Biology subjects

Sorokin, A.

Publications and source records attributed to Sorokin, A..

12 recordsLinked to original sources

bioRxiv2025

Protein trafficking and synaptic demand configure complex and dynamic synaptome architectures of individual neurons

Excitatory synapses are the most abundant synapse type in the brain. Being essential for behaviour and are implicated in hundreds of brain disorders, these synapses exhibit striking structural and functional diversity. Synaptome mapping at single-synapse resolution reveals that synaptic protein diversity is spatially organised along the dendritic tree of individual neurons and varies with age and cell-type. However, the cell biological mechanisms underlying the generation of these complex spatial synaptic patterns remain poorly understood. Potential mechanisms include somatic and dendritic protein synthesis, protein trafficking, and local regulatory mechanisms such as activity-dependent degradation. Here we developed computational models to test how combinations of these processes account for empirical synaptome data. We found that a combination of molecular transport mechanisms and local synaptic demand for proteins was sufficient to explain very complex profiles of synaptic protein distributions observed in young, mature and old mice and in different cell types. Our findings suggest the highly complex and dynamic synaptome architecture of the brain is an emergent property of a minimal set of cell biological processes. Our model sets the stage for simulations of brain tissue incorporating molecularly diverse neuronal and synaptic types in a synaptome and connectome architecture.

neuroscience↗

bioRxiv2025

Reprogramming of Cellular Plasticity via ETS and MYC Core-regulatory Circuits During Response to MAPK Inhibition in BRAF-mutant Colorectal Cancer

BackgroundAberrant enhancer dynamics play a critical role in the initiation and progression of colorectal cancer (CRC). BRAFV600E-mutated metastatic CRC may be a unique subtype, exhibiting a strong epigenetic phenotype. Interestingly, bromodomain 2, a reader protein for H3K27ac-marked enhancers, was found to be synthetically lethal in CRC with BRAF + EGFR inhibition. DesignWe evaluated the effectiveness of targeting aberrant enhancers with bromodomain and extraterminal (BET) + MAPK pathway inhibitors in patient-derived xenograft models of metastatic CRC, followed by comprehensive profiling of transcriptomic and chromatin dynamics upon BET inhibitor combination treatment. ResultsThe combination of BET and standard MAPK inhibitors has demonstrated improved efficacy against BRAFV600E CRC and selective improvements against RAS-mutant CRC in vivo. We showed that BET + MAPK inhibition induced a profound downregulation of the MAPK signaling pathway compared to MAPK inhibition alone. The loss of activation signal on enhancers, as determined by H3K27ac, led to dysregulation of core-regulatory circuitries of CRC, especially loss of the auto-regulatory mechanism of the MAPK downstream E26 transformation-specific transcription factor family. Single nucleus multiome (RNA + ATAC) sequencing further distinguished differential transcriptomic and chromatin dynamics at cell type levels. Profound downregulation of well-differentiated cell types confirmed deep inhibition of MAPK signaling and downstream transcription factors. On the other hand, dedifferentiated cell populations were abundant after MAPK or combination inhibition, suggesting therapy-induced cell state switching and adaptation. ConclusionWe are evaluating BET + BRAF + EGFR inhibition in patients with treatment-refractory BRAFV600E metastatic CRC. ClinicalTrial.gov identifier: NCT06102902. What is already known on this topicEnhancer aberrations emerge as critical epigenetic features in the progression of colorectal cancer (CRC). However, the dynamics of active enhancer and the therapeutic potential of enhancer blockade, particularly in CRC tumors with BRAFV600E mutation, is not well understood. What this study addsThis study demonstrates improved efficacy of BET inhibitor combination therapies in diverse patient-derived models and reveals epigenetic reprogramming driven cellular plasticity in BRAFV600E-mutated CRC. How this study might affect research, practice or policyOur findings support treatment with BET + BRAF + EGFR inhibitors for patients with BRAFV600E-mutant mCRC [NCT06102902]. This study also highlights the potential of combining epigenetic agents to standard targeted therapy, offering a novel treatment option for this subset of patients.

cancer biology↗

bioRxiv2025

Adaptive Plasticity Tumor Cells Modulate MAPK-Targeting Therapy Response in Colorectal Cancer

MAPK pathway inhibitors (MAPKi) are increasingly used in the treatment of advanced colorectal cancer, but often produce short-lived responses in patients. Although acquired resistance by de novo mutations in tumors have been found to reduce response in some patients, additional mechanisms underlying the limited response durability of MAPK targeting therapy remain unknown. Here, we denote new contributory tumor biology and provide insight on the impact of tumor plasticity on therapy response. Analysis of MAPKi treated patients revealed activation of stemness programs and increased ASCL2 expression, which are associated with poor outcomes. Greater ASCL2 with MAPKi treatment was also seen in patient-derived CRC models, independent of driver mutations. We find ASCL2 denotes a distinct cell population, arising from phenotypic plasticity, with a proliferative, stem-like phenotype, and decreased sensitivity to MAPKi therapy, which were named adaptive plasticity tumor (APT) cells. MAPK pathway suppression induces the APT phenotype in cells, resulting in APT cell enrichment in tumors and limiting therapy response in preclinical and clinical data. APT cell depletion improved MAPKi treatment efficacy and extended MAPKi response durability in mice. These findings uncover a cellular program that mitigates the impact of MAPKi therapies and highlights the importance of addressing tumor plasticity to improve clinical outcomes.

cancer biology↗

bioRxiv2024

Therapeutic targeting of Syndecan-1 axis overcomes acquired resistance to KRAS-targeted therapy in gastrointestinal cancers

The therapeutic benefit of recently developed mutant KRAS (mKRAS) inhibitors has been limited by the rapid onset of resistance. Here, we aimed to delineate the mechanisms underlying acquired resistance to mKRAS inhibition and identify actionable targets for overcoming this clinical challenge. Previously, we identified Syndecan-1 (SDC1) as a key effector for pancreatic cancer progression whose surface expression is driven by mKRAS. By leveraging both pancreatic and colorectal cancer models, we found that surface SDC1 expression was initially diminished upon mKRAS inhibition, but recovered in tumor cells that bypass mKRAS dependency. Functional studies showed that these tumors depended on SDC1 for survival, further establishing SDC1 as a driver for the acquired resistance to mKRAS inhibition. Mechanistically, we revealed that the YAP1-SDC1 axis was the major driving force for bypassing mKRAS dependency to sustain nutrient salvage machinery and tumor maintenance. Specifically, YAP1 activation mediated the recovery of SDC1 localization on cell surface that sustained macropinocytosis and enhanced the activation of multiple RTKs, promoting resistance to KRAS-targeted therapy. Overall, our study has provided the rationale for targeting the YAP-SDC1 axis to overcome resistance to mKRAS inhibition, thereby revealing new therapeutic opportunities for improving the clinical outcome of patients with KRAS-mutated cancers.

cancer biology↗

bioRxiv2024

Global sensitivity analysis for investigation of bacterial physiology in complex media with FBA-PRCC

In this paper we propose the use of FBA-PRCC approach, which is based on sampling flux space and global sensitivity analysis (GSA), for analysis of the GEM FBA solution space in the nutrient-rich environment. We identify two new modes of interaction between species and metabolites: attraction and avoidance and propose the way of their use. We have shown that sensitivity coefficients provide additional information about behavior of the bacteria in the nutrient-rich environment in comparison to standard knockouts, FVA and CoPE-FBA analysis.

systems biology↗

bioRxiv2023

BioNAR: An Integrated Biological Network Analysis Package in Bioconductor

Biological function in protein complexes emerges from more than just the sum of their parts: Molecules interact in a range of different subcomplexes and transfer signals/information around internal pathways. Modern proteomic techniques are excellent at producing a parts-list for such complexes, but more detailed analysis demands a network approach linking the molecules together and analyzing the emergent architectural properties. Methods developed for the analysis of networks in social sciences have proven very useful for splitting biological networks into communities leading to the discovery of sub-complexes enriched with molecules associated with specific diseases or molecular functions that are not apparent from the constituent components alone. Here we present the Bioconductor package BioNAR which supports step-by-step analysis of biological/biomedical networks with the aim of quantifying and ranking each of the networks vertices based on network topology and clustering. Examples demonstrate that while BioNAR is not restricted to proteomic networks, it can predict a proteins impact within multiple complexes, and enables estimation of the co-occurrence of meta-data, i.e., diseases and functions across the network, identifying the clusters whose components are likely to share common function and mechanisms. The package is available from Bioconductor release 3.16: https://bioconductor.org/packages/release/bioc/html/BioNAR.html Author BiographiesColin McLean holds a PhD in Experimental Particle Physics from the University of Edinburgh. He is currently a Senior Research Fellow in Health Economics and Data Science at the Institute for Genetics and Cancer at the University of Edinburgh. His research interests include applied network and data science in the biomedical domain. Anatoly Sorokin holds PhD Degree in Biophysics and is a Senior computational biologist in the Biological Systems Unit, Okinawa Institute of Science and Technology. His research interests include graph-based analysis, constraint-base, dynamics and rule-based modelling and application areas include systems biology, bioinformatics and microbiomics. Ian Simpson has a DPhil in Genetics (Oxford 2000) and is currently Director of the UKRI Centre for Doctoral Training in Biomedical Artificial Intelligence and a Reader in Biomedical Informatics in the School of Informatics at The University of Edinburgh. His research interests lie at the boundary between Informatics and Biomedicine and focus on jointly modelling molecular and clinical data to improve our understanding of genetic disease. J Douglas Armstrong holds a PhD in Molecular Genetics (Glasgow 1995) and is currently Professor of Systems Neurobiology at the School of Informatics at Edinburgh University. His research interests focus on structure/function mapping in the brains of model organisms. Oksana Sorokina holds a PhD in Systems Biology (Edinburgh 2010) and is a Senior Researcher at the School of Informatics at Edinburgh University. Her expertise is in the computational analysis of complex datasets primarily proteomics and the integration of genetic and other omic data types to understand molecular complexes at the systems biology level.

bioinformatics↗

bioRxiv2023

Combined KRASG12C and SOS1 inhibition enhances and extends the anti-tumor response in KRASG12C-driven cancers by addressing intrinsic and acquired resistance

Efforts to improve the anti-tumor response to KRASG12C targeted therapy have benefited from leveraging combination approaches. Here, we compare the anti-tumor response induced by the SOS1-KRAS interaction inhibitor, BI-3406, combined with a KRASG12C inhibitor (KRASG12Ci) to those induced by KRASG12Ci alone or combined with SHP2 or EGFR inhibitors. In lung cancer and colorectal cancer (CRC) models, BI-3406 plus KRASG12Ci induces an anti-tumor response stronger than that observed with KRASG12Ci alone and comparable to those by the other combinations. This enhanced anti-tumor response is associated with a stronger and extended suppression of RAS-MAPK signaling. Importantly, BI-3406 plus KRASG12Ci treatment delays the emergence of acquired adagrasib resistance in both CRC and lung cancer models and is associated with re-establishment of anti-proliferative activity in KRASG12Ci-resistant CRC models. Our findings position KRASG12C plus SOS1 inhibition therapy as a promising strategy for treating both KRASG12C-mutated tumors as well as for addressing acquired resistance to KRASG12Ci.

cancer biology↗

bioRxiv2020

SBGN Bricks Ontology as a tool to describe recurring concepts in molecular networks

A comprehensible representation of a molecular network is key to communicating and understanding scientific results in systems biology. The Systems Biology Graphical Notation (SBGN) has emerged as the main standard to represent such networks graphically. It has been implemented by different software tools, and is now largely used to communicate maps in scientific publications. However, learning the standard, and using it to build large maps, can be tedious. Moreover, SBGN maps are not grounded on a formal semantic layer and therefore do not enable formal analysis. Here, we introduce a new set of patterns representing recurring concepts encountered in molecular networks, called SBGN bricks. The bricks are structured in a new ontology, the BricKs Ontology (BKO), to define clear semantics for each of the biological concepts they represent. We show the usefulness of the bricks and BKO for both the template-based construction and the semantic annotation of molecular networks. The SBGN bricks and BKO can be freely explored and downloaded at sbgnbricks.org.

systems biology↗

bioRxiv2020

Chromatin State Dynamics Confers Specific Therapeutic Strategies in Enhancer Subtypes of Colorectal Cancer

The extent and function of chromatin state aberrations during colorectal cancer (CRC) progression is not completely understood. Here, by comprehensive epigenomic characterization of 56 tumors, adenomas, and their matched normal tissues, we define the dynamics of chromatin states during the progression of colorectal cancer. H3K27ac-marked active enhancer state could distinguish between different stages of CRC progression. By epigenomic editing, we present evidence that gains of tumor-specific enhancers for crucial oncogenes, such as ASCL2 and FZD10, was crucial for excessive proliferation. Consistently, combination of MEK plus bromodomain (BET) inhibition was found to have synergistic effects in CRC patient-derived xenograft (PDX) models. Probing inter-tumor heterogeneity, we identified four distinct enhancer subtypes (EpiC), three of which correlate well with previously defined transcriptomic subtypes (CMSs). Importantly, CMS2 can be divided into two EpiC subgroups with significant survival differences. Leveraging such correlation, we devised a combinatorial therapeutic strategy of enhancer-blocking bromodomain inhibitors with pathway-specific inhibitors (PARPi, EGFRi, and TGF{beta}i) for three EPIC groups. Our data suggest that the dynamics of active enhancer underlies colorectal cancer progression and the patient-specific active enhancer patterns govern their unique gene expression patterns which can be leveraged for precision combination therapy.

cancer biology↗

bioRxiv2020

Development and optimization of a germination assay and long-term storage for Cannabis sativa pollen

Pollen viability and storage is of great interest to cannabis breeders and researchers to maintain desirable germplasm for future use in breeding or for biotechnological and gene editing applications. Here, we report a simple and efficient cryopreservation method for long-term storage of Cannabis sativa pollen. Additionally, we have deciphered the bicellular nature of cannabis pollen using DAPI staining. We have also standardized a pollen germination assay to assess the viability of cannabis pollen, and found pollen collected from different principal growth stages exhibits different longevity. Finally, we developed a long-term storage method which includes pollen combination with baked whole wheat flower and desiccation under vacuum for cryopreservation. By using this method, we were able to maintain germination viability in liquid nitrogen after 4 months, suggesting potentially indefinite preservation of cannabis pollen.

plant biology↗

bioRxiv2020

Development of transient expression assay for Cannabis sativa which revealed differential Agrobacterium susceptibility among cannabis cultivars

In plant biology, transient expression analysis plays a vital role to provide a fast method to study the gene of interest and subsequently leads the path to develop an improved crop variety with better agronomic traits. In this study, we have reported a rapid and efficient method for transient expression in Cannabis sativa seedlings using Agrobacterium tumefaciens-mediated transformation. A. tumefaciens strain EHA105 carrying the pCAMBIA1301 construct with uidA gene was used to transform cannabis seedlings and the GUS assay was used to detect the uidA expression. A 1% hydrogen peroxide (H2O2) solution was used for both seed sterilization and rapid germination steps. Transient transformation revealed that both cotyledons and young true leaves are amenable to transformation. Comparison to Nicotiana tabacum (tobacco) showed that cannabis seedlings were less susceptible to transformation with Agrobacterium tumefaciens. The susceptibility to Agrobacterium infection also varied with the different cannabis cultivars. The method established in this study has potential to be an important tool for gene-function studies and genetic improvement in cannabis.

molecular biology↗

bioRxiv2019

Evolutionary dynamics of microbial communities in bioelectrochemical systems.

Bio-electrochemical systems can generate electricity by virtue of mature microbial consortia that gradually and spontaneously optimize performance. To evaluate selective enrichment of these electrogenic microbial communities, five, 3-electrode reactors were inoculated with microbes derived from rice wash wastewater and incubated under a range of applied potentials. Reactors were sampled over a 12-week period and DNA extracted from anodal, cathodal, and planktonic bacterial communities was interrogated using a custom-made bioinformatics pipeline that combined 16S and metagenomic samples to monitor temporal changes in community composition. Some genera that constituted a minor proportion of the initial inoculum dominated within weeks following inoculation and correlated with applied potential. For instance, the abundance of Geobacter increased from 423-fold to 766-fold between -350 mV and -50 mV, respectively. Full metagenomic profiles of bacterial communities were obtained from reactors operating for 12 weeks. Functional analyses of metagenomes revealed metabolic changes between different species of the dominant genus, Geobacter, suggesting that optimal nutrient utilization at the lowest electrode potential is achieved via genome rearrangements and a strong inter-strain selection, as well as adjustment of the characteristic syntrophic relationships. These results reveal a certain degree of metabolic plasticity of electrochemically active bacteria and their communities in adaptation to adverse anodic and cathodic environments.

systems biology↗