terrestrialization and niche adaptation drives metabolic specialization within the Acidobacteria. ImportanceMembers of the Acidobacteria are important players in global biogeochemical cycles, especially in soils. A wide range of Acidobacterial lineages remain currently unexplored. We present a detailed genomic characterization of genomes belonging to the family UBA6911 (also known as group 18) within the phylum Acidobacteria. The genomes belong to different genera and were obtained from soil (genera Gp18_AA60 and QHZH01), freshwater habitats (genera Ga0212092 and UBA6911), and anaerobic digestor (Genus Ga0209509). While all members of the family shared common metabolic features, e.g. heterotrophic respiratory abilities, broad substrate utilization capacities, and few auxotrophies; distinct differences between soil and non-soil genera were observed. Soil genera were characterized by expanded genomes, higher numbers of CRISPR loci, larger carbohydrate active enzyme (CAZyme) repertoire enabling monomer extractions from polymer side chains, and methylotrophic (methanol and methylamine) degradation capacities. In contrast, non-soil genera encoded more versatile respiratory capacities for utilizing nitrite, sulfate, TMAO, and the WL pathway, in addition to oxygen as electron acceptors. Our results not only broaden our understanding of the metabolic capacities within the Acidobacteria, but also, provide interesting clues on how terrestrialization shaped Acidobacteria evolution and niche adaptation.

microbiology↗

bioRxiv2021

The males of the parasitoid wasp, Nasonia vitripennis, can identify which fly hosts contain females.

The reproductive success of a male is limited by the number of females it can mate with. Thus, males deploy elaborate mate-finding strategies to maximize access to females. In the haplodiploid wasp genus, Nasonia, which are parasitoids of cyclorrhaphous flies, mate-finding is restricted to the natal patch, where males compete for access to females. This study investigates whether there are any additional mate finding strategies of males, especially, whether they can identify the presence of adult females which are still inside the fly host. Results reveal that only one out of the four species, N. vitripennis, can distinguish which hosts specifically have adult female wasps indicating a species-specific unique mate-finding capability. Behavioral assays revealed that the cues used by N. vitripennis males are olfactory in nature and not auditory or visual. GC-MS analyses show that these olfactory cues are female-specific cuticular hydrocarbons (CHCs), possibly emanating from within the fly puparium. Further assays indicated that N. vitripennis males can also detect differences in the concentrations of compounds to identify female-specific cues from male-specific ones. This study, therefore, uncovers a previously unknown mate-finding strategy in one of the most widely studied parasitoid wasp.

ecology↗

bioRxiv2021

Binary Interactome Models of Inner- Versus Outer-Complexome Organization

Hundreds of different protein complexes that perform important functions across all cellular processes, collectively comprising the "complexome" of an organism, have been identified1. However, less is known about the fraction of the interactome that exists outside the complexome, in the "outer-complexome". To investigate features of "inner"- versus outer-complexome organisation in yeast, we generated a high-quality atlas of binary protein-protein interactions (PPIs), combining three previous maps2-4 and a new reference all-by-all binary interactome map. A greater proportion of interactions in our map are in the outer-complexome, in comparison to those found by affinity purification followed by mass spectrometry5-7 or in literature curated datasets8-11. In addition, recent advances in deep learning predictions of PPI structures12 mirror the existing experimentally resolved structures in being largely focused on the inner complexome and missing most interactions in the outer-complexome. Our new PPI network suggests that the outer-complexome contains considerably more PPIs than the inner-complexome, and integration with functional similarity networks13-15 reveals that interactions in the inner-complexome are highly detectable and correspond to pairs of proteins with high functional similarity, while proteins connected by more transient, harder-to-detect interactions in the outer-complexome, exhibit higher functional heterogeneity.

systems biology↗

bioRxiv2021

Elucidating biosynthetic pathway of piperine using comparative transcriptome analysis of leaves, root, and spike in Piper longum L.

Piper longum (Pipli; Piperaceae) is an important spice valued for its pungent alkaloids, especially piperine. Albeit, its importance, the mechanism of piperine biosynthesis is still poorly understood. The Next Generation Sequencing (NGS) for P. longum leaves, root and spikes was performed using Illumina platform, which generated 16901456, 54993496 and 22900035, respectively of high quality reads. In de novo assembly P. longum 173381 numbers of transcripts were analyzed. Analysis of transcriptome data from leaf, root and spike showed gene families that were involved in the biosynthetic pathway of piperine and other secondary metabolites. To validate differential expression of the identified genes, 27 genes were randomly selected to confirm the expression level by quantitative real time PCR (qRT-PCR) based on the up regulation and down regulation of differentially expressed genes obtained through comparative transcriptome analysis of leaves and spike of P. longum. With the help of UniProt database the function of all characterized genes was generated.

plant biology↗

bioRxiv2020

Validating gene-phenotype associations using relationships in the UMLS

ObjectiveLarge scale next-generation sequencing of population cohorts paired with patients electronic health records (EHR) provides an excellent resource for the study of gene-disease associations. To validate those associations, researchers often consult databases that identify relationships between genes of interest and relevant disease phenotypes, which we refer to as simply "phenotypes". However, most of these databases contain phenotypes that are not suited for automated analysis of EHR data, which often captured these phenotypes in the form of International Classification of Diseases (ICD) codes. There is a need for a resource that comprehensively provides gene-phenotype mappings in a format that can be used to evaluate phenotypes from EHR. MethodsWe built a directed graph database of genes, medical concepts and ICD codes based on a subset of the National Library of Medicines Unified Medical Language System (UMLS) and other resources. To obtain associations between genes and ICD codes, we traversed the defined relationships from gene, variant and disease concepts to ICD codes, resulting in a set of mappings that link specific genes and variants to these ICD codes. ResultsOur method created 249,764 mappings between genes and ICD codes, including 27,226 "disease" phenotypes and 222,538 "symptom" phenotypes, and provided mappings for 4,456 unique genes. Paths were validated by manual review of a diverse sample of paths. In a cohort of 92,455 samples, we used these mappings to validate gene-phenotype associations in 32,786 samples where a person had a potentially disease-causing genetic mutation and at least one corresponding diagnosis in their EHR. ConclusionThe concepts and relationships in the UMLS can be used to generate gene-ICD phenotype mappings that are not explicit in the source vocabularies. We were able use these mappings to validate gene-disease associations in a large cohort of sequenced exomes paired with EHR.

bioinformatics↗

bioRxiv2020

Glycan processing in the Golgi - optimal information coding and constraints on cisternal number and enzyme specificity

Many proteins that undergo sequential enzymatic modification in the Golgi cisternae are displayed at the plasma membrane as cell identity markers. The modified proteins, called glycans, represent a molecular code. The fidelity of this glycan code is measured by how accurately the glycan synthesis machinery realises the desired target glycan distribution for a particular cell type and niche. In this paper, we quantitatively analyse the tradeoffs between the number of cisternae and the number and specificity of enzymes, in order to synthesize a prescribed target glycan distribution of a certain complexity. We find that to synthesize complex distributions, such as those observed in real cells, one needs to have multiple cisternae and precise enzyme partitioning in the Golgi. Additionally, for fixed number of enzymes and cisternae, there is an optimal level of specificity of enzymes that achieves the target distribution with high fidelity. Our results show how the complexity of the target glycan distribution places functional constraints on the Golgi cisternal number and enzyme specificity.

biophysics↗

bioRxiv2020

Rational design of protein-specific folding modifiers

Protein folding can go wrong in vivo and in vitro, with significant consequences for the living cell and the pharmaceutical industry, respectively. Here we propose a general design principle for constructing small peptide-based protein-specific folding modifiers. We construct a xenonucleus, which is a pre-folded peptide that resembles the folding nucleus of a protein, and demonstrate its activity on the folding of ubiquitin. Using stopped-flow kinetics, NMR spectroscopy, Forster Resonance Energy transfer, single-molecule force measurements, and molecular dynamics simulations, we show that the ubiquitin xenonucleus can act as an effective decoy for the native folding nucleus. It can make the refolding faster by 33 {+/-} 5% at 3 M GdnHCl. In principle, our approach provides a general method for constructing specific, genetically encodable, folding modifiers for any protein which has a well-defined contiguous folding nucleus.

biophysics↗