Biology subjects

Nersisyan, L.

Publications and source records attributed to Nersisyan, L..

8 recordsLinked to original sources

bioRxiv2025

A streamlined nanopore-compatible 5PSeq protocol for rapid phenotypic antimicrobial sensitivity testing

Antimicrobial resistance (AMR) poses a significant threat to public health. Rapid and accurate antimicrobial sensitivity testing is essential to guide effective treatment. Here, we present "simplified 5PSeq" (s5PSeq), a streamlined protocol for profiling 5 monophosphorylated (5P) mRNA degradation intermediates that reflect ribosome dynamics in vivo. By capturing antibiotic-induced, context-specific ribosome stalling events, s5PSeq provides a molecular proxy for bacterial growth inhibition--offering a molecular phenotypic readout without the need for culturing. s5PSeq reduces library preparation time to under four hours and incorporates a novel rRNA blocking strategy. We demonstrated its clinical utility by identifying erythromycin-resistant and sensitive Clostridioides difficile clinical isolates. Combining s5PSeq with real-time nanopore sequencing enables fast AMR diagnosis with as few as 3000 reads. In addition to simplifying the study of 5P co-translational mRNA decay, our work suggests that utilizing information-rich phenotypic molecular readouts can significantly improve AMR diagnostics. HighlightsO_LIs5PSeq is a streamlined protocol for profiling 5P mRNA degradation intermediates. C_LIO_LIContext-specific ribosome stalls can be used to assess phenotypic antimicrobial sensitivity at the molecular level. C_LIO_LIBlocking rRNA sequencing at the ligation step streamlines library preparation and lowers costs and hands-on time. C_LIO_LIIntegration with nanopore sequencing allows same-day antimicrobial sensitivity testing in species with 5-3 exonuclease. C_LI

microbiology↗

bioRxiv2025

Global distribution of honeybee gut microbiome and pesticide-driven adaptations in opportunistic microbial species

Honeybees (Apis mellifera) rely on a specialized gut microbiome shaped by climate, flora, agrochemicals, and dietary supplements. Yet, how these factors alter microbiome composition and function remains unclear. We integrated 16S rRNA and shotgun metagenomics data from eight published studies across six regions, alongside newly generated 16S data from Armenia, to assess how environmental and agrochemical factors influence the honeybee gut microbiome. We also introduced a novel co-abundance and functional analysis pipeline to identify treatment-affected bacterial networks and associated pathways. We observed a stable core of six to twelve phylotypes in amplicon and metagenomic datasets respectively. However, we note significant geographic variation in relative abundances, likely reflecting differences in diet, climate, and local flora. Armenian data revealed distinct seasonal shifts, particularly elevated Commensalibacter in autumn and minor urban-rural differences. Pesticide treatments elicited varying responses: oxalic acid drove pronounced beta-diversity shifts; neonicotinoids had subtler effects, both primarily impacting opportunistic pathogens; and glyphosate disrupted core taxa with stronger effects in newly emerged bees under prolonged exposure. Co-abundance network analysis highlighted that the pesticide-associated community was enriched in adaptive pathways, including potential glyphosate degradation by Pseudomonas, biofilm formation, and aromatic amino acid synthesis. These findings reaffirm the stability of the honeybee core microbiome yet underscore that environmental and anthropogenic stressors induce distinct compositional and functional shifts. We emphasize the need for longitudinal metagenomic approaches that enable high-resolution functional profiling and co-abundance network analysis to clarify how these microbiome shifts impact bee health and colony sustainability.

microbiology↗

bioRxiv2024

The ABCF ATPase New1 resolves translation termination defects associated with specific tRNAArg and tRNALys> isoacceptors in the P site

The efficiency of translation termination is determined by the nature of the stop codon as well as its context. In eukaryotes, recognition of the A-site stop codon and release of the polypeptide are mediated by release factors eRF1 and eRF3, respectively. Translation termination is modulated by other factors which either directly interact with release factors or bind to the E-site and modulate the activity of the peptidyl transferase center. Previous studies suggested that the Saccharomyces cerevisiae ABCF ATPase New1 is involved in translation termination and/or ribosome recycling, however, the exact function remained unclear. Here, we have applied 5PSeq, single-particle cryo-EM and readthrough reporter assays to provide insight into the biological function of New1. We show that the lack of New1 results in ribosomal stalling at stop codons preceded by a lysine or arginine codon and that the stalling is not defined by the nature of the C-terminal amino acid but rather by the identity of the tRNA isoacceptor in the P-site. Collectively, our results suggest that translation termination is inefficient when ribosomes have specific tRNA isoacceptors in the P-site and that the recruitment of New1 rescues ribosomes at these problematic termination contexts.

molecular biology↗

bioRxiv2024

Ribosomes modulate transcriptome abundance via generalized frameshift and out-of-frame mRNA decay.

Cells need to adapt their transcriptome to quickly match cellular needs in changing environments. mRNA abundance can be controlled by altering both its synthesis and decay. Here we show how, in response to poor nutritional conditions, the bulk of the S. cerevisiae transcriptome undergoes -1 ribosome frameshifts and experiences an accelerated out-of-frame co-translational mRNA decay. Using RNA metabolic labelling, we demonstrate that in poor nutritional conditions, NMD-dependent degradation represents at least one third of the total mRNA decay. We further characterize this mechanism and identify low codon optimality as a key factor for ribosomes to induce out-of-frame mRNA decay. Finally, we show that this phenomenon is conserved from bacteria to humans. Our work provides evidence for a direct regulatory feedback mechanism coupling protein demand with the control of mRNA abundance to limit cellular growth and expands the functional role of mRNA quality control.

molecular biology↗

bioRxiv2021

RNA degradation analysis reveals ribosome dynamics in complex microbiome samples

Post-transcriptional regulation is essential for life, yet we are currently unable to investigate its role in complex microbiome samples. Here we discover that co-translational mRNA degradation, where the degradation machinery follows the last translating ribosome, is conserved across prokaryotes. By investigating 5P mRNA decay intermediates, we obtain in vivo ribosome protection information that allows the study of codon and gene specific ribosome stalling in response to stress and drug treatment at single nucleotide resolution. We use this approach to investigate in vivo species-specific ribosome footprints of clinical and environmental microbiomes and show for the first time that ribosome protection patterns can be used to phenotype microbiome perturbations. Our work paves the way for the study of the metatranslatome, and enables the investigation of fast, species-specific, post-transcriptional responses to environmental and chemical perturbations in unculturable microbial communities.

genomics↗

bioRxiv2021

Telomere maintenance pathway activity analysis enables tissue- and gene-level inferences

Telomere maintenance is one of the mechanisms ensuring indefinite divisions of cancer and stem cells. Good understanding of telomere maintenance mechanisms (TMM) is important for studying cancers and designing therapies. However, molecular factors triggering selective activation of either the telomerase dependent (TEL) or the alternative lengthening of telomeres (ALT) pathway are poorly understood. In addition, more accurate and easy-to-use methodologies are required for TMM phenotyping. In this study, we have performed literature based reconstruction of signaling pathways for the ALT and TEL TMMs. Gene expression data were used for computational assessment of TMM pathway activities and compared with experimental assays for TEL and ALT. Explicit consideration of pathway topology makes bioinformatics analysis more informative compared to computational methods based on simple summary measures of gene expression. Application to healthy human tissues showed high ALT and TEL pathway activities in testis, and identified genes and pathways that may trigger TMM activation. Our approach offers a novel option for systematic investigation of TMM activation patterns across cancers and healthy tissues for dissecting pathway-based molecular markers with diagnostic impact.

bioinformatics↗

bioRxiv2020

Fivepseq: analysis of 5' count distribution in RNA-seq datasets for inference on mRNA degradation and translation

In eukaryotes, 5-3 co-translation degradation machinery follows the last translating ribosome providing an in vivo footprint of its position. Thus 5P degradome sequencing, in addition to informing about RNA decay, also provides valuable information regarding ribosome dynamics. Multiple experimental methods have been developed to investigate the mRNA degradome, however computational tools for their reproducible analysis are lacking. Here we present fivepseq: an easy-to-use application for analysis and interactive visualization of 5P degradome data. This tool performs both metagene and gene specific analysis, and allows to easily investigate codon specific ribosome pauses. To demonstrate its ability to provide new biological information, we investigate gene specific ribosome pauses in S. cerevisiae after eIF5A depletion. In addition to identifying pauses at expected codon motifs, we identify multiple genes with strain-specific frameshifts. To show its wide applicability, we investigate more complex 5P degradome from A. thaliana and discover both motif-specific ribosome protection associated with particular developmental stages, as well as generally increased ribosome protection at termination level associated with age. Our work shows how the use of improved analysis tools for the study of 5P degradome can significantly increase the biological information that can be derived from such datasets and facilitate its reproducible analysis. KEY POINTSO_LIAnalysis of 5P degradome data with fivepseq informs about global and gene-specific translational features. C_LIO_LIFrameshifts in translation-related genes in S. cerevisiae may be linked to ribosome stalling. C_LIO_LIRibosome protection at termination and codon motifs are linked to development in A. Thaliana. C_LI

genomics↗

bioRxiv2017

A transcriptome and literature guided algorithm for reconstruction of pathways to assess activity of telomere maintenance mechanisms

Activation of telomere maintenance mechanisms (TMMs) is a crucial factor for indefinite proliferation of cancer cells. The most common TMM is based on the action of telomerase, but in some cancers telomeres are elongated via homologous recombination based alternative mechanism (ALT). Despite their importance, little is known about TMM regulation and factors responsible for TMM phenotype choice in different cells. Currently, many studies address the involvement of few genes in TMMs, but a consensus unified picture of the full process is missing.\n\nWe have developed a computational biology framework combining knowledge- and data-driven approaches to aid in understanding of TMMs. It is based on a greedy algorithm with three core modules: (1) knowledge-based construction/modification of molecular pathways for telomerase-dependent and alternative TMMs, (2) coupled with gene expression data-based validation with an in-house pathway signal flow (PSF) algorithm, and (3) iteration of these two coupled steps until converging at pathway topologies that best reflect state of the art knowledge and are in maximum accordance with the data. We have used gene expression data derived from cell lines and tumor tissues and have performed extensive literature search and multiple cycles of greedy iterations until reaching TMM assessment accuracy of 100% and 77%, respectively.\n\nAvailability of TMM pathways that best reflect recent knowledge and data will facilitate better understanding of TMM processes. As novel experimental findings in TMM biology emerge, and new datasets are generated, our approach may be used to further expand/improve the pathways, possibly allowing for making distinctions not only between telomerase-dependent and ALT TMMs, but also among their different subtypes. Moreover, this method may be used for assessment of TMM phenotypes from gene expression data, which is crucial for studies where experimental detection of TMM states is missing. Furthermore, it can also be used to assess TMM activities in proliferating healthy cells.

bioinformatics↗